The transition of software development from web to cloud has been accelerated. The development of cloud services requires a modeling method that reflects the characteristics of cloud including personalized service, resource sharing service, grouped and distributed services, and crossplatform operability. This study aimed to suggest a method of developing UML-based cloud services suitable for the characteristics of cloud services. A cl oud service metamodel was defined using cloud applications’ characteristic modeling elements, and after that, how these cloud modeling elements are expressed into UML modeling elements was defined with an integrated metamodel between cloud and UML. By applying this hierarchical cloud metamodel, an MDA and MVC-based service-oriented cloud modeling process was established. By doing so, it will be possible to easily design services (applications) and solutions that are suitable for cloud computing environments, and in particular, to create hierarchical reuse models by the level of the abstraction of model-driven development.
SOA for Dynamically Integrated Virtual Learning Environment Systems with Clou...Editor IJCATR
SOA is structural approach for creating services to be reused and shared, so it provides agility and cost saving in software
development by dividing the application into multiple software components to be reused in other systems. Cloud computing is truly scalable
and provide virtualized resources which users can subscribe. Using a cloud and SOA in virtual learning systems provide a great chance for
learners to enhance gained learning outcomes. The adoption of cloud services also assists in reducing the cost of software, hardware, human
resources and infrastructure. This paper will use SOA and cloud computing to transfer virtual learning systems in the cloud to be more
integrated and interoperable through showing a conceptual model of distributed virtual learning system and using cloud computing combined
with services oriented architecture, to contribute in interoperability and integration of e-learning systems in general
Service-oriented computing is meant to support loose relationships between organizations; Serviceoriented
architectures often have the goal to integrate various distributed services of one or more
organizations in a flexible way to be able to quickly react on business changes.
Distributed services provided a new way of distributed computing that achieve the interoperability between
heterogonous application through platform and language independent interfaces. The creation of value
added services by composition of existing ones is gaining a significant momentum. Distributed service
composition is meant to support loose relationships between implemented services in order to provide new
functions. A composite service is the one resulting from the integration, coordination and synchronization
of different service components. In this paper, we generated A Services Composition Model (SCM) that
provides a general solution for the services composition problem by realizing the requirements of a new
service using the requirements of the already existing service. We explained in details all the steps of the
composition process; services registration, services discovery, services selection, services invoking, and
services integration. Although the SCM is not bounded to one particular algorithm to compose services, we
generated an application as an example to test our Service Composition Model.
We also generated the Services Composition Language (SCL) as a simple text-based language which
allows the user to express the requirements of his request, the inserted request will then be analyzed using
our Parsing Algorithm to determine the name of the requested services, after that our Service Composition
Algorithm will execute all the steps of the composition process and return the result of the composition to
the user.
Evolution of Modelling Techniques for Service Oriented ArchitectureIJERA Editor
Service-oriented architecture (SOA) is a software design and architecture design pattern based on independent pieces of software providing functionality as services to other applications. The benefit of SOA in the IT infrastructure is to allow parallel use and data exchange between programs which are services to the enterprise. Unified Modelling Language (UML) is a standardized general-purpose modelling language in the field of software engineering. The UML includes a set of graphic notation techniques to create visual models of object-oriented software systems. We want to make UML available for SOA as well. SoaML (Service oriented architecture Modelling Language) is an open source specification project from the Object Management Group (OMG), describing a UML profile and meta-model for the modelling and design of services within a service-oriented architecture. BPMN was also extended for SOA but there were few pitfalls. There is a need of a modelling framework which dedicated to SOA. Michael Bell authored a framework called Service Oriented Modelling Framework (SOMF) which is dedicated for SOA.
A cloud broker approach with qos attendance and soa for hybrid cloud computin...csandit
Cloud Computing is the industry whose demand has been growing continuously since its
appearance as a solution that offers different types of computing resources as a service over the
Internet. The number of cloud computing providers grows into a run, while the end user is
currently in the position of having many pricing options, distinct features and performance for
the same required service. This work is inserted in the cloud computing task scheduling
research field to hybrid cloud environments with service-oriented architecture (SOA), dynamic
allocation and control of services and QoS requirements attendance. Therefore, it is proposed
the QBroker Architecture, representing a cloud broker with trading features that implement the
intermediation services, defined by the NIST Cloud Computing Reference Model. An
experimental design was created in order to demonstrate compliance to the QoS requirement of
maximum task execution time, the differentiation of services and dynamic allocation of services.
The experimental results obtained by simulation with CloudSim prove that QBroker has the
necessary requirements to provide QoS improvement in hybrid cloud computing environments
based on SOA.
Cloud computing performance evaluation issues and challenges3ijccsa
Cloud Computing makes the dream of computin
g real as a tool and in the form of service. This internet
-
based ongoing technology which has brought flexibility, capacity and power of processing has realized
service
-
oriented idea and has created a new ecosystem in the computing world with its great p
ower and
benefits. Cloud capabilities have been able to move IT industry one step forward. Nowadays, large and
famous enterprise have resorted to cloud computing and have transferred their processing and storage to
it. Due to popularity and progress of clo
ud in different organizations, cloud performance evaluation is of
special importance and this evaluation can help users make right decisions.
In
this paper
,
we
provide an
overall perspective on cloud evaluation criteria and highlight it with help of simula
tion.
For this purpose,
we present different major factors in cloud computing performance and we analyze and evaluate cloud
performance in various scenarios considering these factors.
This document is Priyanka R. Nayak's seminar report on cloud computing submitted to Visvesvaraya Technological University. It discusses key concepts of cloud computing including cyber infrastructure, service-oriented architecture, cloud types (public, private, hybrid), cloud architecture, and cloud components. The report provides an introduction to cloud computing and covers topics such as virtualization and users.
This document discusses dynamic resource allocation using virtual machines. It begins by introducing cloud computing and how it allows scaling of resource usage based on demand through virtualization technology. It then analyzes the existing system of mapping virtual machines to physical resources and proposes an automated resource management system to achieve a balance between overload avoidance and green computing. The key modules of the proposed system are described as the cloud computing module, resource management module, and virtualization module. It further discusses system requirements, feasibility analysis, various UML diagrams including use case diagrams and sequence diagrams, and concludes with describing the software technologies used.
ABSTRACT
In today’s world, the swift increase of utilizing mobile services and simultaneously discovering of the cloud computing services, made the Mobile Cloud Computing (MCC) selected as a wide spread technology among mobile users. Thus, the MCC incorporates the cloud computing with mobile services for achieving facilities in daily using mobile. The capability of mobile devices is limited of computation context, memory capacity, storage ability, and energy. Thus, relying on cloud computing can handle these troubles in the mobile surroundings. Cloud Computing gives computing easiness and capacity such provides availability of services from anyplace through the Internet without putting resources into new foundation, preparing, or application authorizing. Additionally, Cloud Computing is an approach to expand the limitations or increasing the abilities dynamically. The primary favourable position of Cloud Computing is that clients just use what they require and pay for what they truly utilize. Mobile cloud computing is a form for various services, where a mobile gadget is able to utilize the cloud for data saving, seeking, information mining, and multimedia preparing. Cloud computing innovation is also causes many new complications in side of safety and gets to direct when users store significant information with cloud servers. As the clients never again have physical ownership of the outsourced information, makes the information trustworthiness, security, and authenticity insurance in Cloud Computing is extremely difficult and conceivably troublesome undertaking. In MCC environments, it is hard to find a paper embracing most of the concepts and issues such as: architecture, computational offloading, challenges, security issues, authentications and so on. In this paper we discuss these concepts with presenting a review of the most recent papers in the domain of MCC.
SOA for Dynamically Integrated Virtual Learning Environment Systems with Clou...Editor IJCATR
SOA is structural approach for creating services to be reused and shared, so it provides agility and cost saving in software
development by dividing the application into multiple software components to be reused in other systems. Cloud computing is truly scalable
and provide virtualized resources which users can subscribe. Using a cloud and SOA in virtual learning systems provide a great chance for
learners to enhance gained learning outcomes. The adoption of cloud services also assists in reducing the cost of software, hardware, human
resources and infrastructure. This paper will use SOA and cloud computing to transfer virtual learning systems in the cloud to be more
integrated and interoperable through showing a conceptual model of distributed virtual learning system and using cloud computing combined
with services oriented architecture, to contribute in interoperability and integration of e-learning systems in general
Service-oriented computing is meant to support loose relationships between organizations; Serviceoriented
architectures often have the goal to integrate various distributed services of one or more
organizations in a flexible way to be able to quickly react on business changes.
Distributed services provided a new way of distributed computing that achieve the interoperability between
heterogonous application through platform and language independent interfaces. The creation of value
added services by composition of existing ones is gaining a significant momentum. Distributed service
composition is meant to support loose relationships between implemented services in order to provide new
functions. A composite service is the one resulting from the integration, coordination and synchronization
of different service components. In this paper, we generated A Services Composition Model (SCM) that
provides a general solution for the services composition problem by realizing the requirements of a new
service using the requirements of the already existing service. We explained in details all the steps of the
composition process; services registration, services discovery, services selection, services invoking, and
services integration. Although the SCM is not bounded to one particular algorithm to compose services, we
generated an application as an example to test our Service Composition Model.
We also generated the Services Composition Language (SCL) as a simple text-based language which
allows the user to express the requirements of his request, the inserted request will then be analyzed using
our Parsing Algorithm to determine the name of the requested services, after that our Service Composition
Algorithm will execute all the steps of the composition process and return the result of the composition to
the user.
Evolution of Modelling Techniques for Service Oriented ArchitectureIJERA Editor
Service-oriented architecture (SOA) is a software design and architecture design pattern based on independent pieces of software providing functionality as services to other applications. The benefit of SOA in the IT infrastructure is to allow parallel use and data exchange between programs which are services to the enterprise. Unified Modelling Language (UML) is a standardized general-purpose modelling language in the field of software engineering. The UML includes a set of graphic notation techniques to create visual models of object-oriented software systems. We want to make UML available for SOA as well. SoaML (Service oriented architecture Modelling Language) is an open source specification project from the Object Management Group (OMG), describing a UML profile and meta-model for the modelling and design of services within a service-oriented architecture. BPMN was also extended for SOA but there were few pitfalls. There is a need of a modelling framework which dedicated to SOA. Michael Bell authored a framework called Service Oriented Modelling Framework (SOMF) which is dedicated for SOA.
A cloud broker approach with qos attendance and soa for hybrid cloud computin...csandit
Cloud Computing is the industry whose demand has been growing continuously since its
appearance as a solution that offers different types of computing resources as a service over the
Internet. The number of cloud computing providers grows into a run, while the end user is
currently in the position of having many pricing options, distinct features and performance for
the same required service. This work is inserted in the cloud computing task scheduling
research field to hybrid cloud environments with service-oriented architecture (SOA), dynamic
allocation and control of services and QoS requirements attendance. Therefore, it is proposed
the QBroker Architecture, representing a cloud broker with trading features that implement the
intermediation services, defined by the NIST Cloud Computing Reference Model. An
experimental design was created in order to demonstrate compliance to the QoS requirement of
maximum task execution time, the differentiation of services and dynamic allocation of services.
The experimental results obtained by simulation with CloudSim prove that QBroker has the
necessary requirements to provide QoS improvement in hybrid cloud computing environments
based on SOA.
Cloud computing performance evaluation issues and challenges3ijccsa
Cloud Computing makes the dream of computin
g real as a tool and in the form of service. This internet
-
based ongoing technology which has brought flexibility, capacity and power of processing has realized
service
-
oriented idea and has created a new ecosystem in the computing world with its great p
ower and
benefits. Cloud capabilities have been able to move IT industry one step forward. Nowadays, large and
famous enterprise have resorted to cloud computing and have transferred their processing and storage to
it. Due to popularity and progress of clo
ud in different organizations, cloud performance evaluation is of
special importance and this evaluation can help users make right decisions.
In
this paper
,
we
provide an
overall perspective on cloud evaluation criteria and highlight it with help of simula
tion.
For this purpose,
we present different major factors in cloud computing performance and we analyze and evaluate cloud
performance in various scenarios considering these factors.
