Recently, citizens and companies can access utility computing services by using Cloud Computing. These services such as
infrastructures, platforms and applications could be accessed on-demand whenever it is needed. In Cloud Computing, different types of
resources would be required to provide services, but the demands such as requests rates and user's requirements of these services and
the cost of the required resources are continuously varying. Therefore, Service Level Agreements would be needed to guarantee the
service's prices and the offered Quality of Services which are always dependable and interrelated to guarantee revenues maximization
for cloud providers as well as improve customers' satisfaction level. Cloud consumers are always searching for a cloud provider who
provides good service with the least price, so Cloud provider should use advanced technologies and frameworks to increase QoS, and
decrease cost. This paper provides a survey on cloud pricing models and analyzes the recent and relevant research in this field.
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.
A FRAMEWORK FOR SOFTWARE-AS-A-SERVICE SELECTION AND PROVISIONINGIJCNCJournal
As cloud computing is increasingly transforming the information technology landscape, organizations and
businesses are exhibiting strong interest in Software-as-a-Service (SaaS) offerings that can help them
increase business agility and reduce their operational costs. They increasingly demand services that can
meet their functional and non-functional requirements. Given the plethora and the variety of SaaS
offerings, we propose, in this paper, a framework for SaaS provisioning, which relies on brokered Service
Level agreements (SLAs), between service consumers and SaaS providers. The Cloud Service Broker (CSB)
helps service consumers find the right SaaS providers that can fulfil their functional and non-functional
requirements. The proposed selection algorithm ranks potential SaaS providers by matching their offerings
against the requirements of the service consumer using an aggregate utility function. Furthermore, the CSB
is in charge of conducting SLA negotiation with selected SaaS providers, on behalf of service consumers,
and performing SLA compliance monitoring
This document proposes a double resource renting scheme for cloud service providers that combines short-term and long-term renting. It defines a profit maximization problem to determine the optimal configuration of servers and queue capacity. An M/M/m+D queuing model is used to analyze factors like average charge and temporary server usage. The double renting scheme is shown to guarantee quality of service for all requests while reducing waste and generating more profit compared to single renting schemes.
A PROFIT MAXIMIZATION SCHEME WITH GUARANTEED QUALITY OF SERVICE IN CLOUD COMP...Shakas Technologies
The document proposes a double resource renting scheme for cloud computing platforms that combines short-term and long-term resource renting. This is designed to maximize profits while guaranteeing quality of service. An M/M/m+D queuing model is used to analyze the performance of the system. The scheme formulates a profit maximization problem to determine the optimal configuration of resources. Calculations show this double renting scheme achieves higher profits compared to single renting schemes, while guaranteeing quality of service for all requests.
IEEE 2015-2016 A Profit Maximization Scheme with Guaranteed Quality of Servic...1crore projects
1 CRORE PROJECTS offers M.E, BE, M. Tech, B. Tech, PhD, MCA, BCA, MSC & MBA projects based on IEEE (2014-2015) and also a real time application projects.
Final Year Projects for BE, B. Tech - ECE, EEE, CSE, IT, MCA, ME, M. Tech, M SC (IT), BCA, BSC and MBA.
Market-Oriented Cloud Computing (as part of cloud symposium of ACM Compute 2009)
Srikumar Venugopal
Grid Computing and Distributed Systems (GRIDS) Laboratory
Dept. of Computer Science and Software Engineering
The University of Melbourne, Australia
ADAPTIVE MULTI-TENANCY POLICY FOR ENHANCING SERVICE LEVEL AGREEMENT THROUGH R...IJCNCJournal
The appearance of infinite computing resources that available on demand and fast enough to adapt with
load surges makes Cloud computing favourable service infrastructure in IT market. Core feature in Cloud
service infrastructures is Service Level Agreement (SLA) that led seamless service at high quality of service
to client. One of the challenges in Cloud is providing heterogeneous computing services for the clients.
With the increasing number of clients/tenants in the Cloud, unsatisfied agreement is becoming a critical
factor. In this paper, we present an adaptive resource allocation policy which attempts to improve
accountable in Cloud SLA while aiming for enhancing system performance. Specifically, our allocation
incorporates dynamic matching SLA rules to deal with diverse processing requirements from
tenants.Explicitly, it reduces processing overheadswhile achieving better service agreement. Simulation
experiments proved the efficacy of our allocation policy in order to satisfy the tenants; and helps improve
reliable computing.
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.
A FRAMEWORK FOR SOFTWARE-AS-A-SERVICE SELECTION AND PROVISIONINGIJCNCJournal
As cloud computing is increasingly transforming the information technology landscape, organizations and
businesses are exhibiting strong interest in Software-as-a-Service (SaaS) offerings that can help them
increase business agility and reduce their operational costs. They increasingly demand services that can
meet their functional and non-functional requirements. Given the plethora and the variety of SaaS
offerings, we propose, in this paper, a framework for SaaS provisioning, which relies on brokered Service
Level agreements (SLAs), between service consumers and SaaS providers. The Cloud Service Broker (CSB)
helps service consumers find the right SaaS providers that can fulfil their functional and non-functional
requirements. The proposed selection algorithm ranks potential SaaS providers by matching their offerings
against the requirements of the service consumer using an aggregate utility function. Furthermore, the CSB
is in charge of conducting SLA negotiation with selected SaaS providers, on behalf of service consumers,
and performing SLA compliance monitoring
This document proposes a double resource renting scheme for cloud service providers that combines short-term and long-term renting. It defines a profit maximization problem to determine the optimal configuration of servers and queue capacity. An M/M/m+D queuing model is used to analyze factors like average charge and temporary server usage. The double renting scheme is shown to guarantee quality of service for all requests while reducing waste and generating more profit compared to single renting schemes.
A PROFIT MAXIMIZATION SCHEME WITH GUARANTEED QUALITY OF SERVICE IN CLOUD COMP...Shakas Technologies
The document proposes a double resource renting scheme for cloud computing platforms that combines short-term and long-term resource renting. This is designed to maximize profits while guaranteeing quality of service. An M/M/m+D queuing model is used to analyze the performance of the system. The scheme formulates a profit maximization problem to determine the optimal configuration of resources. Calculations show this double renting scheme achieves higher profits compared to single renting schemes, while guaranteeing quality of service for all requests.
IEEE 2015-2016 A Profit Maximization Scheme with Guaranteed Quality of Servic...1crore projects
1 CRORE PROJECTS offers M.E, BE, M. Tech, B. Tech, PhD, MCA, BCA, MSC & MBA projects based on IEEE (2014-2015) and also a real time application projects.
Final Year Projects for BE, B. Tech - ECE, EEE, CSE, IT, MCA, ME, M. Tech, M SC (IT), BCA, BSC and MBA.
Market-Oriented Cloud Computing (as part of cloud symposium of ACM Compute 2009)
Srikumar Venugopal
Grid Computing and Distributed Systems (GRIDS) Laboratory
Dept. of Computer Science and Software Engineering
The University of Melbourne, Australia
ADAPTIVE MULTI-TENANCY POLICY FOR ENHANCING SERVICE LEVEL AGREEMENT THROUGH R...IJCNCJournal
The appearance of infinite computing resources that available on demand and fast enough to adapt with
load surges makes Cloud computing favourable service infrastructure in IT market. Core feature in Cloud
service infrastructures is Service Level Agreement (SLA) that led seamless service at high quality of service
to client. One of the challenges in Cloud is providing heterogeneous computing services for the clients.
With the increasing number of clients/tenants in the Cloud, unsatisfied agreement is becoming a critical
factor. In this paper, we present an adaptive resource allocation policy which attempts to improve
accountable in Cloud SLA while aiming for enhancing system performance. Specifically, our allocation
incorporates dynamic matching SLA rules to deal with diverse processing requirements from
tenants.Explicitly, it reduces processing overheadswhile achieving better service agreement. Simulation
experiments proved the efficacy of our allocation policy in order to satisfy the tenants; and helps improve
reliable computing.
A Profit Maximization Scheme with Guaranteed Quality of Service in Cloud Comp...1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
1) The document proposes an agent-based economic model for analyzing interactions between consumers and clouds (consumer-to-cloud) and between clouds (cloud-to-cloud) in an intelligent intercloud system.
2) For consumer-to-cloud interactions, a novel negotiation protocol and strategy called adaptive concession rate (ACR) and minimally sufficient concession (MSC) is developed.
3) For cloud-to-cloud interactions, a four-stage interaction protocol and strategies for cloud agents that result in coalition formation and fair division of payoffs are developed.
A profit maximization scheme with guaranteed quality of service in cloud comp...Pvrtechnologies Nellore
- The document proposes a double resource renting scheme for cloud service providers that combines short-term and long-term server renting. This aims to guarantee quality of service for all requests while reducing resource waste.
- A profit maximization problem is formulated to determine the optimal configuration of servers. Solutions are obtained for ideal and actual scenarios to maximize profit compared to a single renting scheme.
- Comparisons show the double renting scheme can guarantee complete service quality and obtain more profit than a single renting scheme that does not ensure quality of service.
This white paper discusses the concept of "Carrier Cloud" and the opportunities it presents for telecommunications carriers. The three pillars of Carrier Cloud are being carrier-centric, able to deliver carrier-grade cloud services, and providing differentiation through IT and network innovation. Carriers can capture new revenue streams by positioning themselves in key value chains like business IT using their cloud. Carriers have advantages over other cloud providers through their networks, commercial maturity, datacenter infrastructure, and ability to ensure high service availability. The paper argues Carriers should pursue cloud services as a strategic opportunity.
IRJET- Determination of Multifaceted Trusted Cloud Service using Conventional...IRJET Journal
1. The document proposes a method for determining trusted cloud services using a conventional cloud-based algorithm. It aims to address the issue of selecting trusted cloud services based on user preferences and quality of service attributes.
2. The method involves constructing a multi-granularity standard of trust levels based on Gaussian cloud transformation and developing a computational model of user preferences using cloud analytic hierarchy process.
3. A two-step fuzzy comprehensive evaluation algorithm is then proposed to evaluate and rank different cloud services based on trust scores, providing users with an effective way to select trusted cloud services.
How Cloud Service Providers Can Effectively Monetize and Deliver the Ultimate...Comverse, Inc.
1. CSPs face challenges in monetizing cloud services including becoming a commodity, poor client satisfaction from billing, and missed revenue opportunities.
2. Effective monetization is key to minimizing risks, developing sustainable business models, and creating market differentiation for CSPs.
3. Billing models for CSPs must be flexible, value-based, and reflective of dynamic consumption patterns to meet enterprise needs and avoid issues like "bill shock".
IEEE 2014 DOTNET CLOUD COMPUTING PROJECTS A mechanism design approach to reso...IEEEMEMTECHSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
Privacy Preserving Auction Based Virtual Machine Instances Allocation Scheme ...IJECEIAES
Cloud Computing Environment provides computing resources in the form of Virtual Machines (VMs), to the cloud users through Internet. Auction-based VM instances allocation allows different cloud users to participate in an auction for a bundle of Virtual Machine instances where the user with the highest bid value will be selected as the winner by the auctioneer (Cloud Service Provider) to gain more. In this auction mechanism, individual bid values are revealed to the auctioneer in order to select the winner as a result of which privacy of bid values are lost. In this paper, we proposed an auction scheme to select the winner without revealing the individual bid values to the auctioneer to maintain privacy of bid values. The winner will get the access to the bundle of VM instances. This scheme relies on a set of cryptographic protocols including Oblivious Transfer (OT) protocol and Yao’s protocol to maintain privacy of bid values.
In this e-zine, we’ve assembled fresh thinking and ideas about the solutions and services that create revenue opportunities and support emerging business models for providers.
A survey on various resource allocation policies in cloud computing environmenteSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Cloud computing altanai bisht , collge 2nd year , part iALTANAI BISHT
Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. It allows users to access technology-based services from the internet without knowledge of, expertise in, or control over the underlying technology infrastructure. Potential advantages of cloud computing include scalability, flexibility, and reduced capital and operating expenses. However, issues like regulatory compliance, security, and availability must be addressed for successful deployment.
This document discusses an approach for seamless real-time and batch processing of telecom transaction records. The approach allows telecom service providers to transition from offline batch processing of stored data to real-time analysis of streaming data. The approach is demonstrated through implementing a telecom revenue assurance solution using IBM Infosphere Streams, which can process stored call detail records (CDRs) offline and analyze streaming CDR data in real-time. This dual mode processing approach could benefit other domains like utilities, banking that deal with high volumes of transaction records.
THE COST OF MOVING TO ADVANCED COLLABORATIONdominion
This document analyzes and compares the total cost of ownership for implementing advanced collaboration solutions using IBM and Microsoft platforms across different user estate sizes. It finds that IBM solutions are up to 37% cheaper for infrastructure and support costs. When factoring in licensing costs, particularly for Microsoft Office, the savings are even more significant for IBM. Implementing instant messaging can save up to 40% with IBM, while basic document sharing saves 30%, and a full collaboration platform saves 18-27% compared to Microsoft.
The document introduces cloud computing, exploring its characteristics, service models, and deployment models. It discusses that cloud computing uses shared infrastructure and dynamic provisioning to provide scalable access to applications and services via the internet. The main service models described are software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS). The document also briefly mentions communications services available in the cloud.
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.
This document discusses satellite managed services, which refers to proactively managing customers' satellite networks end-to-end through ongoing monitoring and maintenance according to service level agreements. The benefits of this model include allowing companies to focus on their core business instead of network operations, providing predictable costs through monthly fees, and reducing capital investment needs through outsourcing expertise. As satellite networks become more complex with new technologies like high throughput satellites, the value of outsourcing network management to expert providers will increase.
1. Service science, management, and engineering (SSME) is an interdisciplinary approach to studying, designing, and implementing complex service systems.
2. SSME aims to make productivity, quality, compliance, sustainability, learning rates, and innovation more predictable for organization-to-organization services.
3. There are several frameworks for conceptualizing service systems, including considering the front stage customer experience separately from the back office operations.
Web Services-Enhanced Agile Modeling and Integrating Business ProcessesMustafa Salam
We propose a model-driven approach, based on Web services standards, for modeling and integrating agile business processes using Web services. The choice of focusing on Web services technology was not arbitrary. The large and broad adoption of this technology by enterprises will lead most business processes to be performed using Web services. Besides, the added value of Web services and their great interest to business process management are beyond doubt. Web services produce, on the one hand, loosely coupled applicative components.
On the other hand, they are the most widely used implementation technology of SOA (Service-Oriented Architecture), which is based on the large experiences of software and distributed component technologies. Being founded on the XML (eXtensible Markup Language) language, the SOAP (Simple Object Access Protocol) protocol and the UDDI (Universal Description Discovery and Integration) repository, this technology can be considered as an appropriate mean to ensure interoperability, data exchange and the publication and discovery of business processes when they can be implemented as Web services.
The document summarizes and compares various pricing models used in cloud computing. It discusses key cloud computing concepts like service models (IaaS, PaaS, SaaS) and characteristics. It then reviews several proposed pricing models and schemes, comparing factors like fairness, quality of service, and pricing approach. Most proposed models are theoretical and not implemented, though simulations show promise. Most also favor the service provider over customers. The document aims to provide a foundation for designing improved future pricing models.
A Study On Service Level Agreement Management Techniques In CloudTracy Drey
This document discusses techniques for managing service level agreements (SLAs) in cloud computing. It begins with an introduction to cloud computing and SLAs. SLAs establish performance standards and consequences for violations between cloud service providers and their customers. The document then reviews several proposed techniques for SLA management from other researchers: (1) allowing multiple SLAs with different performance metrics, (2) using third-party auditing to verify SLA fulfillment, and (3) a layered approach to prevent SLA violations through self-management of cloud resources. The techniques aim to help cloud providers better satisfy SLAs and retain customers.
Profit Maximization for Service Providers using Hybrid Pricing in Cloud Compu...Editor IJCATR
Cloud computing has recently emerged as one of the buzzwords in the IT industry. Several IT vendors are promising to offer computation, data/storage, and application hosting services, offering Service-Level Agreements (SLA) backed performance and uptime promises for their services. While these „clouds‟ are the natural evolution of traditional clusters and data centers, they are distinguished by following a pricing model where customers are charged based on their utilization of computational resources, storage and transfer of data. They offer subscription-based access to infrastructure, platforms, and applications that are popularly termed as IaaS (Infrastructure as a Service), PaaS (Platform as a Service), and SaaS (Software as a Service). In order to improve the profit of service providers we implement a technique called hybrid pricing , where this hybrid pricing model is a pooled with fixed and spot pricing techniques.
A Profit Maximization Scheme with Guaranteed Quality of Service in Cloud Comp...1crore projects
IEEE PROJECTS 2015
1 crore projects is a leading Guide for ieee Projects and real time projects Works Provider.