This document is Priyanka R. Nayak's seminar report on cloud computing submitted to Visvesvaraya Technological University. It discusses key concepts of cloud computing including cyber infrastructure, service-oriented architecture, cloud types (public, private, hybrid), cloud architecture, and cloud components. The report provides an introduction to cloud computing and covers topics such as virtualization and users.
This document discusses dynamic resource allocation using virtual machines. It begins by introducing cloud computing and how it allows scaling of resource usage based on demand through virtualization technology. It then analyzes the existing system of mapping virtual machines to physical resources and proposes an automated resource management system to achieve a balance between overload avoidance and green computing. The key modules of the proposed system are described as the cloud computing module, resource management module, and virtualization module. It further discusses system requirements, feasibility analysis, various UML diagrams including use case diagrams and sequence diagrams, and concludes with describing the software technologies used.
ABSTRACT
In today’s world, the swift increase of utilizing mobile services and simultaneously discovering of the cloud computing services, made the Mobile Cloud Computing (MCC) selected as a wide spread technology among mobile users. Thus, the MCC incorporates the cloud computing with mobile services for achieving facilities in daily using mobile. The capability of mobile devices is limited of computation context, memory capacity, storage ability, and energy. Thus, relying on cloud computing can handle these troubles in the mobile surroundings. Cloud Computing gives computing easiness and capacity such provides availability of services from anyplace through the Internet without putting resources into new foundation, preparing, or application authorizing. Additionally, Cloud Computing is an approach to expand the limitations or increasing the abilities dynamically. The primary favourable position of Cloud Computing is that clients just use what they require and pay for what they truly utilize. Mobile cloud computing is a form for various services, where a mobile gadget is able to utilize the cloud for data saving, seeking, information mining, and multimedia preparing. Cloud computing innovation is also causes many new complications in side of safety and gets to direct when users store significant information with cloud servers. As the clients never again have physical ownership of the outsourced information, makes the information trustworthiness, security, and authenticity insurance in Cloud Computing is extremely difficult and conceivably troublesome undertaking. In MCC environments, it is hard to find a paper embracing most of the concepts and issues such as: architecture, computational offloading, challenges, security issues, authentications and so on. In this paper we discuss these concepts with presenting a review of the most recent papers in the domain of MCC.
Swiftly increasing demand of computational
calculations in the process of business, transferring of files
under certain protocols and data centers force to develop an
emerging technology cater to the services for computational
need, highly manageable and secure storage. To fulfill these
technological desires cloud computing is the best answer by
introducing various sorts of service platforms in high
computational environment. Cloud computing is the most
recent paradigm promising to turn around the vision of
“computing utilities” into reality. The term “cloud
computing” is relatively new, there is no universal agreement
on this definition. In this paper, we go through with different
area of expertise of research and novelty in cloud computing
domain and its usefulness in the genre of management. Even
though the cloud computing provides many distinguished
features, it still has certain sorts of short comings amidst with
comparatively high cost for both private and public clouds. It
is the way of congregating amasses of information and
resources stored in personal computers and other gadgets
and further putting them on the public cloud for serving
users. Resource management in a cloud environment is a
hard problem, due to the scale of modern data centers, their
interdependencies along with the range of objectives of the
different actors in a cloud ecosystem. Cloud computing is
turning to be one of the most explosively expanding
technologies in the computing industry in this era. It
authorizes the users to transfer their data and computation to
remote location with minimal impact on system performance.
With the evolution of virtualization technology, cloud
computing has been emerged to be distributed systematically
or strategically on full basis. The idea of cloud computing has
not only restored the field of distributed systems but also
fundamentally changed how business utilizes computing
today. Resource management in cloud computing is in fact a
typical problem which is due to the scale of modern data
centers, the variety of resource types and their inter
dependencies, unpredictability of load along with the range of
objectives of the different actors in a cloud ecosystem.
DYNAMIC TENANT PROVISIONING AND SERVICE ORCHESTRATION IN HYBRID CLOUDijccsa
The advent of container orchestration and cloud computing, as well as associated security and compliance complexities, make it challenging for the enterprises to develop robust, secure, manageable and extendable architectures which would be applicable to the public and private cloud. The main challenges stem from the fact that on-premises, private cloud and third-party, public cloud services often have seemingly different and sometimes conflicting requirements to tenant provisioning, service deployment, security and compliance and that can lead to rather different architectures which still have a lot of commonalities but evolve independently. Understanding and bridging the functionality gaps between such architectures is highly desirable in terms of common approaches, API/SPI as well as maintainability and extendibility. The authors discuss and propose common architectural approaches to the dynamic tenant provisioning and service orchestration in public, private and hybrid clouds focusing on deployment, security, compliance, scalability and extendibility of stateful Kubernetes runtimes.
URECA Research Paper - Mobile Cloud ComputingAce Zachary
This document discusses mobile cloud computing. It begins by introducing how mobile cloud computing can help address limitations of mobile devices like limited computation power and battery life by offloading processing and data storage to the cloud. It then describes different cloud computing delivery models including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). For mobile cloud computing, it introduces a new model called Network as a Service (NaaS). The document also discusses enabling technologies for mobile cloud computing like HTML5 and cloudlets, as well as advantages such as extended battery life and lower development costs.
This document discusses model-driven architecture (MDA), an approach to system specification and interoperability based on the use of formal models. MDA uses platform-independent models that are translated to platform-specific models using formal rules. Core MDA standards like UML, MOF, XMI, and CWM define the infrastructure. The vision is for nearly seamless interoperability based on shared metadata and formal model translations, with a long-term goal of adaptive object models that can dynamically interpret models at runtime.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
MULTIVIEW SOA : EXTENDING SOA USING A PRIVATE CLOUD COMPUTING AS SAAS AND DAASijseajournal
This work is based on two major areas, the Multiview Service Oriented Architecture and the combination between the computing cloud and MV-SOA. Thus, it is suggested to extend firstly the service oriented architecture (SOA) into an architecture called MV-SOA by adding two components, the Multiview service generator, whose role is to transform the classic service into Multiview service, and the data base, this component seeks to stock all of consumer service information. It is also suggested to combine the computing cloud and Multiview Service Oriented Architecture MVSOA. To reach such combination, the
MVSOA architecture was taken and we added to the client-side a private cloud in SaaS and DaaS.
An Efficient Queuing Model for Resource Sharing in Cloud Computingtheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
360º Degree Requirement Elicitation Framework for Cloud Service ProvidersIJERA Editor
Thisstudy addresses the factors responsible for cloud computing adoption in implementing cloud computing for any organization. Service Level Agreements play a major role for cloud consumer as well as for cloud provider. SLA depends on the requirements gathered by the cloud providers and they vary with the type of organizations for which process is being performed such as education, retail, IT industry etc. SLAs for cloud computing involves technical as well as business requirements which makes the gathering of requirements from stakeholders point of view the heterogeneous process. This research work proposes a 360 degree requirement gathering framework, which reduces the complexitiesduring the process of requirement gathering by cloud service providersas well as SLAs more reliant.
Revenue Maximization with Good Quality of Service in Cloud ComputingINFOGAIN PUBLICATION
Cloud computing enables people to use resources and services without implementing them on their systems. Profit and quality of service is the most important factor for service providers and it is mainly determined by the configuration of a cloud service platform under given market demand. Single long term renting scheme is usually adopted to design a cloud platform which leads to resource waste and having more renting charges. The novel double renting scheme which is combination of short term and long term renting is aiming at existing issue. This double renting scheme will effectively and efficiently promises a good quality of service of all request and reduces the resource waste significantly. It also provides services with lower cost compared to short term renting scheme. It uses optimal queuing model to maximize the profit. That means the users can access the services simultaneously. The main objective of proposed system is, to maximize profit of service provider by providing efficient and effective services to user.
IRJET- Resource Management in Mobile Cloud Computing: MSaaS & MPaaS with Femt...IRJET Journal
This document discusses resource management in mobile cloud computing using Mobile Software as a Service (MSaaS) and Mobile Platform as a Service (MPaaS) with femtocell and Wi-Fi networks. It proposes using femtocell and Wi-Fi private cloud networks to overcome mobile performance issues like limited battery life, storage, and bandwidth. MSaaS and MPaaS can further improve quality of service, pricing, and standard interfaces. The document suggests this approach can effectively manage resources and improve the performance of mobile cloud computing.
Cloud-based augmentation for mobile devices: Motivation, Taxonomy, and Open C...Saeid Abolfazli
Comprehensive Survey on Mobile Cloud Computing. The paper abstract is here:
Recently, Cloud-based Mobile Augmentation (CMA) approaches have gained remarkable ground from academia and industry. CMA is the state-of-the-art mobile augmentation model that employs resource-rich clouds to increase, enhance, and optimize computing capabilities of mobile devices aiming at execution of resource-intensive mobile applications. Augmented mobile devices envision to perform extensive computations and to store big data beyond their intrinsic capabilities with least footprint and vulnerability. Researchers utilize varied cloud-based computing resources (e.g., distant clouds and nearby mobile nodes) to meet various computing requirements of mobile users. However, employing cloud-based computing resources is not a straightforward panacea. Comprehending critical factors (e.g., current state of mobile client and remote resources) that impact on augmentation process and optimum selection of cloud-based resource types are some challenges that hinder CMA adaptability. This paper comprehensively surveys the mobile augmentation domain and presents taxonomy of CMA approaches. The objectives of this study is to highlight the effects of remote resources on the quality and reliability of augmentation processes and discuss the challenges and opportunities of employing varied cloud-based resources in augmenting mobile devices. We present augmentation definition, motivation, and taxonomy of augmentation types, including traditional and cloud-based. We critically analyze the state-of-the-art CMA approaches and classify them into four groups of distant fixed, proximate fixed, proximate mobile, and hybrid to present a taxonomy. Vital decision making and performance limitation factors that influence on the adoption of CMA approaches are introduced and an exemplary decision making flowchart for future CMA approaches are presented. Impacts of CMA approaches on mobile computing is discussed and open challenges are presented as the future research directions.
A Novel Framework for Reliable and Fault Tolerant Web ServicesAbhishek Kumar
This document proposes a novel framework for providing reliable and fault tolerant web services. The framework uses replication and a replication manager to select a primary web service from among multiple replicas. When the primary web service fails or becomes unavailable, the replication manager switches to a new primary by updating the WSDL registration to ensure uninterrupted service for consumers. The replication manager continuously monitors the web services and can trigger recovery, reconfiguration or restart processes to maintain reliability. The proposed approach aims to achieve high performance and reliability for web services.
Exploring the cloud deployment and service delivery modelscloudresearcher
This document summarizes cloud computing deployment and service delivery models. It describes common cloud deployment models including private clouds for internal use, public clouds for external use, hybrid clouds combining public and private, and community clouds for specific groups. It also outlines emerging models like combined and inter clouds. For service delivery, it defines the main models of Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), explaining the level of control users have and examples of each.
"A Highly Decoupled Front-end Framework for High Trafficked Web Applications"...Prem Gurbani
This document summarizes a paper that proposes a new front-end framework architecture for high-traffic web applications. The framework aims to decouple layers to improve scalability, flexibility, and development efficiency. It proposes producing JSON data on the server and caching reusable components on the client to reduce bandwidth. This allows parallel development and minimizes dependencies between teams.
With a rapid growth of the mobile applications and development of cloud computing concept, mobile cloud
computing (MCC) has been introduced to be a potential technology for mobile services. MCC integrates the cloud
computing into the mobile environment and overcomes obstacles related to the performance, security etc discussed in
mobile computing. This paper gives an overview of the MCC including the definition, architecture, and applications. The
issues, existing solutions and approaches are presented.