It has been provided Lot of Guidance for Thousands of Students & made them more beneficial in all Technology Training.
Dot Net
DOTNET Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
Java Project Domain list 2015
1. IEEE based on datamining and knowledge engineering
2. IEEE based on mobile computing
3. IEEE based on networking
4. IEEE based on Image processing
5. IEEE based on Multimedia
6. IEEE based on Network security
7. IEEE based on parallel and distributed systems
ECE IEEE Projects 2015
1. Matlab project
2. Ns2 project
3. Embedded project
4. Robotics project
Eligibility
Final Year students of
1. BSc (C.S)
2. BCA/B.E(C.S)
3. B.Tech IT
4. BE (C.S)
5. MSc (C.S)
6. MSc (IT)
7. MCA
8. MS (IT)
9. ME(ALL)
10. BE(ECE)(EEE)(E&I)
TECHNOLOGY USED AND FOR TRAINING IN
1. DOT NET
2. C sharp
3. ASP
4. VB
5. SQL SERVER
6. JAVA
7. J2EE
8. STRINGS
9. ORACLE
10. VB dotNET
11. EMBEDDED
12. MAT LAB
13. LAB VIEW
14. Multi Sim
CONTACT US
1 CRORE PROJECTS
Door No: 214/215,2nd Floor,
No. 172, Raahat Plaza, (Shopping Mall) ,Arcot Road, Vadapalani, Chennai,
Tamin Nadu, INDIA - 600 026
Email id: 1croreprojects@gmail.com
website:1croreprojects.com
Phone : +91 97518 00789 / +91 72999 51536
1) The document proposes an agent-based economic model for analyzing interactions between consumers and clouds (consumer-to-cloud) and between clouds (cloud-to-cloud) in an intelligent intercloud system.
2) For consumer-to-cloud interactions, a novel negotiation protocol and strategy called adaptive concession rate (ACR) and minimally sufficient concession (MSC) is developed.
3) For cloud-to-cloud interactions, a four-stage interaction protocol and strategies for cloud agents that result in coalition formation and fair division of payoffs are developed.
A profit maximization scheme with guaranteed quality of service in cloud comp...Pvrtechnologies Nellore
- The document proposes a double resource renting scheme for cloud service providers that combines short-term and long-term server renting. This aims to guarantee quality of service for all requests while reducing resource waste.
- A profit maximization problem is formulated to determine the optimal configuration of servers. Solutions are obtained for ideal and actual scenarios to maximize profit compared to a single renting scheme.
- Comparisons show the double renting scheme can guarantee complete service quality and obtain more profit than a single renting scheme that does not ensure quality of service.
This white paper discusses the concept of "Carrier Cloud" and the opportunities it presents for telecommunications carriers. The three pillars of Carrier Cloud are being carrier-centric, able to deliver carrier-grade cloud services, and providing differentiation through IT and network innovation. Carriers can capture new revenue streams by positioning themselves in key value chains like business IT using their cloud. Carriers have advantages over other cloud providers through their networks, commercial maturity, datacenter infrastructure, and ability to ensure high service availability. The paper argues Carriers should pursue cloud services as a strategic opportunity.
IRJET- Determination of Multifaceted Trusted Cloud Service using Conventional...IRJET Journal
1. The document proposes a method for determining trusted cloud services using a conventional cloud-based algorithm. It aims to address the issue of selecting trusted cloud services based on user preferences and quality of service attributes.
2. The method involves constructing a multi-granularity standard of trust levels based on Gaussian cloud transformation and developing a computational model of user preferences using cloud analytic hierarchy process.
3. A two-step fuzzy comprehensive evaluation algorithm is then proposed to evaluate and rank different cloud services based on trust scores, providing users with an effective way to select trusted cloud services.
How Cloud Service Providers Can Effectively Monetize and Deliver the Ultimate...Comverse, Inc.
1. CSPs face challenges in monetizing cloud services including becoming a commodity, poor client satisfaction from billing, and missed revenue opportunities.
2. Effective monetization is key to minimizing risks, developing sustainable business models, and creating market differentiation for CSPs.
3. Billing models for CSPs must be flexible, value-based, and reflective of dynamic consumption patterns to meet enterprise needs and avoid issues like "bill shock".
IEEE 2014 DOTNET CLOUD COMPUTING PROJECTS A mechanism design approach to reso...IEEEMEMTECHSTUDENTPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
Privacy Preserving Auction Based Virtual Machine Instances Allocation Scheme ...IJECEIAES
Cloud Computing Environment provides computing resources in the form of Virtual Machines (VMs), to the cloud users through Internet. Auction-based VM instances allocation allows different cloud users to participate in an auction for a bundle of Virtual Machine instances where the user with the highest bid value will be selected as the winner by the auctioneer (Cloud Service Provider) to gain more. In this auction mechanism, individual bid values are revealed to the auctioneer in order to select the winner as a result of which privacy of bid values are lost. In this paper, we proposed an auction scheme to select the winner without revealing the individual bid values to the auctioneer to maintain privacy of bid values. The winner will get the access to the bundle of VM instances. This scheme relies on a set of cryptographic protocols including Oblivious Transfer (OT) protocol and Yao’s protocol to maintain privacy of bid values.
In this e-zine, we’ve assembled fresh thinking and ideas about the solutions and services that create revenue opportunities and support emerging business models for providers.
A survey on various resource allocation policies in cloud computing environmenteSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Cloud computing altanai bisht , collge 2nd year , part iALTANAI BISHT
Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. It allows users to access technology-based services from the internet without knowledge of, expertise in, or control over the underlying technology infrastructure. Potential advantages of cloud computing include scalability, flexibility, and reduced capital and operating expenses. However, issues like regulatory compliance, security, and availability must be addressed for successful deployment.
This document discusses an approach for seamless real-time and batch processing of telecom transaction records. The approach allows telecom service providers to transition from offline batch processing of stored data to real-time analysis of streaming data. The approach is demonstrated through implementing a telecom revenue assurance solution using IBM Infosphere Streams, which can process stored call detail records (CDRs) offline and analyze streaming CDR data in real-time. This dual mode processing approach could benefit other domains like utilities, banking that deal with high volumes of transaction records.
THE COST OF MOVING TO ADVANCED COLLABORATIONdominion
This document analyzes and compares the total cost of ownership for implementing advanced collaboration solutions using IBM and Microsoft platforms across different user estate sizes. It finds that IBM solutions are up to 37% cheaper for infrastructure and support costs. When factoring in licensing costs, particularly for Microsoft Office, the savings are even more significant for IBM. Implementing instant messaging can save up to 40% with IBM, while basic document sharing saves 30%, and a full collaboration platform saves 18-27% compared to Microsoft.
The document introduces cloud computing, exploring its characteristics, service models, and deployment models. It discusses that cloud computing uses shared infrastructure and dynamic provisioning to provide scalable access to applications and services via the internet. The main service models described are software as a service (SaaS), platform as a service (PaaS), and infrastructure as a service (IaaS). The document also briefly mentions communications services available in the cloud.
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.
This document discusses satellite managed services, which refers to proactively managing customers' satellite networks end-to-end through ongoing monitoring and maintenance according to service level agreements. The benefits of this model include allowing companies to focus on their core business instead of network operations, providing predictable costs through monthly fees, and reducing capital investment needs through outsourcing expertise. As satellite networks become more complex with new technologies like high throughput satellites, the value of outsourcing network management to expert providers will increase.
1. Service science, management, and engineering (SSME) is an interdisciplinary approach to studying, designing, and implementing complex service systems.
2. SSME aims to make productivity, quality, compliance, sustainability, learning rates, and innovation more predictable for organization-to-organization services.
3. There are several frameworks for conceptualizing service systems, including considering the front stage customer experience separately from the back office operations.
Web Services-Enhanced Agile Modeling and Integrating Business ProcessesMustafa Salam
We propose a model-driven approach, based on Web services standards, for modeling and integrating agile business processes using Web services. The choice of focusing on Web services technology was not arbitrary. The large and broad adoption of this technology by enterprises will lead most business processes to be performed using Web services. Besides, the added value of Web services and their great interest to business process management are beyond doubt. Web services produce, on the one hand, loosely coupled applicative components.
On the other hand, they are the most widely used implementation technology of SOA (Service-Oriented Architecture), which is based on the large experiences of software and distributed component technologies. Being founded on the XML (eXtensible Markup Language) language, the SOAP (Simple Object Access Protocol) protocol and the UDDI (Universal Description Discovery and Integration) repository, this technology can be considered as an appropriate mean to ensure interoperability, data exchange and the publication and discovery of business processes when they can be implemented as Web services.
The document summarizes and compares various pricing models used in cloud computing. It discusses key cloud computing concepts like service models (IaaS, PaaS, SaaS) and characteristics. It then reviews several proposed pricing models and schemes, comparing factors like fairness, quality of service, and pricing approach. Most proposed models are theoretical and not implemented, though simulations show promise. Most also favor the service provider over customers. The document aims to provide a foundation for designing improved future pricing models.
A Study On Service Level Agreement Management Techniques In CloudTracy Drey
This document discusses techniques for managing service level agreements (SLAs) in cloud computing. It begins with an introduction to cloud computing and SLAs. SLAs establish performance standards and consequences for violations between cloud service providers and their customers. The document then reviews several proposed techniques for SLA management from other researchers: (1) allowing multiple SLAs with different performance metrics, (2) using third-party auditing to verify SLA fulfillment, and (3) a layered approach to prevent SLA violations through self-management of cloud resources. The techniques aim to help cloud providers better satisfy SLAs and retain customers.
Profit Maximization for Service Providers using Hybrid Pricing in Cloud Compu...Editor IJCATR
Cloud computing has recently emerged as one of the buzzwords in the IT industry. Several IT vendors are promising to offer computation, data/storage, and application hosting services, offering Service-Level Agreements (SLA) backed performance and uptime promises for their services. While these „clouds‟ are the natural evolution of traditional clusters and data centers, they are distinguished by following a pricing model where customers are charged based on their utilization of computational resources, storage and transfer of data. They offer subscription-based access to infrastructure, platforms, and applications that are popularly termed as IaaS (Infrastructure as a Service), PaaS (Platform as a Service), and SaaS (Software as a Service). In order to improve the profit of service providers we implement a technique called hybrid pricing , where this hybrid pricing model is a pooled with fixed and spot pricing techniques.
Cloud computing charecteristics and types altanai bisht , 2nd year, part iiiALTANAI BISHT
Computing is being transformed to a model consisting of services based on their requirements without regard to where the services are hosted or how they are delivered.
ENERGY-AWARE LOAD BALANCING AND APPLICATION SCALING FOR THE CLOUD ECOSYSTEMShakas Technologies
This document proposes a double resource renting scheme for cloud service providers to maximize profit while guaranteeing quality of service. It models the cloud system as an M/M/m+D queuing model. The scheme combines long-term and short-term server rentals to provide the necessary computing capacity over time. An optimization problem is formulated to determine the optimal server configuration that maximizes profit by balancing rental costs against increased revenue from meeting quality guarantees. Comparisons show the double renting scheme achieves higher profit than single renting while guaranteeing all requests are served on time.
A Profit Maximization Scheme with Guaranteed Quality of Service in Cloud Com...nexgentechnology
bulk ieee projects in pondicherry,ieee projects in pondicherry,final year ieee projects in pondicherry
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
A PROFIT MAXIMIZATION SCHEME WITH GUARANTEED QUALITY OF SERVICE IN CLOUD COMP...Nexgen Technology
bulk ieee projects in pondicherry,ieee projects in pondicherry,final year ieee projects in pondicherry
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
A Profit Maximization Scheme with Guaranteed Quality of Service in Cloud Com...nexgentechnology
bulk ieee projects in pondicherry,ieee projects in pondicherry,final year ieee projects in pondicherry
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
A Profit Maximization Scheme with Guaranteed Quality of Service in Cloud Com...nexgentechnology
1) A double resource renting scheme is proposed that combines short-term and long-term server renting to guarantee quality of service while maximizing cloud provider profits.
2) An M/M/m+D queuing model is used to represent the cloud system and analyze key performance indicators.
3) An optimal configuration problem is formulated and solved to determine the profit-maximizing number of long-term servers, balancing rental costs against meeting service-level agreements.
A profit maximization scheme with guaranteednexgentech15
Nexgen Technology Address:
Nexgen Technology
No :66,4th cross,Venkata nagar,
Near SBI ATM,
Puducherry.
Email Id: praveen@nexgenproject.com.
www.nexgenproject.com
Mobile: 9751442511,9791938249
Telephone: 0413-2211159.
NEXGEN TECHNOLOGY as an efficient Software Training Center located at Pondicherry with IT Training on IEEE Projects in Android,IEEE IT B.Tech Student Projects, Android Projects Training with Placements Pondicherry, IEEE projects in pondicherry, final IEEE Projects in Pondicherry , MCA, BTech, BCA Projects in Pondicherry, Bulk IEEE PROJECTS IN Pondicherry.So far we have reached almost all engineering colleges located in Pondicherry and around 90km
In the present atmosphere of tighter budgets and pressure on resources, many public sector organiza-tions, including local authorities, are outsourcing services to outer organizations under service level agreements in cloud computing. Cloud computing is an approach to convey facilitated benefits over the web. Services are available to the users relying upon cloud arrangement and the Service Level Agreement (SLA) between the service providers and the cli-ents. Service level agreements are being utilized inside associations, directing connection between various sections of the association. It requires a commitment from both parties to support and adhere to the agreement in order for the SLA to work effectively. In spite of the fact that it gives a straightforward view about the cloud condition, such as cloud services, cloud distribution, security issues, responsibilities, agreements and warranties of the services. However, there are several issues occur from incorrect SLA which can cause misunderstanding among service providers and clients. SLA checking device confirm the SLA effectively whether it deals with all administrations as per SLA. In this paper, we represent a SLA confirmation and checking process that can distinguish SLA verification in gathering the information. We consider IaaS (Infrastructure as a Service) parameters for SLA verification in Cloud.
A SURVEY ON RESOURCE ALLOCATION IN CLOUD COMPUTINGijccsa
Cloud computing is an on-demand service resource which includes applications to data centers on a
pay-per-use basis. In order to allocate these resources properly and satisfy users’ demands, an efficient
and flexible resource allocation mechanism is needed. Due to increasing user demand, the resource
allocating process has become more challenging and difficult. One of the main focuses of research
scholars is how to develop optimal solutions for this process. In this paper, a literature review on proposed
dynamic resource allocation techniques is introduced.
A SURVEY ON RESOURCE ALLOCATION IN CLOUD COMPUTINGijccsa
Cloud computing is an on-demand service resource which includes applications to data centers on a
pay-per-use basis. In order to allocate these resources properly and satisfy users’ demands, an efficient
and flexible resource allocation mechanism is needed. Due to increasing user demand, the resource
allocating process has become more challenging and difficult. One of the main focuses of research
scholars is how to develop optimal solutions for this process. In this paper, a literature review on proposed
dynamic resource allocation techniques is introduced.
A Survey on Resource Allocation in Cloud Computingneirew J
Cloud computing is an on-demand service resource which includes applications to data centers on a
pay-per-use basis. In order to allocate these resources properly and satisfy users’ demands, an efficient
and flexible resource allocation mechanism is needed. Due to increasing user demand, the resource
allocating process has become more challenging and difficult. One of the main focuses of research
scholars is how to develop optimal solutions for this process. In this paper, a literature review on proposed
dynamic resource allocation techniques is introduced.
This document proposes a framework called SLA-Based resource allocation to reduce infrastructure costs and minimize violations of service level agreements (SLAs) for Software as a Service (SaaS) providers. The framework maps customer requests to infrastructure parameters, handles dynamic changes in customer demands, and allocates virtual machines based on SLAs while considering heterogeneity of resources. The goal is to maximize the SaaS provider's profit by optimizing resource usage and reducing penalties from SLA violations when customers dynamically change resource sharing.
This document discusses applying transaction cost theory to analyze the economics of cloud computing from the customer perspective. It conducted interviews with cloud vendors, customers, and consultants to understand various costs associated with cloud computing beyond just the pricing. The findings indicate that cloud computing has high "asset specificity" due to costs of change management, additional services, and business process reengineering. It also has high levels of "uncertainty" requiring management of contracts, cloud-specific monitoring solutions, and legal compliance reviews. However, cloud computing has high "transaction frequency" which can compensate for the costs of uncertainty and asset specificity. The goal of the research is to provide a more comprehensive understanding of the total costs of cloud computing.