Semantic Web: A Study on Web Service Composition Approachesijtsrd
A Web service is a collection of open protocols and standards used for exchanging data between applications and systems. Web Service discovery, selection and composition are the important tasks of the any automated business processes. In a web service composition set of web services are collectively executed to achieve the objectives. This study reveals the existing approaches used for web service composition in both syntactic and semantic environments. We have reviewed more than 40 articles in this domain and concluded with merits and demerits of the methodologies applied for the implementation of the web service composition. Michael Raj TF, | Siva Prakasam. P"Semantic Web: A Study on Web Service Composition Approaches" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-4 , June 2017, URL: http://www.ijtsrd.com/papers/ijtsrd115.pdf http://www.ijtsrd.com/computer-science/world-wide-web/115/semantic-web-a-study-on-web-service-composition-approaches/michael-raj-tf-
Cloud computing is the fastest emerging technology and a novel buzzword in the field of IT domain that offer distinct services, applications and focuses on providing sustainable, reliable, scalable and virtualized resources to its consumer. The main aim of cloud computing is to enhance the use of distributed resources to achieve higher throughput and resource utilization in large-scale computation problems. Scheduling affects the efficiency of cloud and plays a significant role in cloud computing to create high performance environment. The Quality of Service (QoS) requirements of user application define the scheduling of resources. Numbers of researchers have tried to solve these scheduling problems using different QoS based scheduling techniques. In this paper, a detail analysis of resource scheduling methodology is presented, with different types of scheduling based on soft computing techniques, their comparisons, benefits and results are discussed. Major finding of this paper helps researchers to decide suitable approach for scheduling user’s applications considering their QoS requirements.
1) The document proposes a modeling approach for sensor-based, service-oriented business processes. It uses the Unified Modeling Language (UML) to model processes from high-level enterprise problems to low-level detailed processes.
2) The modeling approach is implemented using the Business Process Execution Language (BPEL) and analyzes business process integration between enterprises.
3) The proposed approach aims to improve process integration and interface between enterprises by exchanging necessary information to carry out activities according to the business process model in a peer-to-peer manner.
On Optimal and Fair Service Allocation in Mobile Cloud ComputingReza Rahimi
This document proposes MapCloud, a framework for optimal service allocation in mobile cloud computing. It uses a 2-tier cloud architecture with local and public clouds to balance factors like delay, cost, and scalability. MapCloud models mobile applications and quality of service using location-time workflows. It introduces an algorithm called MuSIC that allocates services for single-user or group applications in a way that optimizes factors like power consumption and delay based on user mobility patterns. The document outlines MapCloud's features and provides diagrams of its architecture and workflow.
This document discusses applying Agile principles to develop cloud applications through Agile Service Networks (ASN). It begins by defining cloud computing categories like Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). Requirements for cloud applications are then outlined, including additiveness, security, reliability, and being consumer-centric. Agile Manifesto principles of prioritizing individuals/interaction over processes/tools and working software over documentation are introduced. Key features of ASNs like being collaborative, emergent, dynamic and business-oriented are described. The document proposes that by combining ASNs with Agile principles, cloud application requirements can be mapped and fulfilled in
Model-Driven Architecture for Cloud Applications Development, A survey Editor IJCATR
Model Driven Architecture and Cloud computing are among the most important paradigms in software service engineering now a days. As cloud computing continues to gain more activities, more issues and challenges for many systems with its dynamic usage are introduced. Model Driven Architecture (MDA) approach for development and maintenance becomes an evident choice for ensuring software solutions that are robust, flexible and agile for developing applications.
This paper aims to survey and analyze the research issues and challenges that have been emerging in cloud computing applications with a focus on using Model Driven architecture (MDA) development. We discuss the open research issues and highlight future research problems.
Model-Driven Architecture for Cloud Applications Development, A surveyEditor IJCATR
Model Driven Architecture and Cloud computing are among the most important paradigms in software service engineering
now a days. As cloud computing continues to gain more activities, more issues and challenges for many systems with its dynamic usage
are introduced. Model Driven Architecture (MDA) approach for development and maintenance becomes an evident choice for ensuring
software solutions that are robust, flexible and agile for developing applications.
This paper aims to survey and analyze the research issues and challenges that have been emerging in cloud computing applications with
a focus on using Model Driven architecture (MDA) development. We discuss the open research issues and highlight future research
problems.
Swiftly increasing demand of computational
calculations in the process of business, transferring of files
under certain protocols and data centers force to develop an
emerging technology cater to the services for computational
need, highly manageable and secure storage. To fulfill these
technological desires cloud computing is the best answer by
introducing various sorts of service platforms in high
computational environment. Cloud computing is the most
recent paradigm promising to turn around the vision of
“computing utilities” into reality. The term “cloud
computing” is relatively new, there is no universal agreement
on this definition. In this paper, we go through with different
area of expertise of research and novelty in cloud computing
domain and its usefulness in the genre of management. Even
though the cloud computing provides many distinguished
features, it still has certain sorts of short comings amidst with
comparatively high cost for both private and public clouds. It
is the way of congregating amasses of information and
resources stored in personal computers and other gadgets
and further putting them on the public cloud for serving
users. Resource management in a cloud environment is a
hard problem, due to the scale of modern data centers, their
interdependencies along with the range of objectives of the
different actors in a cloud ecosystem. Cloud computing is
turning to be one of the most explosively expanding
technologies in the computing industry in this era. It
authorizes the users to transfer their data and computation to
remote location with minimal impact on system performance.
With the evolution of virtualization technology, cloud
computing has been emerged to be distributed systematically
or strategically on full basis. The idea of cloud computing has
not only restored the field of distributed systems but also
fundamentally changed how business utilizes computing
today. Resource management in cloud computing is in fact a
typical problem which is due to the scale of modern data
centers, the variety of resource types and their inter
dependencies, unpredictability of load along with the range of
objectives of the different actors in a cloud ecosystem.
DYNAMIC TENANT PROVISIONING AND SERVICE ORCHESTRATION IN HYBRID CLOUDijccsa
The advent of container orchestration and cloud computing, as well as associated security and compliance complexities, make it challenging for the enterprises to develop robust, secure, manageable and extendable architectures which would be applicable to the public and private cloud. The main challenges stem from the fact that on-premises, private cloud and third-party, public cloud services often have seemingly different and sometimes conflicting requirements to tenant provisioning, service deployment, security and compliance and that can lead to rather different architectures which still have a lot of commonalities but evolve independently. Understanding and bridging the functionality gaps between such architectures is highly desirable in terms of common approaches, API/SPI as well as maintainability and extendibility. The authors discuss and propose common architectural approaches to the dynamic tenant provisioning and service orchestration in public, private and hybrid clouds focusing on deployment, security, compliance, scalability and extendibility of stateful Kubernetes runtimes.
URECA Research Paper - Mobile Cloud ComputingAce Zachary
This document discusses mobile cloud computing. It begins by introducing how mobile cloud computing can help address limitations of mobile devices like limited computation power and battery life by offloading processing and data storage to the cloud. It then describes different cloud computing delivery models including Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). For mobile cloud computing, it introduces a new model called Network as a Service (NaaS). The document also discusses enabling technologies for mobile cloud computing like HTML5 and cloudlets, as well as advantages such as extended battery life and lower development costs.
This document discusses model-driven architecture (MDA), an approach to system specification and interoperability based on the use of formal models. MDA uses platform-independent models that are translated to platform-specific models using formal rules. Core MDA standards like UML, MOF, XMI, and CWM define the infrastructure. The vision is for nearly seamless interoperability based on shared metadata and formal model translations, with a long-term goal of adaptive object models that can dynamically interpret models at runtime.
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
MULTIVIEW SOA : EXTENDING SOA USING A PRIVATE CLOUD COMPUTING AS SAAS AND DAASijseajournal
This work is based on two major areas, the Multiview Service Oriented Architecture and the combination between the computing cloud and MV-SOA. Thus, it is suggested to extend firstly the service oriented architecture (SOA) into an architecture called MV-SOA by adding two components, the Multiview service generator, whose role is to transform the classic service into Multiview service, and the data base, this component seeks to stock all of consumer service information. It is also suggested to combine the computing cloud and Multiview Service Oriented Architecture MVSOA. To reach such combination, the
MVSOA architecture was taken and we added to the client-side a private cloud in SaaS and DaaS.
An Efficient Queuing Model for Resource Sharing in Cloud Computingtheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
360º Degree Requirement Elicitation Framework for Cloud Service ProvidersIJERA Editor
Thisstudy addresses the factors responsible for cloud computing adoption in implementing cloud computing for any organization. Service Level Agreements play a major role for cloud consumer as well as for cloud provider. SLA depends on the requirements gathered by the cloud providers and they vary with the type of organizations for which process is being performed such as education, retail, IT industry etc. SLAs for cloud computing involves technical as well as business requirements which makes the gathering of requirements from stakeholders point of view the heterogeneous process. This research work proposes a 360 degree requirement gathering framework, which reduces the complexitiesduring the process of requirement gathering by cloud service providersas well as SLAs more reliant.
Revenue Maximization with Good Quality of Service in Cloud ComputingINFOGAIN PUBLICATION
Cloud computing enables people to use resources and services without implementing them on their systems. Profit and quality of service is the most important factor for service providers and it is mainly determined by the configuration of a cloud service platform under given market demand. Single long term renting scheme is usually adopted to design a cloud platform which leads to resource waste and having more renting charges. The novel double renting scheme which is combination of short term and long term renting is aiming at existing issue. This double renting scheme will effectively and efficiently promises a good quality of service of all request and reduces the resource waste significantly. It also provides services with lower cost compared to short term renting scheme. It uses optimal queuing model to maximize the profit. That means the users can access the services simultaneously. The main objective of proposed system is, to maximize profit of service provider by providing efficient and effective services to user.
IRJET- Resource Management in Mobile Cloud Computing: MSaaS & MPaaS with Femt...IRJET Journal
This document discusses resource management in mobile cloud computing using Mobile Software as a Service (MSaaS) and Mobile Platform as a Service (MPaaS) with femtocell and Wi-Fi networks. It proposes using femtocell and Wi-Fi private cloud networks to overcome mobile performance issues like limited battery life, storage, and bandwidth. MSaaS and MPaaS can further improve quality of service, pricing, and standard interfaces. The document suggests this approach can effectively manage resources and improve the performance of mobile cloud computing.
Cloud-based augmentation for mobile devices: Motivation, Taxonomy, and Open C...Saeid Abolfazli
Comprehensive Survey on Mobile Cloud Computing. The paper abstract is here:
Recently, Cloud-based Mobile Augmentation (CMA) approaches have gained remarkable ground from academia and industry. CMA is the state-of-the-art mobile augmentation model that employs resource-rich clouds to increase, enhance, and optimize computing capabilities of mobile devices aiming at execution of resource-intensive mobile applications. Augmented mobile devices envision to perform extensive computations and to store big data beyond their intrinsic capabilities with least footprint and vulnerability. Researchers utilize varied cloud-based computing resources (e.g., distant clouds and nearby mobile nodes) to meet various computing requirements of mobile users. However, employing cloud-based computing resources is not a straightforward panacea. Comprehending critical factors (e.g., current state of mobile client and remote resources) that impact on augmentation process and optimum selection of cloud-based resource types are some challenges that hinder CMA adaptability. This paper comprehensively surveys the mobile augmentation domain and presents taxonomy of CMA approaches. The objectives of this study is to highlight the effects of remote resources on the quality and reliability of augmentation processes and discuss the challenges and opportunities of employing varied cloud-based resources in augmenting mobile devices. We present augmentation definition, motivation, and taxonomy of augmentation types, including traditional and cloud-based. We critically analyze the state-of-the-art CMA approaches and classify them into four groups of distant fixed, proximate fixed, proximate mobile, and hybrid to present a taxonomy. Vital decision making and performance limitation factors that influence on the adoption of CMA approaches are introduced and an exemplary decision making flowchart for future CMA approaches are presented. Impacts of CMA approaches on mobile computing is discussed and open challenges are presented as the future research directions.
A Novel Framework for Reliable and Fault Tolerant Web ServicesAbhishek Kumar
This document proposes a novel framework for providing reliable and fault tolerant web services. The framework uses replication and a replication manager to select a primary web service from among multiple replicas. When the primary web service fails or becomes unavailable, the replication manager switches to a new primary by updating the WSDL registration to ensure uninterrupted service for consumers. The replication manager continuously monitors the web services and can trigger recovery, reconfiguration or restart processes to maintain reliability. The proposed approach aims to achieve high performance and reliability for web services.
Exploring the cloud deployment and service delivery modelscloudresearcher
This document summarizes cloud computing deployment and service delivery models. It describes common cloud deployment models including private clouds for internal use, public clouds for external use, hybrid clouds combining public and private, and community clouds for specific groups. It also outlines emerging models like combined and inter clouds. For service delivery, it defines the main models of Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS), explaining the level of control users have and examples of each.
"A Highly Decoupled Front-end Framework for High Trafficked Web Applications"...Prem Gurbani
This document summarizes a paper that proposes a new front-end framework architecture for high-traffic web applications. The framework aims to decouple layers to improve scalability, flexibility, and development efficiency. It proposes producing JSON data on the server and caching reusable components on the client to reduce bandwidth. This allows parallel development and minimizes dependencies between teams.
With a rapid growth of the mobile applications and development of cloud computing concept, mobile cloud
computing (MCC) has been introduced to be a potential technology for mobile services. MCC integrates the cloud
computing into the mobile environment and overcomes obstacles related to the performance, security etc discussed in
mobile computing. This paper gives an overview of the MCC including the definition, architecture, and applications. The
issues, existing solutions and approaches are presented.
Semantic Web: A Study on Web Service Composition Approachesijtsrd
A Web service is a collection of open protocols and standards used for exchanging data between applications and systems. Web Service discovery, selection and composition are the important tasks of the any automated business processes. In a web service composition set of web services are collectively executed to achieve the objectives. This study reveals the existing approaches used for web service composition in both syntactic and semantic environments. We have reviewed more than 40 articles in this domain and concluded with merits and demerits of the methodologies applied for the implementation of the web service composition. Michael Raj TF, | Siva Prakasam. P"Semantic Web: A Study on Web Service Composition Approaches" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-1 | Issue-4 , June 2017, URL: http://www.ijtsrd.com/papers/ijtsrd115.pdf http://www.ijtsrd.com/computer-science/world-wide-web/115/semantic-web-a-study-on-web-service-composition-approaches/michael-raj-tf-
Cloud computing is the fastest emerging technology and a novel buzzword in the field of IT domain that offer distinct services, applications and focuses on providing sustainable, reliable, scalable and virtualized resources to its consumer. The main aim of cloud computing is to enhance the use of distributed resources to achieve higher throughput and resource utilization in large-scale computation problems. Scheduling affects the efficiency of cloud and plays a significant role in cloud computing to create high performance environment. The Quality of Service (QoS) requirements of user application define the scheduling of resources. Numbers of researchers have tried to solve these scheduling problems using different QoS based scheduling techniques. In this paper, a detail analysis of resource scheduling methodology is presented, with different types of scheduling based on soft computing techniques, their comparisons, benefits and results are discussed. Major finding of this paper helps researchers to decide suitable approach for scheduling user’s applications considering their QoS requirements.
1) The document proposes a modeling approach for sensor-based, service-oriented business processes. It uses the Unified Modeling Language (UML) to model processes from high-level enterprise problems to low-level detailed processes.
2) The modeling approach is implemented using the Business Process Execution Language (BPEL) and analyzes business process integration between enterprises.
3) The proposed approach aims to improve process integration and interface between enterprises by exchanging necessary information to carry out activities according to the business process model in a peer-to-peer manner.
On Optimal and Fair Service Allocation in Mobile Cloud ComputingReza Rahimi
This document proposes MapCloud, a framework for optimal service allocation in mobile cloud computing. It uses a 2-tier cloud architecture with local and public clouds to balance factors like delay, cost, and scalability. MapCloud models mobile applications and quality of service using location-time workflows. It introduces an algorithm called MuSIC that allocates services for single-user or group applications in a way that optimizes factors like power consumption and delay based on user mobility patterns. The document outlines MapCloud's features and provides diagrams of its architecture and workflow.
This document discusses applying Agile principles to develop cloud applications through Agile Service Networks (ASN). It begins by defining cloud computing categories like Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). Requirements for cloud applications are then outlined, including additiveness, security, reliability, and being consumer-centric. Agile Manifesto principles of prioritizing individuals/interaction over processes/tools and working software over documentation are introduced. Key features of ASNs like being collaborative, emergent, dynamic and business-oriented are described. The document proposes that by combining ASNs with Agile principles, cloud application requirements can be mapped and fulfilled in
Model-Driven Architecture for Cloud Applications Development, A survey Editor IJCATR
Model Driven Architecture and Cloud computing are among the most important paradigms in software service engineering now a days. As cloud computing continues to gain more activities, more issues and challenges for many systems with its dynamic usage are introduced. Model Driven Architecture (MDA) approach for development and maintenance becomes an evident choice for ensuring software solutions that are robust, flexible and agile for developing applications.
This paper aims to survey and analyze the research issues and challenges that have been emerging in cloud computing applications with a focus on using Model Driven architecture (MDA) development. We discuss the open research issues and highlight future research problems.
Model-Driven Architecture for Cloud Applications Development, A surveyEditor IJCATR
Model Driven Architecture and Cloud computing are among the most important paradigms in software service engineering
now a days. As cloud computing continues to gain more activities, more issues and challenges for many systems with its dynamic usage
are introduced. Model Driven Architecture (MDA) approach for development and maintenance becomes an evident choice for ensuring
software solutions that are robust, flexible and agile for developing applications.
This paper aims to survey and analyze the research issues and challenges that have been emerging in cloud computing applications with
a focus on using Model Driven architecture (MDA) development. We discuss the open research issues and highlight future research
problems.
Model-Driven Architecture for Cloud Applications Development, A surveyEditor IJCATR
Model Driven Architecture and Cloud computing are among the most important paradigms in software service engineering
now a days. As cloud computing continues to gain more activities, more issues and challenges for many systems with its dynamic usage
are introduced. Model Driven Architecture (MDA) approach for development and maintenance becomes an evident choice for ensuring
software solutions that are robust, flexible and agile for developing applications.
This paper aims to survey and analyze the research issues and challenges that have been emerging in cloud computing applications with
a focus on using Model Driven architecture (MDA) development. We discuss the open research issues and highlight future research
problems.
WiSANCloud: a set of UML-based specifications for the integration of Wireless...Priscill Orue Esquivel
Giving the current trend to combine the advantages of Wireless Sensor and Actor Networks (WSANs) with the Cloud Computing technology, this work proposes a set of specifications, based on the Unified Modeling Language - UML, in order to provide the general framework for the design of the integration of said components. One of the keys of the integration is the architecture of the WSAN, due to its structural relationship with the Cloud in the definition of the combination. Regarding the standard applied in the integration, UML and its subset, Systems Modeling Language - SysML , are proposed by the Object Management Group - OMG to deal with cloud applications; so, this indicates the starting point of the process of the design of specifications for WSAN-Cloud Integration. Based on the current state of UML tools for analysis and design, there are several aspects to take into account in order to define the integration process.
Task Performance Analysis in Virtual Cloud EnvironmentRSIS International
Cloud computing based applications are beneficial for
businesses of all sizes and industries as they don’t have to invest
a huge amount on initial setup. This way, businesses can opt for
Cloud services and can implement innovative ideas. But
evaluating the performance of provisioning (e.g. CPU scheduling
and resource allocation) policies in a real Cloud computing
environment for different application techniques is challenging
because clouds show dynamic demands, workloads, supply
patterns, VM sizes, and resources (hardware, software, and
network). User’s requests and services requirements are
heterogeneous and dynamic. Applications models have
unpredictable performance, workloads, and dynamic scaling
requirements. So a demand for a Simulation toolkit for Cloud is
there. Cloudsim is self-contained simulation framework that
provides simulation and modeling of Cloud-based application in
lesser time with lesser efforts. In this paper we tried to simulate
the task performance of a cloudlet using one data center, one
VM. We also developed a Graphical User Interface to
dynamically change the simulation parameters and show
simulation results.
AN OPEN JACKSON NETWORK MODEL FOR HETEROGENEOUS INFRASTRUCTURE AS A SERVICE O...IJCNCJournal
Cloud computing is an environment which provides services for user demand such as software, platform, infrastructure. Applications which are deployed on cloud computing have become more varied and complex to adapt to increase end-user quantity and fluctuating workload. One popular characteristic of
cloud computing is the heterogeneity of network, hosts and virtual machines (VM). There were many studies on cloud computing modeling based on queuing theory, but most studies have focused on homogeneity characteristic. In this study, we propose a cloud computing model based on open Jackson
network for multi-tier application systems which are deployed on heterogeneous VMs of IaaS cloud computing. The important metrics are analyzed in our experiments such as mean waiting time; mean request quantity, the throughput of the system. Besides that, metrics in model is used to modify number VMs
allocated for applications. Result of experiments shows that open queue network provides high efficiency.
Challenges and solutions in Cloud computing for the Future InternetSOFIProject
This document discusses two projects - REMICS and Cloud4Trends - that address challenges in cloud computing. REMICS develops a model-driven methodology for migrating legacy applications to cloud services and addresses interoperability issues. It focuses on providing a domain-specific language for abstracting cloud deployment complexity and solving behavioral and data interoperability. Cloud4Trends leverages cloud infrastructure for real-time trend detection in social media streams, providing a scalable solution for analyzing large-scale data. It detects variations and trends using a cloud computing service developed by the VENUS-C project.
ADVANCES IN HIGHER EDUCATIONAL RESOURCE SHARING AND CLOUD SERVICES FOR KSAIJCSES Journal
This document summarizes research on cloud computing services and resource sharing for higher education in Saudi Arabia. It discusses several frameworks and tools for evaluating cloud migration options, including decision support systems that allow users to select suitable cloud providers based on their requirements. Case studies on cloud adoption in various fields like healthcare, oil and gas, and education are also reviewed. The document concludes that cloud computing provides opportunities to reduce costs while improving access to resources, but security, reliability and control issues must be considered during migration planning.
A CLOUD BROKER APPROACH WITH QOS ATTENDANCE AND SOA FOR HYBRID CLOUD COMPUTIN...cscpconf
Cloud Computing is the industry whose demand has been growing continuously since its appearance as a solution that offers different types of computing resources as a service over the Internet. The number of cloud computing providers grows into a run, while the end user is currently in the position of having many pricing options, distinct features and performance for the same required service. This work is inserted in the cloud computing task scheduling research field to hybrid cloud environments with service-oriented architecture (SOA), dynamic allocation and control of services and QoS requirements attendance. Therefore, it is proposed the QBroker Architecture, representing a cloud broker with trading features that implement the intermediation services, defined by the NIST Cloud Computing Reference Model. An experimental design was created in order to demonstrate compliance to the QoS requirement of maximum task execution time, the differentiation of services and dynamic allocation of services. The experimental results obtained by simulation with CloudSim prove that QBroker has the necessary requirements to provide QoS improvement in hybrid cloud computing environments based on SOA.
Resource usage optimization in cloud based networksDimo Iliev
This document provides a literature review and background research on resource usage optimization in cloud-based networks. It discusses several approaches to optimization including operational optimizations, cloud virtualization, emerging concepts, quality-of-service and service level agreements, traffic differentiation, cloud federation, and resource scheduling. The research aims to develop a prototype solution that combines these approaches and tools to improve efficiency of resource usage in cloud environments.
Location-aware deep learning-based framework for optimizing cloud consumer q...IJECEIAES
The expanding propensity of organization users to utilize cloud services urges to deliver services in a service pool with a variety of functional and non-functional attributes from online service providers. brokers of cloud services must intense rivalry competing with one another to provide quality of service (QoS) enhancements. Such rivalry prompts a troublesome and muddled providing composite services on the cloud using a simple service selection and composition approach. Therefore, cloud composition is considered a non-deterministic polynomial (NP-hard) and economically motivated problem. Hence, developing a reliable economic model for composition is of tremendous interest and to have importance for the cloud consumer. This paper provides “A location-aware deep learning framework for improving the QoS-based service composition for cloud consumers”. The proposed framework is firstly reducing the dimensions of data. Secondly, it applies a combination of the deep learning long short-term memory network and particle swarm optimization algorithm additionally to considering the location parameter to correctly forecast the QoS provisioned values. Finally, it composes the ideal services need to reduce the customer cost function. The suggested framework's performance has been demonstrated using a real dataset, proving that it superior the current models in terms of prediction and composition accuracy.