An Analysis on Business Value of Cloud ComputingIOSR Journals
This document analyzes the business value of cloud computing. It begins by defining cloud computing as a model for enabling on-demand access to shared computing resources over the internet. The key concepts of cloud computing including on-demand self-service, broad network access, resource pooling, rapid elasticity, and measured service are described. The three cloud computing service models - Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) - are outlined. The four deployment models of public, private, hybrid, and community clouds are also discussed. The document explores how cloud computing benefits business models by providing flexibility and a pay-as-you-go option. Ch
Dynamic congestion management system for cloud service brokerIJECEIAES
The cloud computing model offers a shared pool of resources and services with diverse models presented to the clients through the internet by an on-demand scalable and dynamic pay-per-use model. The developers have identified the need for an automated system (cloud service broker (CSB)) that can contribute to exploiting the cloud capability, enhancing its functionality, and improving its performance. This research presents a dynamic congestion management (DCM) system which can manage the massive amount of cloud requests while considering the required quality for the clients’ requirements as regulated by the service-level policy. In addition, this research introduces a forwarding policy that can be utilized to choose high-priority calls coming from the cloud service requesters and passes them by the broker to the suitable cloud resources. The policy has made use of one of the mechanisms that are used by Cisco to assist the administration of the congestion that might take place at the broker side. Furthermore, the DCM system is used to help in provisioning and monitoring the works of the cloud providers through the job operation. The proposed DCM system was implemented and evaluated by using the CloudSim tool.
The recent surge in cloud computing arises from its ability to provide software, infrastructure, and platform services without requiring large investments or expenses to manage and operate them. Clouds typically involve service providers,
Infrastructure / resource providers, and service users (or clients). They include applications delivered as services, as well as the hardware and software systems providing these services. Our proposed framework for generic cloud collaboration allows clients and cloud applications to simultaneously use services from and route data among multiple clouds. This framework supports universal and dynamic collaboration in a multicloud system. It lets clients simultaneously use services from multiple clouds without prior business agreements among (CSP) cloud service providers, and without adopting common standards and specifications.
Apache Hadoop is an open-source software framework for distributed storage and processing of large datasets across clusters of computers. It consists of Hadoop Common (libraries and utilities), HDFS (distributed file system), YARN (resource management), and MapReduce (programming model). Hadoop is designed to reliably handle failures of individual machines or racks of machines by detecting and handling failures in software. It allows programming in any language using Hadoop Streaming and exposes higher-level interfaces like Pig Latin and SQL through related projects.
Similar to Pricing Models for Cloud Computing Services, a Survey (20)
Text Mining in Digital Libraries using OKAPI BM25 ModelEditor IJCATR
The emergence of the internet has made vast amounts of information available and easily accessible online. As a result, most libraries have digitized their content in order to remain relevant to their users and to keep pace with the advancement of the internet. However, these digital libraries have been criticized for using inefficient information retrieval models that do not perform relevance ranking to the retrieved results. This paper proposed the use of OKAPI BM25 model in text mining so as means of improving relevance ranking of digital libraries. Okapi BM25 model was selected because it is a probability-based relevance ranking algorithm. A case study research was conducted and the model design was based on information retrieval processes. The performance of Boolean, vector space, and Okapi BM25 models was compared for data retrieval. Relevant ranked documents were retrieved and displayed at the OPAC framework search page. The results revealed that Okapi BM 25 outperformed Boolean model and Vector Space model. Therefore, this paper proposes the use of Okapi BM25 model to reward terms according to their relative frequencies in a document so as to improve the performance of text mining in digital libraries.
Green Computing, eco trends, climate change, e-waste and eco-friendlyEditor IJCATR
This document discusses green computing practices and sustainable IT services. It provides an overview of factors driving adoption of green computing to reduce costs and environmental impact of data centers, such as rising energy costs and density. Green strategies discussed include improving infrastructure efficiency, power management, thermal management, efficient product design, and virtualization to optimize resource utilization. The document examines how green computing aims to lower costs and environmental footprint, and how sustainable IT services take a broader approach considering economic, environmental and social impacts.
Policies for Green Computing and E-Waste in NigeriaEditor IJCATR
Computers today are an integral part of individuals’ lives all around the world, but unfortunately these devices are toxic to the environment given the materials used, their limited battery life and technological obsolescence. Individuals are concerned about the hazardous materials ever present in computers, even if the importance of various attributes differs, and that a more environment -friendly attitude can be obtained through exposure to educational materials. In this paper, we aim to delineate the problem of e-waste in Nigeria and highlight a series of measures and the advantage they herald for our country and propose a series of action steps to develop in these areas further. It is possible for Nigeria to have an immediate economic stimulus and job creation while moving quickly to abide by the requirements of climate change legislation and energy efficiency directives. The costs of implementing energy efficiency and renewable energy measures are minimal as they are not cash expenditures but rather investments paid back by future, continuous energy savings.
Performance Evaluation of VANETs for Evaluating Node Stability in Dynamic Sce...Editor IJCATR
Vehicular ad hoc networks (VANETs) are a favorable area of exploration which empowers the interconnection amid the movable vehicles and between transportable units (vehicles) and road side units (RSU). In Vehicular Ad Hoc Networks (VANETs), mobile vehicles can be organized into assemblage to promote interconnection links. The assemblage arrangement according to dimensions and geographical extend has serious influence on attribute of interaction .Vehicular ad hoc networks (VANETs) are subclass of mobile Ad-hoc network involving more complex mobility patterns. Because of mobility the topology changes very frequently. This raises a number of technical challenges including the stability of the network .There is a need for assemblage configuration leading to more stable realistic network. The paper provides investigation of various simulation scenarios in which cluster using k-means algorithm are generated and their numbers are varied to find the more stable configuration in real scenario of road.
Optimum Location of DG Units Considering Operation ConditionsEditor IJCATR
The optimal sizing and placement of Distributed Generation units (DG) are becoming very attractive to researchers these days. In this paper a two stage approach has been used for allocation and sizing of DGs in distribution system with time varying load model. The strategic placement of DGs can help in reducing energy losses and improving voltage profile. The proposed work discusses time varying loads that can be useful for selecting the location and optimizing DG operation. The method has the potential to be used for integrating the available DGs by identifying the best locations in a power system. The proposed method has been demonstrated on 9-bus test system.
Analysis of Comparison of Fuzzy Knn, C4.5 Algorithm, and Naïve Bayes Classifi...Editor IJCATR
Early detection of diabetes mellitus (DM) can prevent or inhibit complication. There are several laboratory test that must be done to detect DM. The result of this laboratory test then converted into data training. Data training used in this study generated from UCI Pima Database with 6 attributes that were used to classify positive or negative diabetes. There are various classification methods that are commonly used, and in this study three of them were compared, which were fuzzy KNN, C4.5 algorithm and Naïve Bayes Classifier (NBC) with one identical case. The objective of this study was to create software to classify DM using tested methods and compared the three methods based on accuracy, precision, and recall. The results showed that the best method was Fuzzy KNN with average and maximum accuracy reached 96% and 98%, respectively. In second place, NBC method had respective average and maximum accuracy of 87.5% and 90%. Lastly, C4.5 algorithm had average and maximum accuracy of 79.5% and 86%, respectively.
Web Scraping for Estimating new Record from Source SiteEditor IJCATR
Study in the Competitive field of Intelligent, and studies in the field of Web Scraping, have a symbiotic relationship mutualism. In the information age today, the website serves as a main source. The research focus is on how to get data from websites and how to slow down the intensity of the download. The problem that arises is the website sources are autonomous so that vulnerable changes the structure of the content at any time. The next problem is the system intrusion detection snort installed on the server to detect bot crawler. So the researchers propose the use of the methods of Mining Data Records and the method of Exponential Smoothing so that adaptive to changes in the structure of the content and do a browse or fetch automatically follow the pattern of the occurrences of the news. The results of the tests, with the threshold 0.3 for MDR and similarity threshold score 0.65 for STM, using recall and precision values produce f-measure average 92.6%. While the results of the tests of the exponential estimation smoothing using ? = 0.5 produces MAE 18.2 datarecord duplicate. It slowed down to 3.6 datarecord from 21.8 datarecord results schedule download/fetch fix in an average time of occurrence news.
Evaluating Semantic Similarity between Biomedical Concepts/Classes through S...Editor IJCATR
Most of the existing semantic similarity measures that use ontology structure as their primary source can measure semantic similarity between concepts/classes using single ontology. The ontology-based semantic similarity techniques such as structure-based semantic similarity techniques (Path Length Measure, Wu and Palmer’s Measure, and Leacock and Chodorow’s measure), information content-based similarity techniques (Resnik’s measure, Lin’s measure), and biomedical domain ontology techniques (Al-Mubaid and Nguyen’s measure (SimDist)) were evaluated relative to human experts’ ratings, and compared on sets of concepts using the ICD-10 “V1.0” terminology within the UMLS. The experimental results validate the efficiency of the SemDist technique in single ontology, and demonstrate that SemDist semantic similarity techniques, compared with the existing techniques, gives the best overall results of correlation with experts’ ratings.