Cloud service ranking with an integration of k-means algorithm and decision-m...IJECEIAES
The present research focuses on ranking cloud services by using the k-means algorithm with multi-criteria decision-making (MCDM) approaches that are the prime factor in the decision-making process and have been used to choose cloud services. The tools offered by MCDM can solve almost any decision-making problem. When faced with a selection challenge in the cloud environment, the trusted party would need to weigh the client’s choice against a predetermined list of criteria. There is a wide range of approaches to evaluating the quality of cloud services. The deep learning model has been considered a branch of artificial intelligence that assesses datasets to perform training and testing and makes decisions accordingly. This paper presents a concise overview of MCDM approaches and discusses some of the most commonly used MCDM methods. Also, a model based on deep learning with the k-means algorithm based decision-making trial and evaluation laboratory (kDE-MATEL) and analytic network process (ANP) is proposed as k-means algorithm based decision-making trial and evaluation laboratory with analytic network process (kD-ANP) for selecting cloud services. The proposed model uses the k-means algorithm and gives different levels of priority and weight to a set of criteria. A traditional model is also compared with a proposed model to reflect the efficiency of the proposed approach.
A Case Study on Academic Services Application Using Agile Methodology for Mob...IJRES Journal
Recently, Mobile Cloud Computing reveals many modern development areas in the Information
Technology industry. Several software engineering frameworks and methodologies have been developed to
provide solutions for deploying cloud computing resources on mobile application development. Agile
methodology is one of the most commonly used methodologies in the field. This paper presents the MCCAS a
Web and Mobile application that provide feature for the Palestinian higher education/academic institutions. An
Agile methodology was used in the development of the MCCAS but in parallel with emphasis on Cloud
computing resources deployment. Also many related issues is discussed such as how software engineering
modern methodologies (advances) influenced the development process.
The document discusses cloud computing projects for final year students based on 2011-2012 IEEE papers. It provides an overview of cloud computing concepts like SaaS, PaaS, IaaS and virtualization. It then lists over 30 potential cloud computing project topics derived from recent IEEE papers covering areas like load balancing, security, storage management, and network management. It outlines the training and methodology that will be used for the projects including requirements gathering, design, development, testing and documentation review. Contact details are provided to inquire about these cloud computing final year projects.
Web Services Based Information Retrieval Agent System for Cloud ComputingEditor IJCATR
This document proposes a framework for an information retrieval agent system using web services in a cloud computing environment. The system would allow users to search for medical information from a private medical cloud. Hospitals and clinics in the cloud provide web services with information about specialists and doctors. The proposed multi-agent system would let patients search for information by day, time, doctor name, clinic, or disease. It would include interface, information, and reasoning agents. The interface agent would receive queries, format them, pass them to the information agent, and return results. The information agent would search cloud databases and retrieve results. The reasoning agent would analyze results and return the most relevant to the interface agent.
A Literature Review On The Readiness For Providing Cloud Services Locally In ...Amanda Summers
This document provides a literature review on the readiness for providing cloud services locally in Yemen. It discusses cloud computing concepts, features, and models including infrastructure as a service, platform as a service, and software as a service. The document also examines cloud adoption in other countries and identifies factors to consider for cloud readiness such as understanding network infrastructure capabilities and classifying sensitive data. Finally, the challenges of security and privacy for cloud computing services are addressed.
Cloud computing evolved from earlier computing technologies and paradigms like client-server computing and service-oriented computing. It delivers scalable computing resources and services remotely via private, public, or hybrid clouds. Cloud computing components include infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS). Service-oriented computing (SOC) provides a model for cloud computing by defining services that can be loosely connected across platforms and organizations. SOC and cloud computing have a reciprocal relationship where SOC provides computing as a service and cloud computing provides services for computing.
A Journey to the Future of Cloud-native Media MicroservicesWashington Cabral
The impact of digital transformation on media
and entertainment (M&E) sector is reshaping traditional
media services and the way solution vendors think, design
and market their products. Audience consuming habits shifts
from traditional, linear viewing hours, to pervasive, any time,
any device, any location patterns, broadcasters find
themselves on a hard track to keep up their infrastructure
with a consumption model that defies both operational and
business models.
This document discusses various computing paradigms such as fog computing, cloud computing, edge computing, mobile cloud computing, and fog-based computing. It provides an overview of fog computing, describing its layered architecture and comparing it to similar paradigms like cloud and edge computing. Some key points discussed include:
- Fog computing enhances cloud computing by extending services and resources to the network edge, supporting low-latency applications.
- It has a 3-layer architecture with end devices, fog nodes, and cloud layers, placing resources closer to end users than the cloud.
- Characteristics of fog computing include low latency, mobility support, location awareness, and decentralized storage and analytics.
- Challen
Similar to A service-oriented cloud modeling method and process (20)
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
Embedded machine learning-based road conditions and driving behavior monitoringIJECEIAES
Car accident rates have increased in recent years, resulting in losses in human lives, properties, and other financial costs. An embedded machine learning-based system is developed to address this critical issue. The system can monitor road conditions, detect driving patterns, and identify aggressive driving behaviors. The system is based on neural networks trained on a comprehensive dataset of driving events, driving styles, and road conditions. The system effectively detects potential risks and helps mitigate the frequency and impact of accidents. The primary goal is to ensure the safety of drivers and vehicles. Collecting data involved gathering information on three key road events: normal street and normal drive, speed bumps, circular yellow speed bumps, and three aggressive driving actions: sudden start, sudden stop, and sudden entry. The gathered data is processed and analyzed using a machine learning system designed for limited power and memory devices. The developed system resulted in 91.9% accuracy, 93.6% precision, and 92% recall. The achieved inference time on an Arduino Nano 33 BLE Sense with a 32-bit CPU running at 64 MHz is 34 ms and requires 2.6 kB peak RAM and 139.9 kB program flash memory, making it suitable for resource-constrained embedded systems.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Neural network optimizer of proportional-integral-differential controller par...IJECEIAES
Wide application of proportional-integral-differential (PID)-regulator in industry requires constant improvement of methods of its parameters adjustment. The paper deals with the issues of optimization of PID-regulator parameters with the use of neural network technology methods. A methodology for choosing the architecture (structure) of neural network optimizer is proposed, which consists in determining the number of layers, the number of neurons in each layer, as well as the form and type of activation function. Algorithms of neural network training based on the application of the method of minimizing the mismatch between the regulated value and the target value are developed. The method of back propagation of gradients is proposed to select the optimal training rate of neurons of the neural network. The neural network optimizer, which is a superstructure of the linear PID controller, allows increasing the regulation accuracy from 0.23 to 0.09, thus reducing the power consumption from 65% to 53%. The results of the conducted experiments allow us to conclude that the created neural superstructure may well become a prototype of an automatic voltage regulator (AVR)-type industrial controller for tuning the parameters of the PID controller.
An improved modulation technique suitable for a three level flying capacitor ...IJECEIAES
This research paper introduces an innovative modulation technique for controlling a 3-level flying capacitor multilevel inverter (FCMLI), aiming to streamline the modulation process in contrast to conventional methods. The proposed
simplified modulation technique paves the way for more straightforward and
efficient control of multilevel inverters, enabling their widespread adoption and
integration into modern power electronic systems. Through the amalgamation of
sinusoidal pulse width modulation (SPWM) with a high-frequency square wave
pulse, this controlling technique attains energy equilibrium across the coupling
capacitor. The modulation scheme incorporates a simplified switching pattern
and a decreased count of voltage references, thereby simplifying the control
algorithm.
A review on features and methods of potential fishing zoneIJECEIAES
This review focuses on the importance of identifying potential fishing zones in seawater for sustainable fishing practices. It explores features like sea surface temperature (SST) and sea surface height (SSH), along with classification methods such as classifiers. The features like SST, SSH, and different classifiers used to classify the data, have been figured out in this review study. This study underscores the importance of examining potential fishing zones using advanced analytical techniques. It thoroughly explores the methodologies employed by researchers, covering both past and current approaches. The examination centers on data characteristics and the application of classification algorithms for classification of potential fishing zones. Furthermore, the prediction of potential fishing zones relies significantly on the effectiveness of classification algorithms. Previous research has assessed the performance of models like support vector machines, naïve Bayes, and artificial neural networks (ANN). In the previous result, the results of support vector machine (SVM) were 97.6% more accurate than naive Bayes's 94.2% to classify test data for fisheries classification. By considering the recent works in this area, several recommendations for future works are presented to further improve the performance of the potential fishing zone models, which is important to the fisheries community.
Electrical signal interference minimization using appropriate core material f...IJECEIAES
As demand for smaller, quicker, and more powerful devices rises, Moore's law is strictly followed. The industry has worked hard to make little devices that boost productivity. The goal is to optimize device density. Scientists are reducing connection delays to improve circuit performance. This helped them understand three-dimensional integrated circuit (3D IC) concepts, which stack active devices and create vertical connections to diminish latency and lower interconnects. Electrical involvement is a big worry with 3D integrates circuits. Researchers have developed and tested through silicon via (TSV) and substrates to decrease electrical wave involvement. This study illustrates a novel noise coupling reduction method using several electrical involvement models. A 22% drop in electrical involvement from wave-carrying to victim TSVs introduces this new paradigm and improves system performance even at higher THz frequencies.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Determination of Equivalent Circuit parameters and performance characteristic...pvpriya2
Includes the testing of induction motor to draw the circle diagram of induction motor with step wise procedure and calculation for the same. Also explains the working and application of Induction generator
A high-Speed Communication System is based on the Design of a Bi-NoC Router, ...DharmaBanothu
The Network on Chip (NoC) has emerged as an effective
solution for intercommunication infrastructure within System on
Chip (SoC) designs, overcoming the limitations of traditional
methods that face significant bottlenecks. However, the complexity
of NoC design presents numerous challenges related to
performance metrics such as scalability, latency, power
consumption, and signal integrity. This project addresses the
issues within the router's memory unit and proposes an enhanced
memory structure. To achieve efficient data transfer, FIFO buffers
are implemented in distributed RAM and virtual channels for
FPGA-based NoC. The project introduces advanced FIFO-based
memory units within the NoC router, assessing their performance
in a Bi-directional NoC (Bi-NoC) configuration. The primary
objective is to reduce the router's workload while enhancing the
FIFO internal structure. To further improve data transfer speed,
a Bi-NoC with a self-configurable intercommunication channel is
suggested. Simulation and synthesis results demonstrate
guaranteed throughput, predictable latency, and equitable
network access, showing significant improvement over previous
designs
This presentation is about Food Delivery Systems and how they are developed using the Software Development Life Cycle (SDLC) and other methods. It explains the steps involved in creating a food delivery app, from planning and designing to testing and launching. The slide also covers different tools and technologies used to make these systems work efficiently.
Applications of artificial Intelligence in Mechanical Engineering.pdfAtif Razi
Historically, mechanical engineering has relied heavily on human expertise and empirical methods to solve complex problems. With the introduction of computer-aided design (CAD) and finite element analysis (FEA), the field took its first steps towards digitization. These tools allowed engineers to simulate and analyze mechanical systems with greater accuracy and efficiency. However, the sheer volume of data generated by modern engineering systems and the increasing complexity of these systems have necessitated more advanced analytical tools, paving the way for AI.
AI offers the capability to process vast amounts of data, identify patterns, and make predictions with a level of speed and accuracy unattainable by traditional methods. This has profound implications for mechanical engineering, enabling more efficient design processes, predictive maintenance strategies, and optimized manufacturing operations. AI-driven tools can learn from historical data, adapt to new information, and continuously improve their performance, making them invaluable in tackling the multifaceted challenges of modern mechanical engineering.
We have designed & manufacture the Lubi Valves LBF series type of Butterfly Valves for General Utility Water applications as well as for HVAC applications.
Impartiality as per ISO /IEC 17025:2017 StandardMuhammadJazib15
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This study Examines the Effectiveness of Talent Procurement through the Imple...DharmaBanothu
In the world with high technology and fast
forward mindset recruiters are walking/showing interest
towards E-Recruitment. Present most of the HRs of
many companies are choosing E-Recruitment as the best
choice for recruitment. E-Recruitment is being done
through many online platforms like Linkedin, Naukri,
Instagram , Facebook etc. Now with high technology E-
Recruitment has gone through next level by using
Artificial Intelligence too.
Key Words : Talent Management, Talent Acquisition , E-
Recruitment , Artificial Intelligence Introduction
Effectiveness of Talent Acquisition through E-
Recruitment in this topic we will discuss about 4important
and interlinked topics which are
AI in customer support Use cases solutions development and implementation.pdfmahaffeycheryld
AI in customer support will integrate with emerging technologies such as augmented reality (AR) and virtual reality (VR) to enhance service delivery. AR-enabled smart glasses or VR environments will provide immersive support experiences, allowing customers to visualize solutions, receive step-by-step guidance, and interact with virtual support agents in real-time. These technologies will bridge the gap between physical and digital experiences, offering innovative ways to resolve issues, demonstrate products, and deliver personalized training and support.
https://www.leewayhertz.com/ai-in-customer-support/#How-does-AI-work-in-customer-support
2. Int J Elec & Comp Eng ISSN: 2088-8708
A service-oriented cloud modeling method and process (Chee-Yang Song)
963
a design pattern for relating the user interface, function process and data structure separately. Using both
MDA and MVC patterns may improve reusability of model by creating a modular, independent model.
This study aimed to suggest a service-oriented cloud metamodel and modeling process for
developing applications that reflect the characteristics of cloud, and support hierarchical modeling using
MDA and MVC from early cloud requirements to architecture design to deployment. An MDA approach
defines development phases and task activities with CIM, PIM and PSM depending on the level of
the abstraction of development. First, a metamodel is defined to express the characteristics of cloud well.
Based on the metamodel, a cloud development process is established [5]. This study suggests a service-
oriented development methodology based on the characteristics of cloud services, and a hierarchical
development process using an MDA approach based on the modeling elements of the developed metamodel.
The rest of this paper is organized as follows. Section 2 analyzes the MDA based software and cloud
development methods from relevant studies. Section 3 deals with the service-oriented cloud metamodel.
Section 4 describes a design method for the service-oriented modeling framework and process using
these metamodels. Section 5 applies the proposed modeling process to the PDMCS system. In Section 6,
a comparison with existing methods is discussed.
2. RELATED WORK
2.1. MDA web-based software
There has been a lot of research on model transformation as a development method of MDA based
web application (software). Let's look at the existing methods of converting a CIM model into a PIM model
to develop a web application by using MDA. In [6], based on the MDA, it addressed the model
transformation of the BPMN model at CIM level to the use case model and class model (with MVC
expression) at PIM level. The transformation rule between models was implemented in the atras
transformation language (ATL). Rhazali et. al [7] proposed a method for converting the CIM activity model
into a web model of PIM use case model and class model, and then into SoaML and interaction flow
modeling language (IFML). In [8], it addressed a method for converting a CIM business model to a PIM web
model. That is, the business model expressed as the activity model is transformed into the web model which
is the use case model. In [9], it provided the model transformation of the CIM E3value model to the PIM
IFML model. It suggested the automatic transformation between models by applying ATL transformation
rules based on the metamodel. In this paper, MDA approach will be used for defining a model-based layered
cloud modeling process
2.2. Cloud service development method
For the development of UML-based cloud applications, CAML (Cloud Application Modeling
Language) [10] expanded from a UML deployment model is used to expresses cloud applications with
component models and deployment topologies based on the patterns of the model driven architecture (MDA).
This, however, does not include an early phase of defining requirements, meets some characteristics of cloud
services only, and does not provide a method that considers security. For this reason, it is not easy to use
CAML in reality. Kamali et al [11] develops cloud applications by identifying and designing nine
requirements for designing, executing and managing cloud applications. As this method is limited to
deployment modeling only, this does not support the overall modeling process for cloud applications.
For the development of feature-based cloud applications, Hwang et al [12] suggested a software development
methodology for multi-tenant SaaS cloud services (SCoD: SaaS Cloud-oriented Development). Since this
development method considers tenant-focused cloud features only, it is difficult to use it for general purposes
as a feature-based, not object-based, cloud development process. Benfenatki et al [13] Suggested, as an agile
methodology based on service-oriented architecture (SOA), a cloud application development methodology,
called MADONA (Methodology for Automatic Development of clOud-based busiNess Application),
that encompasses several processes from specifying requirements to combining, implementing and deploying
services. However, since this method is based on reuse, that is, a development method focused on identifying
and combining services, this does not provide a UML-based development method for developing new cloud
services. For the development of architecture-oriented cloud applications, Hamdaqa et al [14] suggested
a cloud software architecture for designing cloud applications as a metamodel. Establishment of SaaS cloud
services [15] is similar to the development of SOA-based applications, which has processes including
analysis, design, development and transformation
Among cloud service development cases, Zhang et al [16] suggested an architecture design process
and domain-specific architecture description language for developing cloud robotic systems. One of
the commercial cloud service development methods is Cloud Native Application development in PaaS
(CNAPS) [17], a cloud development methodology for PaaS services characterized by microservice
3. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 10, No. 1, February 2020 : 962 - 977
964
architecture and domain-driven designs. CNAPS is an incremental model composed of the phases of defining
requirements and architecture, domain-driven design, agile model-driven development (MDD), sustainable
development, integrated test and system implementation.
Meanwhile, many studies have been conducted on porting existing applications to cloud
applications. Existing UML models are transformed into cloud services after being converted into
SOA-based models. Sabiri and Benabbou [18] suggested a method of porting an existing application or
component to a cloud application, but this is also not for developing a new cloud application. [19] Introduced
an abstract model for standard application programming interface (API) to secure compatibility between
different clouds. The model suggested 8 common and standard API services and developed APIs using UML,
and the developed API was applied to Amazon’s EC2 and Google’s AppEngine, which indicates that this
model is for the development of standard APIs, not for the development of cloud applications. Jagli and
Yeddu [20] suggested Cloud SaaS SDLC (Software Development Life Cycle) that is suitable for
the development of cloud applications, and this covered the life cycle model for the cloud development phase
only. Some earlier studies were conducted on the types of cloud services to be established [21-22].
3. RESULTS SERVICE-ORIENTED CLOUD METAMODEL
To develop services that reflect the characteristics and policies of cloud, this study defined
a metamodel with modeling elements required for modeling from defining requirements at an early phase to
designing an architecture for grouping distributed deployments. Depending on the phase of development,
a modeling process was established using these modeling elements. In this chapter, a feature-based
metamodel for developing a cloud service and its elements were defined.
3.1. Cloud service metamodel
A metamodel for developing a cloud service needs to be composed of the characteristic elements of
requirements that this service need to have. In addition, the features of cloud need to be considered from
the perspective of design and implementation. From the perspective of design, there are features like security
(privacy etc.), resource sharing (group management, distributed management, change management), tenant-
base and self-service, and from the perspective of implementation, features such as dynamic environments,
various media and on-demand measured service are included.
Based on these characteristic elements, a cloud service metamodel (CSM) is defined as shown in
Figure 1. First, elements that are essential and common in a cloud service such as SaaS, PaaS, IaaS, DaaS
(Database) and XaaS are identified as a delivery type (or model), and its characteristics such as
resource_sharing, tenent_service, and self_service are extracted. Requirements that a cloud service needs to
meet are composed of business-processes and components as a function, and security as a non-function.
In addition, execution_environment (including media_independent) for the implementation of services, and
in particular synchronization that is important for sharing resources are identified, and cloud_policy for
implementing a cloud service, and cloud_model and cloud_property (function_property, security_property)
for implementing based on this policy are identified.
In terms of the relations between the elements of cloud modeling, since the elements of
cloud_service including service_name, service_definition, user, delivery_type, operation_type and use_type
are essential components, their relations are expressed with aggregation and composition. On the other hand,
the relation between cloud_service and cloud_policy is that of realization because cloud_policy is an element
for realizing the service. In addition, to provide hierarchical approaches depending on the level of
the abstraction of development, the modeling elements of a cloud service need to be hierarchized using
the MDA method. In other words, based on the level of patterns of CIM (domain-commonality, thin solid
line box), PIM (domain customizability, platform non-specific-commonality, thick dotted line box), and PSM
(platform specific-variability, thick solid line box), the components of a cloud service metamodel are
hierarchized and defined. For example, modeling elements including cloud_service, service_name,
service_difinition, delivery_type, use_type and cloud_policy are involved in the CIM modeling level;
function_property and security_property, in the PIM modeling level; and modeling elements (detailed
algorithm, protocol) including cloud_model, component, cloud_mechanism, SLA_monitor (Service Level
Aggreement) and synchronization, in the PSM modeling level. When modeling a cloud application,
an application model can be generated in an easy and accurate manner by using the modeling elements of this
cloud service metamodel and the relations between them. In addition, it is possible to create a cloud model by
the level of the abstraction of development, which improves the reusability of the model.
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Figure 1. A cloud service metamodel for designing cloud application: CSM
For the standardized specification of modeling elements of a unit “cloud service,” the elements are
defined according to the method of defining data elements (classification standard and attribute specification)
in the Metadata Registry (MDR, ISO/IEC 11179) standard [23-25]. Table 1 shows the definition of the cloud
service specification (or attribute specification) of a unit cloud service that have key common elements that
are directly involved, focusing on the elements of “Cloud_service” in the cloud service metamodel. That is,
the modeling elements in the CIM level that are directly involved in “cloud_service” in the metamodel in
Figure 1 are defined. Therefore, the cloud service specifies the attributes that the service needs to have
according to the format in Table 1, which can be utilized to search and share the cloud service by doing so.
3.2. OCL definition of cloud modeling elements
In order to clearly express the constraints of the cloud modeling elements defined in the metamodel,
OCL (Object Constraint Language) [26-27] is used, because the metamodel expressed as a class model does
not fully express the meaning of modeling elements themselves and the constraints between them in
a graphic way due to its non-standardized specification. The attribute profile of modeling elements in Table 1
is also stated in natural language, which contains ambiguity. For this reason, the syntactic relations of
modeling elements and the profile of attributes are not clearly stated in the class model. Therefore, invariant
conditions that modeling elements have, pre/post conditions and other constraints need to be added to define
the modeling elements in a clear and specific manner. For example, Figure 2 shows the specification of
the modeling element of “Cloud_service” in the cloud service metamodel as shown in Figure 1 written in
OCL. The specification converted from the class model to OCL maps the class model to a context, attributes
to types, and operation to operation. The specification written in OCL expresses operation by declaring
the types of constants or variables that use inv and using pre/ post/ let. As shown in Figure 2, since there is
only one name of the cloud service and one type of the model, which is unchangeable, it is expressed as “1”
in the declaration of the type.
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Table 1. Cloud service specification (attribute specification) of unit cloud service
Cloud service property (CIM) Cloud service definition
Identifying
Attributes
Service_name Name of a cloud service
Service_definition
(foundation)
Specification of common properties of cloud services
- Describe the functions, staus of fuctions, and semantics of functions provided by
the service
Service_user Users who use cloud services
- Related to the realization of tenant-base
Domain_task The name of the upper domain and task to which the cloud service belongs.
- Domain, application area
Cloud_policy
- Function policy
- Security policy
The policy on how to provide and manage Shared Services Assets, ie, guidelines and
regulations (Resource policy, Service Level Agreement service area policy, legal
policy, payment policy, etc.)