Semantic Similarity Measures between Terms in the Biomedical Domain within f...Editor IJCATR
The techniques and tests are tools used to define how measure the goodness of ontology or its resources. The similarity between biomedical classes/concepts is an important task for the biomedical information extraction and knowledge discovery. However, most of the semantic similarity techniques can be adopted to be used in the biomedical domain (UMLS). Many experiments have been conducted to check the applicability of these measures. In this paper, we investigate to measure semantic similarity between two terms within single ontology or multiple ontologies in ICD-10 “V1.0” as primary source, and compare my results to human experts score by correlation coefficient.
A Strategy for Improving the Performance of Small Files in Openstack Swift Editor IJCATR
This is an effective way to improve the storage access performance of small files in Openstack Swift by adding an aggregate storage module. Because Swift will lead to too much disk operation when querying metadata, the transfer performance of plenty of small files is low. In this paper, we propose an aggregated storage strategy (ASS), and implement it in Swift. ASS comprises two parts which include merge storage and index storage. At the first stage, ASS arranges the write request queue in chronological order, and then stores objects in volumes. These volumes are large files that are stored in Swift actually. During the short encounter time, the object-to-volume mapping information is stored in Key-Value store at the second stage. The experimental results show that the ASS can effectively improve Swift's small file transfer performance.
Integrated System for Vehicle Clearance and RegistrationEditor IJCATR
Efficient management and control of government's cash resources rely on government banking arrangements. Nigeria, like many low income countries, employed fragmented systems in handling government receipts and payments. Later in 2016, Nigeria implemented a unified structure as recommended by the IMF, where all government funds are collected in one account would reduce borrowing costs, extend credit and improve government's fiscal policy among other benefits to government. This situation motivated us to embark on this research to design and implement an integrated system for vehicle clearance and registration. This system complies with the new Treasury Single Account policy to enable proper interaction and collaboration among five different level agencies (NCS, FRSC, SBIR, VIO and NPF) saddled with vehicular administration and activities in Nigeria. Since the system is web based, Object Oriented Hypermedia Design Methodology (OOHDM) is used. Tools such as Php, JavaScript, css, html, AJAX and other web development technologies were used. The result is a web based system that gives proper information about a vehicle starting from the exact date of importation to registration and renewal of licensing. Vehicle owner information, custom duty information, plate number registration details, etc. will also be efficiently retrieved from the system by any of the agencies without contacting the other agency at any point in time. Also number plate will no longer be the only means of vehicle identification as it is presently the case in Nigeria, because the unified system will automatically generate and assigned a Unique Vehicle Identification Pin Number (UVIPN) on payment of duty in the system to the vehicle and the UVIPN will be linked to the various agencies in the management information system.
Assessment of the Efficiency of Customer Order Management System: A Case Stu...Editor IJCATR
The Supermarket Management System deals with the automation of buying and selling of good and services. It includes both sales and purchase of items. The project Supermarket Management System is to be developed with the objective of making the system reliable, easier, fast, and more informative.
Energy-Aware Routing in Wireless Sensor Network Using Modified Bi-Directional A*Editor IJCATR
Energy is a key component in the Wireless Sensor Network (WSN)[1]. The system will not be able to run according to its function without the availability of adequate power units. One of the characteristics of wireless sensor network is Limitation energy[2]. A lot of research has been done to develop strategies to overcome this problem. One of them is clustering technique. The popular clustering technique is Low Energy Adaptive Clustering Hierarchy (LEACH)[3]. In LEACH, clustering techniques are used to determine Cluster Head (CH), which will then be assigned to forward packets to Base Station (BS). In this research, we propose other clustering techniques, which utilize the Social Network Analysis approach theory of Betweeness Centrality (BC) which will then be implemented in the Setup phase. While in the Steady-State phase, one of the heuristic searching algorithms, Modified Bi-Directional A* (MBDA *) is implemented. The experiment was performed deploy 100 nodes statically in the 100x100 area, with one Base Station at coordinates (50,50). To find out the reliability of the system, the experiment to do in 5000 rounds. The performance of the designed routing protocol strategy will be tested based on network lifetime, throughput, and residual energy. The results show that BC-MBDA * is better than LEACH. This is influenced by the ways of working LEACH in determining the CH that is dynamic, which is always changing in every data transmission process. This will result in the use of energy, because they always doing any computation to determine CH in every transmission process. In contrast to BC-MBDA *, CH is statically determined, so it can decrease energy usage.
Security in Software Defined Networks (SDN): Challenges and Research Opportun...Editor IJCATR
In networks, the rapidly changing traffic patterns of search engines, Internet of Things (IoT) devices, Big Data and data centers has thrown up new challenges for legacy; existing networks; and prompted the need for a more intelligent and innovative way to dynamically manage traffic and allocate limited network resources. Software Defined Network (SDN) which decouples the control plane from the data plane through network vitalizations aims to address these challenges. This paper has explored the SDN architecture and its implementation with the OpenFlow protocol. It has also assessed some of its benefits over traditional network architectures, security concerns and how it can be addressed in future research and related works in emerging economies such as Nigeria.
Measure the Similarity of Complaint Document Using Cosine Similarity Based on...Editor IJCATR
Report handling on "LAPOR!" (Laporan, Aspirasi dan Pengaduan Online Rakyat) system depending on the system administrator who manually reads every incoming report [3]. Read manually can lead to errors in handling complaints [4] if the data flow is huge and grows rapidly, it needs at least three days to prepare a confirmation and it sensitive to inconsistencies [3]. In this study, the authors propose a model that can measure the identities of the Query (Incoming) with Document (Archive). The authors employed Class-Based Indexing term weighting scheme, and Cosine Similarities to analyse document similarities. CoSimTFIDF, CoSimTFICF and CoSimTFIDFICF values used in classification as feature for K-Nearest Neighbour (K-NN) classifier. The optimum result evaluation is pre-processing employ 75% of training data ratio and 25% of test data with CoSimTFIDF feature. It deliver a high accuracy 84%. The k = 5 value obtain high accuracy 84.12%
Hangul Recognition Using Support Vector MachineEditor IJCATR
The recognition of Hangul Image is more difficult compared with that of Latin. It could be recognized from the structural arrangement. Hangul is arranged from two dimensions while Latin is only from the left to the right. The current research creates a system to convert Hangul image into Latin text in order to use it as a learning material on reading Hangul. In general, image recognition system is divided into three steps. The first step is preprocessing, which includes binarization, segmentation through connected component-labeling method, and thinning with Zhang Suen to decrease some pattern information. The second is receiving the feature from every single image, whose identification process is done through chain code method. The third is recognizing the process using Support Vector Machine (SVM) with some kernels. It works through letter image and Hangul word recognition. It consists of 34 letters, each of which has 15 different patterns. The whole patterns are 510, divided into 3 data scenarios. The highest result achieved is 94,7% using SVM kernel polynomial and radial basis function. The level of recognition result is influenced by many trained data. Whilst the recognition process of Hangul word applies to the type 2 Hangul word with 6 different patterns. The difference of these patterns appears from the change of the font type. The chosen fonts for data training are such as Batang, Dotum, Gaeul, Gulim, Malgun Gothic. Arial Unicode MS is used to test the data. The lowest accuracy is achieved through the use of SVM kernel radial basis function, which is 69%. The same result, 72 %, is given by the SVM kernel linear and polynomial.
Application of 3D Printing in EducationEditor IJCATR
This paper provides a review of literature concerning the application of 3D printing in the education system. The review identifies that 3D Printing is being applied across the Educational levels [1] as well as in Libraries, Laboratories, and Distance education systems. The review also finds that 3D Printing is being used to teach both students and trainers about 3D Printing and to develop 3D Printing skills.
Survey on Energy-Efficient Routing Algorithms for Underwater Wireless Sensor ...Editor IJCATR
In underwater environment, for retrieval of information the routing mechanism is used. In routing mechanism there are three to four types of nodes are used, one is sink node which is deployed on the water surface and can collect the information, courier/super/AUV or dolphin powerful nodes are deployed in the middle of the water for forwarding the packets, ordinary nodes are also forwarder nodes which can be deployed from bottom to surface of the water and source nodes are deployed at the seabed which can extract the valuable information from the bottom of the sea. In underwater environment the battery power of the nodes is limited and that power can be enhanced through better selection of the routing algorithm. This paper focuses the energy-efficient routing algorithms for their routing mechanisms to prolong the battery power of the nodes. This paper also focuses the performance analysis of the energy-efficient algorithms under which we can examine the better performance of the route selection mechanism which can prolong the battery power of the node
Comparative analysis on Void Node Removal Routing algorithms for Underwater W...Editor IJCATR
The designing of routing algorithms faces many challenges in underwater environment like: propagation delay, acoustic channel behaviour, limited bandwidth, high bit error rate, limited battery power, underwater pressure, node mobility, localization 3D deployment, and underwater obstacles (voids). This paper focuses the underwater voids which affects the overall performance of the entire network. The majority of the researchers have used the better approaches for removal of voids through alternate path selection mechanism but still research needs improvement. This paper also focuses the architecture and its operation through merits and demerits of the existing algorithms. This research article further focuses the analytical method of the performance analysis of existing algorithms through which we found the better approach for removal of voids
Decay Property for Solutions to Plate Type Equations with Variable CoefficientsEditor IJCATR
In this paper we consider the initial value problem for a plate type equation with variable coefficients and memory in
1 n R n ), which is of regularity-loss property. By using spectrally resolution, we study the pointwise estimates in the spectral
space of the fundamental solution to the corresponding linear problem. Appealing to this pointwise estimates, we obtain the global
existence and the decay estimates of solutions to the semilinear problem by employing the fixed point theorem
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
Removing Uninteresting Bytes in Software FuzzingAftab Hussain
Imagine a world where software fuzzing, the process of mutating bytes in test seeds to uncover hidden and erroneous program behaviors, becomes faster and more effective. A lot depends on the initial seeds, which can significantly dictate the trajectory of a fuzzing campaign, particularly in terms of how long it takes to uncover interesting behaviour in your code. We introduce DIAR, a technique designed to speedup fuzzing campaigns by pinpointing and eliminating those uninteresting bytes in the seeds. Picture this: instead of wasting valuable resources on meaningless mutations in large, bloated seeds, DIAR removes the unnecessary bytes, streamlining the entire process.
In this work, we equipped AFL, a popular fuzzer, with DIAR and examined two critical Linux libraries -- Libxml's xmllint, a tool for parsing xml documents, and Binutil's readelf, an essential debugging and security analysis command-line tool used to display detailed information about ELF (Executable and Linkable Format). Our preliminary results show that AFL+DIAR does not only discover new paths more quickly but also achieves higher coverage overall. This work thus showcases how starting with lean and optimized seeds can lead to faster, more comprehensive fuzzing campaigns -- and DIAR helps you find such seeds.
- These are slides of the talk given at IEEE International Conference on Software Testing Verification and Validation Workshop, ICSTW 2022.
Cosa hanno in comune un mattoncino Lego e la backdoor XZ?Speck&Tech
ABSTRACT: A prima vista, un mattoncino Lego e la backdoor XZ potrebbero avere in comune il fatto di essere entrambi blocchi di costruzione, o dipendenze di progetti creativi e software. La realtà è che un mattoncino Lego e il caso della backdoor XZ hanno molto di più di tutto ciò in comune.
Partecipate alla presentazione per immergervi in una storia di interoperabilità, standard e formati aperti, per poi discutere del ruolo importante che i contributori hanno in una comunità open source sostenibile.
BIO: Sostenitrice del software libero e dei formati standard e aperti. È stata un membro attivo dei progetti Fedora e openSUSE e ha co-fondato l'Associazione LibreItalia dove è stata coinvolta in diversi eventi, migrazioni e formazione relativi a LibreOffice. In precedenza ha lavorato a migrazioni e corsi di formazione su LibreOffice per diverse amministrazioni pubbliche e privati. Da gennaio 2020 lavora in SUSE come Software Release Engineer per Uyuni e SUSE Manager e quando non segue la sua passione per i computer e per Geeko coltiva la sua curiosità per l'astronomia (da cui deriva il suo nickname deneb_alpha).
Generating privacy-protected synthetic data using Secludy and MilvusZilliz
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Have you ever been confused by the myriad of choices offered by AWS for hosting a website or an API?
Lambda, Elastic Beanstalk, Lightsail, Amplify, S3 (and more!) can each host websites + APIs. But which one should we choose?
Which one is cheapest? Which one is fastest? Which one will scale to meet our needs?
Join me in this session as we dive into each AWS hosting service to determine which one is best for your scenario and explain why!
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
In his public lecture, Christian Timmerer provides insights into the fascinating history of video streaming, starting from its humble beginnings before YouTube to the groundbreaking technologies that now dominate platforms like Netflix and ORF ON. Timmerer also presents provocative contributions of his own that have significantly influenced the industry. He concludes by looking at future challenges and invites the audience to join in a discussion.
How to Get CNIC Information System with Paksim Ga.pptxdanishmna97
Pakdata Cf is a groundbreaking system designed to streamline and facilitate access to CNIC information. This innovative platform leverages advanced technology to provide users with efficient and secure access to their CNIC details.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Things to Consider When Choosing a Website Developer for your Website | FODUUFODUU
Choosing the right website developer is crucial for your business. This article covers essential factors to consider, including experience, portfolio, technical skills, communication, pricing, reputation & reviews, cost and budget considerations and post-launch support. Make an informed decision to ensure your website meets your business goals.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
AI-Powered Food Delivery Transforming App Development in Saudi Arabia.pdfTechgropse Pvt.Ltd.
In this blog post, we'll delve into the intersection of AI and app development in Saudi Arabia, focusing on the food delivery sector. We'll explore how AI is revolutionizing the way Saudi consumers order food, how restaurants manage their operations, and how delivery partners navigate the bustling streets of cities like Riyadh, Jeddah, and Dammam. Through real-world case studies, we'll showcase how leading Saudi food delivery apps are leveraging AI to redefine convenience, personalization, and efficiency.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems
Pricing Models for Cloud Computing Services, a Survey
1. International Journal of Computer Applications Technology and Research
Volume 5– Issue 3, 126 - 131, 2016, ISSN:- 2319–8656
www.ijcat.com 126
Pricing Models for Cloud Computing Services, a Survey
Taj Eldin Suliman M. Ali
College of Graduate Studies,
Computer Science and Information Technology
Sudan University for science and technology
Khartoum, Sudan
Hany H. Ammar
Lane Department of Computer Science and
Electrical Engineering,
College of Engineering and Mineral Resources
West Virginia University
Morgantown, USA
Abstract: Recently, citizens and companies can access utility computing services by using Cloud Computing. These services such as
infrastructures, platforms and applications could be accessed on-demand whenever it is needed. In Cloud Computing, different types of
resources would be required to provide services, but the demands such as requests rates and user's requirements of these services and
the cost of the required resources are continuously varying. Therefore, Service Level Agreements would be needed to guarantee the
service's prices and the offered Quality of Services which are always dependable and interrelated to guarantee revenues maximization
for cloud providers as well as improve customers' satisfaction level. Cloud consumers are always searching for a cloud provider who
provides good service with the least price, so Cloud provider should use advanced technologies and frameworks to increase QoS, and
decrease cost. This paper provides a survey on cloud pricing models and analyzes the recent and relevant research in this field.
Keywords: Cloud Computing; Software-as-a-Service (SaaS); Service Level Agreement (SLA); Dynamic pricing; Quality of Service
(QoS); revenue maximization; CSL.
1. INTRODUCTION
Cloud computing is an emerging parallel and distributed
computing paradigm that depends on the internet to deploy
computer resources and services dynamically and enables a
provider to deploy a single application to execute in multiple
machines based on a contract between the cloud providers and
the consumers called Service Level Agreement (SLA).
Traditionally, the resource/service price is defined in SLA and
remains static. This static pricing mechanism has several
problems such as overprovisioning as well as under
provisioning problems. On the other hand, dynamic pricing is
needed to overcome these problems. The central objectives of
cloud provider are profit maximization and increase customer
satisfaction level (CSL) i.e. the market sharing maximization.
To achieve these objectives, the cloud provider need to reduce
cost, SLA violations, response time, and power consumption;
and deploy services in different prices (Dynamic pricing)
based on the current consumer's requirements as well as the
level of the offered QoS. On the contrary, the main objectives
of cloud consumers are minimizing cost (price) and access
services with high quality of services (QoS). To achieve all of
these objectives - provider's and consumer's objectives -, the
negotiation between them would be established through
service level agreement (SLA).