- Functional goals that this service must meet
- The security objectives that this service must meet (non-functional)
Authentification, privacy(confidentiality), integrity, availability, access control,
non-repudiation
Business process Business flow or scenario of a cloud service
Delivery
Attributes
Delivery_type Choice of cloud service delivery type: SaaS, PaaS, IaaS
Opearation_type Select the type of target that provides cloud service: Public_cloud, Private_cloud,
Hybrid_cloud
Use
Attributes
Pre_condition Conditions that must be satisfied before the execution of the cloud service
Post_condition Conditions that must be satisfied after the implementation of the cloud service
Fee The fee for using this cloud service
Figure 2. An OCL specification for the “Cloud_service” modeling element
3.3. An integrated metamodel between cloud and UML
Normally, business applications are designed using unified modeling language (UML), a universal
language, for developing software, and thus cloud applications are modeled using UML. Therefore,
the modeling elements of the cloud service in Figure 1 need to be expressed with the elements of a UML
model. The Integrated Metamodel of mapping Cloud into UML design (IMCU) in Figure 3 shows
the connected modeling between cloud modeling and UML modeling. Figure 3 shows how the application
model of cloud can be established into a UML model through a three-layered modeling approach. The UML
model on the right side is the function-security integrated metamodel suggested by [28], and the cloud model
(gray box) on the left side is the one that was newly defined based on Figure 1 in this study. Mutual mapping
between these models is defined based on the realization relation between modeling elements. The cloud
requirement modeling marked in gray on the left side is the one that this study suggests.
The composition of the IMCU is defined by identifying the key elements of individual metamodels
associated with cloud modeling and UML modeling (for example, “class” in the class model), and connecting
modeling elements between models and elements in each modeling phase in a vertical (materialization of
models) and horizontal (relation between cloud and UML mapping) manner. The IMCU is hierarchized
according to the MDA-based CIM, PIM and PIM modeling levels in order to establish a cloud application
model by the level of the abstraction of development.
Horizontal mapping between cloud modeling and UML-based modeling is expressed with
the relations of the cloud elements that give constraints (function, non-function) to UML elements.
In the CIM level, use cases that express functions in an early use case model for UML modeling are
the elements that compose cloud_service in cloud modeling, and thus the relation between them is
the realization relation. This means that a unit cloud service is expressed as a use case of UML, and is
realized later. In the PIM level, since classes in the class model need to meet the attributes of cloud, their
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relation with cloud_property is the realization relation. In the PSM level, the cloud model is realized as
a component model by assembling components, which is the realization relation. As a modeling element for
specifying systems in the PSM level, certain component types, in this study spring (spring frameworks) and
COM+, were expressed in UML modeling, and certain cloud sites, in this study Google’s AppEngine and
Amazon’s EC2, were expressed in cloud modeling.
Figure 3. The integrated metamodel of harmonizing cloud into UML design: IMCU
4. SERVICE-ORIENTED CLOUD MODELING PROCESS
In this chapter, a service-oriented cloud modeling process is established using the metamodel
(chapter 3) according to the life cycle of cloud development. To do so, a conceptual modeling framework is
defined, and the structure and behavior models of the cloud development process are defined in detail based
on the framework. For the metamodel-based definition of development process, task activities in each
modeling phase are performed using the modeling elements of the hierarchical metamodel in chapter 3
according to the MDA paradigm. By doing so, the productivity of development can be improved, and
the development process can be easily used. Meanwhile, the design of the suggested cloud modeling process
has the following principles: multi-tenant-focused customized service (specified as service user in the cloud
service specification); cloud service-oriented; architecture-focused (specifying the type of deployment in
a deployment model); and reuse-oriented (MDA approach).
4.1. Cloud service modeling framework
The software development process (methodology) is defined with methods (or paradigms) and
processes. This development process has incremental and repeated development paradigms, and development
phases and task activities are performed in order. That is, the approaching method between development
phases has an incremental and repeated life cycle, which allows to continuously improve and expand
the created model. Based on this approaching method, the framework of the general cloud development
process was defined as shown in Figure 4. This framework is defined as a two-dimensional structure
composed of the function and non-function requirements of the cloud application service from a vertical
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perspective, and modeling phase based on MDD (Model Driven Development) that has time concept from
a horizontal perspective. Therefore, the cloud service modeling process is defined with three development
phases: cloud requirement definition phase (CIM level), cloud analysis phase (PIM level) and cloud design
phase (PSM level). Each phase can be modeled hierarchically using the cloud service metamodel CSM,
Figure 1 and the integrated metamodel IMCU, Figure 3.
Figure 4. A modeling process framework for cloud service: MPF
4.2. Service-oriented cloud modeling process
Based on the cloud service modeling framework MPF, Figure 4, detailed development process
models are obtained as follows: SM-CMP (Structural Model for Cloud Modeling Process) as shown in
Figure 5, and BM-CMP (Behavioral Model for Cloud Modeling Process (skipped for lack of space).
The structural model for modeling process expresses task activities required during the development process,
and the behavioral model (skipped for lack of space) shows the implementation of activities in
the development process.
Modeling phases are composed of multiple task activities, and outputs are generated as
the outcomes of the activities. The activities are modeling tasks associated with the function and non-function
(security, performance, reliability, etc.) of cloud. As an example, Definition 4-1 shows the definition of task
activities in the development phase not the definition of modeling phase (set of activities). Definition 4-1
(Cloud modeling activity). A cloud modeling activity of cloud analysis phase CMA = (n, Role, Input, Task,
→, WP, Criteria) consists of: (1) the modeling activity’s name n (Identify cloud attribute identify, Make
analysis class model, Build analysis sequence model); (2) the role and responsibility of modeling activity
Role (function analyst); (3) the required input for modeling activity (use case model, cloud service
specification); (4) a finite-set Task of tasks s, t, r CMA, where the task can contain options ([Task]) or can
be mandatory (Task), and where a cloud model should be built as an artifact using the work
product of the previous task as well as the modeling elements in the metamodel; (5) a transition
relation (Task x Task), where contains the relation type of previous/after and fork/join among
the tasks; (6) the output or work product WP of a task; and (7) Initiation and end criteria for initiating and
finishing this task.
The overall process of cloud application modeling is as follows. In the phase of defining cloud
requirements, requirements are expressed with a use case model, and associated use cases are grouped to
identify unit cloud services, and to write the specification of each cloud service. To specify the service model
in detail, class models (function structural models), and sequence models (implementation models) for each
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use case included within a unit cloud service are written in the cloud analysis phase. In the cloud design
phase in which architectures and specific mechanisms are established considering implementation
environments, classes are grouped to generate components, and cloud application component models are
created. Unit cloud services are generated with components associated with use cases included within a unit
service that is defined in the requirement definition phase. The internal design of components is performed
using multiple class models.
Figure 5. A structural model for cloud modeling process: SM-CMP
Here, the relations between modeling elements can differ depending on granularity, but they can be
set as follows:
- Identifying unit cloud services with more than one use case
- Writing class and sequence models for unit cloud services
(If the size of a service is big, models can be written for each use case within each service.)
- Generating components with more than one use case within a service
- Forming services with components, and components with classes
In the cloud requirement definition phase (CIM-level), for generating cloud domain models in
Figure 5, requirements and policies that are necessary for independently developing cloud applications are
established in target domains. Task activities in this phase include “definition of requirements” of functions
and non-functions; “writing function models based on use cases” and “writing cloud service specifications.”
Here, the specific task activities for “writing function models based on use cases” include “writing use case
models” and “writing use case specifications.” When writing cloud service specifications, the policies of
cloud, that is, the function and non-function (security, etc.) policies of cloud are specified.
For requirements for functions, use case models are written, and “use case specifications” are
written for one use case. After that, based on functional similarity, associated use cases are combined to
identify unit cloud services and to specify each service in detail through cloud service specifications.
Here, high-level cloud policies are also defined. For tasks involved in “defining requirements,”
the requirements of cloud applications are analyzed and identified by tenant based on commonality and
variability [12]. In use case models, use cases that have an “extend” relation between use cases shows
the requirements of variability, while the rest use cases show the requirements of commonality. Cloud service
specification are written based on Table 1. Unit cloud services are identified using a use case-based method
[29], but their types are selected according the granularity of services.
In the cloud analysis phase (PIM-level) for establishing cloud attribute models, cloud attribute
models for unit cloud services (or the size of use cases), the outputs of the requirement definition phase,
are written independently in a development platform by identifying and adding cloud attributes in class
models and sequence models using the MVC method based on the use case and cloud service specifications.
In other words, the function and non-function attributes of cloud are defined based on the already-defined
cloud policies. The attributes are reflected and expressed in the class and sequence models in the form of
stereotypes in the PIM level of the metamodel using the modeling elements. The reason why one class model
and sequence model are created for a unit cloud service is to generate service-oriented analysis models, and
to secure the size of models in the case when the size of use cases is small.
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Lastly, in the cloud design phase (PSM-level), resource-sharing distributed or C/S (Client/Server)
cloud architecture models are established and the inner structure of cloud classes are designed to define cloud
deployment and cloud delivery models by adding implementation environments. First, a system architecture
is expressed as a deployment model, and an application architecture is expressed as a component model.
A unit cloud service defined in the CIM level is expanded and expressed using the notation of deployment
models. Components included in a unit cloud service are deployed and expressed within nodes, and are
grouped to express the service and components together within nodes using the stereotype of
<<Unit_Cloud_Service>>. Models are designed to provide the cloud computing service by mounting
the components that independently function within the architecture model, and the cloud service in which
these components are combined and converted into an executable file. By doing so, service-oriented cloud
applications can be established. After that, class models and sequence models based on internal cloud
attributes to which implementation environments are added are defined. In addition, the protocol and
algorithm of cloud are designed in class operations.
5. CASE STUDY
In order to demonstrate the effectiveness of the proposed method, practices are conducted and
deliverables by activities are described based on the procedures of the SM-CMP in Figure 5 targeting
the Personal Data Management Service (PDMCS) system. At this time, the conversion and mapping between
the UML models are as described in [28]. That is, the transformation mapping between modeling elements
over modeling phases is applied the method in [28]. Each activity is conducted to do modeling by using
modeling elements of CSM metamodel as shown in Figure 1, UML metamodels [5], and IMCU metamodel
as shown in Figure 3 hierarchized by development phases. The PDMCS system is a system to manage
processes of supporting storage capacity support, conducting synchronization and backup, providing email
and folder management services. In this case, the design on a multi-tenant service for data storage, folder
management and synchronization functions is performed. Deliverables of this case are seen in use case model
and cloud service specification at the CIM cloud requirement definition phase, class model and sequence
model at the PIM cloud analysis phase, and the component model and deployment model at the PSM cloud
design phase.
5.1. Cloud requirement definition for PDMCS system (CIM)
The modeling work in the cloud requirement definition phase as shown in Figure 5 create a domain
model of the PDMCS system as a use case model, identify the unit cloud services based on the use case, and
specify the cloud policy for these services. Shown in Figure 6 is a use case model that consists of
the requirement functions for this system: account, folder, capacity, file, synchronization, and so on. For how
the cloud’s characteristics in Figure 1 are represented in the identified use cases in Figure 6, the "account"
use case represents the cloud personalization service of the "Tenant_base" and "Self_service" modeling
elements. The "charge" use case represents "Usage_based_payment", and the "folder_share" use case
expresses the cloud characteristic of "Resource_sharing" modeling element respectively. Through this model,
commonality and variability also can be identified by relationship type between use cases. That is, use cases
that have an "extend" relationship between use cases are identified as requirement functions of variability.
In other words, "folder_share", "synchronization (back-up)", "charge" use cases are variability functions and
the remaining use cases mean common functions. Next, based on conceptual similarity of functions, use
cases are grouped to identify unit cloud services. As a result, the "account_management",
"folder_management", "file_management", "payment_management", and "capacity_management" are
identified as unit cloud services and they are expressed in package notation. For instance,
the "Account_management" unit cloud service is a group of use cases for account, login, security (SSO:
Single Sign On). Next, in order to specify unit cloud services, cloud service specification is written by using
the attribute specification with cloud in Table 1. As an example, the cloud service specification for unit
"folder" cloud service is shown in Table 2. In table 2, the cloud policy for the "folder" cloud service may
have functional-policy and non-functional-policy, as shown in the modeling elements in Figure 1. That is,
these include resource policy (computer, network, storage, firewall, etc.), Service Level Agreement (SLA),
security policy, and payment policy. For instance, the "Provide folder service only to account person
registered in the cloud." sentence describes security policy of this cloud service. This is shown on how
the “Authentication” security policy of the "account" use case is specified by cloud service specification in
detail. In other words, this is shown by mapping the characteristics of the cloud in Figure 3 to UML elements.
That is, "Non-Function_policy" of "cloud_policy" is expressed into UML "useCase" modeling element.
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5.2. Cloud analysis for PDMCS system (PIM)
In the cloud analysis phase as shown in Figure 5, the functional models that is composed of the class
model and the sequence model as analysis model of PDMCS are specified in detail based on the cloud
service specification asshown in Table 2, deliverable from prior phase by the MVC pattern at the PIM level
independently of the platform environment. Here, one class model and one sequence model are written for
one cloud service.
Figure 6. Use case model of PDMCS system
First, the attributes of functional and non-functional aspects related to cloud policy based on
the cloud service specification are extracted and incorporate them into the analysis model. Therefore,
the class model is generated as shown in Figure 7, reflecting the attributes of the cloud. Policy-based cloud
attributes was described in Table 2 in the cloud policy section. These attributes can be expressed within
the classes (in attributes and operations) of the class model. For instance, the cloud attribute for the policy of
"① To create a folder, user must have a certain amount of personal storage." in Table 2 is set to attribute of
"personal_storage_capacity" class as shown "storage_size = 25giga" that the specified capacity was declared
as the initial value in Figure 7. As shown in Figure 7, the class model with the attributes of the cloud
(underlined) is created by the MVC pattern for the unit "folder" cloud service. In Figure 7, the classes
directly related to folder function are grouped (in bold box) and represented in the "folder_management"
package that is a unit folder cloud service. The class model is created with both folder itself classes and
the related classes to use folder function, such as login class, and file class that folder includes.
In this phase, personalization service and self service, which are the characteristic elements of
the cloud as shown in Figure 1, are represented into respectively "personal_service_UI" class for handling
individual use, "folder_controller" class for processing resource sharing service and also "account" class and
"personal_storage_capacity" class for tenant service. The MVC expression for “folder” class is expressed as
follows: the "folder_UI" as a View class represents screen display of folder explorer; the "folder_controller"
as a Control class indicates performing actual function processing; and the "folder" as a Model class means
an entity class for storing and managing related folder data. On the other hand, the security attributes of
the non-functional cloud policy are expressed within the related classes. For example,
in the "folder_Controller" class, a security of "non-repudiation" is expressed as a stereotype.
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5.3. Cloud design for PDMCS system (PSM)
In the cloud design phase, the environments of an operation platform are reflected, and a system
architecture is designed by adding cloud to it for the implementation of a PDMCS system based on the cloud
analysis model as shown in Figure 7. The inner structure of the architecture is specified with the protocol and
mechanism of cloud, and is written using the modeling elements applied in the PSM level as shown in
Figure 1 and Figure 3. For the PDMCS system, application and system architectures are written.
These models mean the “cloud model,” a PSM modeling element in Figure 1. Figure 8 shows the application
architecture designed using the MVC method for a unit cloud service, “Folder.”
Table 2. Cloud service specification of unit “folder” cloud service
Cloud service property (CIM) Cloud service definition
Identifying
Attributes
Service_name Folder management
Service_definition
(foundation)
The cloud service creates and shares folders, stores files in folders, and provides
search.
Service_user Users using Google cloud service
Domain_task File management
Cloud_policy
- Function policy
- Security policy
① To create a folder, user must have a certain amount of personal
storage.
② The folder determines whether to share according to the
individual security policy.
③ Provide folder services only to account users registered in the
cloud service
- The Google Account holder of a specific tenant that is authorized has access and
management rights to the folder.
- Login is required to use folder service. (Authentication)
- Reading and writing from an illegal subject to a folder are prohibited.
(Confidentiality, Integrity)
Business process (1) Make a folder.
(2) Save the file.
(3) Set up and provide sharing and searching of folders.
Delivery
Attributes
Delivery_type SaaS
Opearation_type Private_cloud (a dedicated system managed by users, defined by privacy settings and
administrative responsibilities)
Use
Attributes
Pre_condition - Users should be logged in to Google's cloud system.
- Storage capacity should be at least 15 gigabytes.
Post_condition The folder is created and the file is saved.
Fee Free
After that, based on this component model, a system architecture model is written as shown in
Figure 9. Here, a C/S (Client/ Server)-type cloud architecture model is designed. Cloud application, file and
DB servers are established. The unit cloud service, “Folder,” was created by grouping three execution
components including “FolderUIWeb.war.” As an example of reflecting operation platform environments,
among cloud storage types (object, file, block), file storage was selected, and Network Attached Storage
(NAS) was expressed as its server using Amazon’s Elastic File System (EFS) solution.
Meanwhile, for communications between client and server (C/S), the processing of log-in through
web sites was expressed with HTTP, and P2P for file transfer. In addition, for security assurance for mutual
communications, <<secrecy, encrypted, authentification>> was expressed, which expresses the requirement
of security among non-function cloud policies. The deployment type of the “Folder” cloud service was
expressed with <<SaaS>>. The cloud model above is specified and implemented with protocols and
mechanisms. Cloud mechanisms as shown in Figure 1 include auto-expand listener, load distribution, SLA
monitor and on-demand measurement monitor. For example, auto-expand listener is an agent that
automatically expands the capacity when resources lack. In the PSM level, its processing mechanism is
written in detail. The characteristics of cloud are reflected in this level as follows. “Customization” is
reflected by expressing that each user computer (UC1) has “Folder_Service” in its server in Figure 9, and
“distributed processing” is reflected by expressing that users in A and B areas use servers in each area.
For example, “different platform operation” is implemented by allowing “FolderControlSearch.jar” to be
operated in both the Spring Framework and COM+.
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Figure 7. Class model with cloud attribute of the unit “folder” cloud service in PDMCS system
Figure 8. Component model of application architecture for unit “Folder” cloud service
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Figure 9. Component model of system architecture for unit “Folder” cloud service
6. EVALUATION
As an evaluation of the proposed method, this section describes the self-evaluation, comparison with
the existing methods, and also characteristics and shortcomings of the proposed method.
6.1. Comparative evaluation with the existing method
In order to compare proposed methods in this study and existing methods together, matrices related
to metamodels and modeling processes were analysed as shown in Table 3. Table 3 shows the analysis of
the metamodel and the matrices related to the modeling process for comparison between the presentation
method and the existing method. The score of each item is 1.0. The value of the item for comparison methods
means level or degree of support.
CAML proposed a MDA approach method for creating a PIM component model to cloud
applications and designing it as a PSM deployment model using CAML that extends UML. However, it did
not support service oriented method and requirement definition phase, and cloud characteristics such as
personalization and resource sharing were not reflected enough. UCC presented a method for designing,
executing, and managing nine requirements for building cloud applications. This also defined meta-models
that is consisted of modeling elements for deploying cloud applications in the cloud environment. However,
it does not provide a service-oriented and the modeling process covering overall development pahses. SCoD
suggested a feature-based cloud development method that supports multi-tenants. However, this was not
a general UML-based object development method and did not support service-oriented development.
MADONA proposed a reuse-based service-oriented cloud development method, so was not a method for
developing new cloud services. Conventional research did not support fully based on service-oriented design,
hierarchical modeling by MDA and MVC pattern, and metamodel-based approach. Therefore, it was not easy
to use and did not maximize the number of reuse-available model of created application model.
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Table 3. Comparison of metamodel and process with legacy method
Assessed items (point) CAML [10] UCC
[11]
SCoD
[12]
MADONA
[13]
Proposed
method
Mapping metamodel from Cloud to UML
modelling (1.0)
0.50 0.50 0.25 0.25 0.75
Layered cloud
Metamodel (1.0)
0.25 0.25 0.25 0.25 1.00
Cloud modelling process Covering
whole development life cycle (1.0)
0.50 0.75 1.00 1.00
(Reuse)
0.50
(Design)
Hierarchical designing by layered
metamodel or process (1.0)
0.75 0.50 0.50 0.25 0.75
Service-oriented modelling (1.0) 0.25 0.25 0.75 1.00 0.50
Security modelling method (1.0) 0.25 0.25 0.25 0.25 0.75
MDA-based modelling (1.0) 0.75 0.50 0.50 0.50 0.75
MVC-based modelling (1.0) 0.25 0.25 0.25 0.25 0.75
Conversion profile between Models(1.0) 0.25 0.25 0.50 0.25 0.50
Weight total 100% (9.0) 42%(3.75) 39%(3.50) 47%(4.25) 44%(4.00) 69%(6.25)
[Legend] 1.00: Very high (support), 0.75: Good, 0.5
6.2. Characteristics and limitations
The characteristics and expected effects of the proposed methods are as follows:
a. Cloud property-driven
- Cloud service metamodels are proposed based on cloud properties such as personalization (tenant,
self-service), resource sharing, distributed processing, etc.
- Cloud chracteristics are modeled and detailed by top-down approach according to service, policy,
attribute, mechanism, etc.
b. Cloud-UML Mapping-driven in Figure 3
- The integrated metamodel (IMCU) and modeling process is provided on how the characteristic
elements of the cloud are mapped and represented into UML modeling elements.
c. Service-driven
- This method provides that is designed the architecture and interior focusing to unit cloud service.
d. Model pattern-driven
- The number of reusable models can be maximized by using approaches such as the CIM/PIM/PSM
of the MDA, and Model/View/Control methods. CIM model + {(number of models by PIM/PSM) x
(number of models by MVC)} = 1 + (2 x 3) = 7
- Independent modularity between models is more increased.
e. Metamodel-based driven
- Modeling practices become easy by applying the modeling elements and relationships of
the formalized individual as shown in Figure 1 and integration Figure 3 metamodels.
The limitations of the proposed methods are as follows:
a. Proposed cloud metamodels and modeling processes cannot provide a perfectly integrated modeling
between function and security.
- To use proposed modeling processes to real practices as commercialized methodologies, task, step,
guideline and artifact should be specified more and connecting practices should be clarified more.
b. It does not provide more concreted methods of establishing various cloud policies, attributes, protocols,
and techniques that implement and realizes this policy.
- The development methods for SLA policy, resource policy, service area policy, legal policy,
payment policy, etc. are required.
c. It is necessary to support successful practice deliverables by continuously applying them to cases
7. CONCLUSION
Conventional methods of developing cloud applications create services and expand deployment
models based on porting or reuse, but UML-based unified development methods that consider the overall
characteristics of cloud have not been researched much. This study suggested metamodels, transformation
profiles, frameworks and processes based on MDA and MVC patterns for developing service-oriented
applications that reflect the characteristics of cloud. The cloud service metamodel was defined with cloud
requirement features and elements for implementation including policies, attributes and mechanisms.
How these cloud elements are transformed and expressed into UML modeling elements was established in an
MDA-based integrated metamodel. The framework of three development phases to which MVC patterns
were applied was defined, and the cloud modeling process composed of development phases and task
activities was defined. Task activities were ensured to be performed using the modeling elements and
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relations of standardized individual and integrated metamodels. In terms of their expected effects.
For example, it will be possible to design unified service-oriented cloud applications suitable for cloud
computing environments, and to design clearer cloud service models using standardized cloud metamodels
and processes. As a follow-up study, it will be necessary to develop specific guidelines for task activities
within the cloud modeling process that can accept various policies, and to research the automated
establishment of cloud applications by developing case tools with the improved methods.
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16. Int J Elec & Comp Eng ISSN: 2088-8708
A service-oriented cloud modeling method and process (Chee-Yang Song)
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BIOGRAPHIES OF AUTHORS
Chee-Yang Song received the bachelor and master's degrees in Computer Science from
the Hannam university in 1985 and the Chungang University in 1987, respectively. He received
the Ph.D. degree in Computer Science from Korea University in 2003. From 1990 to 2005,
he was a researcher at Research center of Korea Telecom (KT). He has been a Professor in
the Department of Software at Kyungpook National University since 2008. His research interests
include service oriented modeling, business-software integrated design process, security design,
and cloud computing
Eun-Sook Cho received the B.S. degree in Computer Science from DongEui University, Korea
in 1993. He received the M.S and Ph.D degree in Computer Science from SoongSil University,
Korea, in 1996 and 2000, respectively. Dr. Cho joined the faculty of the Department of Software
Engineering at Seoil University, Seoul, Korea, in 2005. He is currently a Professor in the
Department of Software Engineering, Seoil University. He is interested in component-based
development, cloud computing, and IoT applications