“Service Level Agreement (SLA) is an agreement used to
guarantee web service delivery, it defines the understanding
and expectations from a service provider and service
consumer” [1]. SLA is a legal contract that grantees Quality of
Service (QoS) between the cloud provider and the consumers.
This contract includes and defines many things, such as
parties, services, prices, service level objectives (SLOs),
obligations, penalties.
The business organization uses SLA to enlarge market sharing
because, through SLA, the provider can increase CSL; as a
result improve its profits. When SLA is violated, the CSL go
down and some penalties would be enforced.
1.1 Background
The Cloud model is cost-effective i.e. the price is reasonable
because cloud consumers only pay for their actual usage, they
do not need to pay any upfront costs. Also, it is elastic as the
cloud provider can deliver more or less according to the
customers' needs.
Cloud provider offers different services to cloud consumers
[14] at different prices, therefore, two stakeholders – cloud
provider and cloud consumer - would be communicated and
negotiated about several things such as QoS, price, etc. All of
the negotiation points would be written in SLA clearly. Pricing
represents an important indicator for success business
companies which provide services or products [15]. Cloud
provider uses several pricing models to specify the price. This
pricing model would be established properly to define the fair
price for both stakeholders (providers and consumers). A good
pricing model supports cloud providers to achieve their
objectives such as profit maximization; meanwhile it
considers the cloud consumers.
1.2 Cloud Computing
1.2.1. Cloud Computing Definitions
Definition 1: “Cloud computing is a model for enabling
convenient, on-demand network access to a shared pool of
configurable computing resources (for example, networks,
servers, storage, applications, and services) that can be
rapidly provisioned and released with minimal management
effort or service-provider interaction.” [17].
Definition 2: “A Cloud is a type of parallel and distributed
system consisting of a collection of inter-connected and
virtualized computers that are dynamically provisioned and
presented as one or more unified computing resource(s) based
on service-level agreements established through negotiation
between the service provider and consumer.” [4].
Definition 3: “Cloud computing is a large-scale distributed
computing paradigm that is driven by economies of scale, in
which a pool of abstracted, virtualized, dynamically-scalable,
managed computing power, storage, platforms, and services
2. International Journal of Computer Applications Technology and Research
Volume 5– Issue 3, 126 - 131, 2016, ISSN:- 2319–8656
www.ijcat.com 127
are delivered on demand to external customers over the
Internet.”[3]
1.2.2. Cloud Computing Deployment Models
Cloud Computing approach is designed mainly to achieve
many services generally and services deployment particularly.
To deploy services, Cloud computing has several deployment
models, such as public, private, community, and hybrid cloud.
The brief descriptions for these models as follows:
Public Cloud: through this model, services could be
provisioned for general consumers, and cloud provider
responsible for several thing main of them is
infrastructure.
Private Cloud: it is a model by which services could be
deployed for particular consumers in an organization, the
needed infrastructure owned and managed by the
organization or by other third party organization.
Community Cloud: at this model, cloud provider deploys
services to organizations that have common objectives and
policies, the needed infrastructure could be managed by
one of these organizations or by the third party.
Hybrid Cloud: Sometimes environment requiring a
combination of two or more mentioned deployment
models, at this case service provisioned by other model
called a hybrid cloud.
1.2.3. Cloud Computing Service Models
Cloud computing providers offer their services for cloud
consumers through using three fundamental models [5],
software-as-a-service (SaaS), platform-as-a-service (PaaS),
and infrastructure-as-a-service (IaaS).
SaaS model: at this model, consumers use the internet to
access services (applications) which could be hosted in
service provider's company. There would be two
cornerstones, the provider, and the consumer. Service
provider controls everything whereas service consumer
controls application settings only. The common examples
of SaaS are Facebook and Twitter. [5]
PaaS model: through this model, providers deploy several
things such as tools, programming environments, and
configuration management for consumers to support them
to deploy and develop the application. PaaS consumer's
examples are software designers, testers, administrators,
and developers. Common example of PaaS is Google
AppEngine [8].
IaaS model: this model enables providers to deploy virtual
machines (VMs); storage places …etc for service
consumers to help them to build systems. Some example
of IaaS consumers are system administrators and system
developers. Common example of IaaS is Amazon EC2 [6].
1.3 Objective
The objective of this paper is to survey current research on
cloud computing pricing models, and analyze and compare
their characteristics. We focus on SaaS services. We compare
static and dynamic models, and identify the weaknesses of
existing models.
1.4 Organization
The rest of the paper organized as follows: in the next section
the researcher introduces Cloud Computing pricing models, its
important concepts, classification, and provides some
examples. In section three the paper focuses on the related
works to cloud pricing, discusses some of the existing works
and draws a comparison among the common existing pricing
models. In the last section, the paper gives relevant conclusion
and offers some suggestions.
2. CLOUD COMPUTING PRICING
MODELS:
Demands and revenues are controlled by several factors. And
"pricing" is considered to be the most important one. Cloud
providers always use pricing to know (1) how much service
provisioning could be done for different consumers (2) the
relationship between pricing and other issues such as
provisioning period and grant discounts.
2.1. Cloud Computing Pricing Model
classification:
As mentioned in [7, 21], the two common types of pricing
models are:
Fixed Pricing Model: Here the price charging doesn't
change, and the cloud provider is someone who determines
the price to the resource type in advance. For example,
Amazon provides disk space for $0.15/GB, and service
consumers have the same services at all time, such as Pay-
per-use model. According to Yeoa et al. [2], fixed pricing
model is more straightforward and easy to understand, but
it is unfair for all customers because they are not having
the same needs.
Dynamic Pricing Model: In this model the price charging
changes dynamically according to market status quo. The
service price could be calculated for each request
according to the pricing mechanism that is used. In this
case, service consumer requests and receives several types
and levels of services in need, such as Market-dependant
pricing model.
Table1 bellow shows the strength and weakness of the above
types of pricing models:
Table1. Fixed pricing vs. dynamic pricing
Pricing
Model
Advantages
Disadvantages
Fixed
pricing
model
It supports
assurances for
consumers.
Consumers
know how
much they will
pay.
More
consistent.
It reduces
risks.
Make profit
estimation
easy.
Unfair for
consumer: If the
user doesn't
consume the
resource
extensively, he/she
may pay more than
his/her real
utilization.
It does not allow
provider to change
price at any
account.
Unfair for provider:
During proper
resource utilization
consumer may pay
less than his/her real
utilization.
Dynamic
pricing
model
It supports
provider to
maximize
profits with
each
consumer.
Some consumers
are not interested in
this model as they
prefer a fixed price
to dynamic price.
Consumers who pay
more feel inequality
3. International Journal of Computer Applications Technology and Research
Volume 5– Issue 3, 126 - 131, 2016, ISSN:- 2319–8656
www.ijcat.com 128
Fair for
consumer as it
enables him to
pay according
to the offered
QoS.
It supports
provider to set
price based on
current state of
the market
(season or
supply and
demand)
consequently having
negative opinions.
In some
environments such
as entertainment
sites consumers do
not prefer dynamic
pricing.
Financially, the economic efficiency could be measured by
two indicators i) the number of allocated resources for
providers, and the total of the achieved consumers' requests.
ii) The average of the consumers' welfare. Authors of [20]
draw a comparison among the number of the achieved
consumers' requests, the number of provider's allocated
resources, and the average of consumer's welfare with a fixed
pricing.
According to [9], in cloud computing, there are several points
that determine the price, as follow:
The annual costs: it is the fees that cloud provider pays
annually to buy the resources.
The period: it is the leasing period of resources by
consumers. In this respect some provider confirms that
service price could be decreased if the leasing period is
long.
Quality of Services: it is the quality assurance that the
cloud providers use to identify the entity of service. Such as
service availability, security, and privacy. Some providers
increase service price if the level of QoS for service is high.
The level of resource: it is the age of resource that the cloud
consumer rents. Some providers say that older resources
mean lower price.
Maintenance fees: it is the annual cost to maintain and
secure resources. Some rented resources become weak or
damaged because of the continuous use. These resources
could be maintained.
Consumers can assess the providers depending on the
following factors:
Pricing Scheme: the mechanism in which service price
could be determined, such as pay-as-you-go model.
Service Customizability: the way by which provider
customizes his SaaS services to meet service consumer's
requirements.
Leasing period: the period, at which customers can
consume services, some examples of this period are
subscription, pay-per-use, and perpetual.
Service QoS: the mechanism by which service
requirements could be specified; such as scalability,
availability, and security.
2.2. Examples of Cloud Pricing Models:
There are several pricing models, as follow:
Pay-as-you-go Model: in this model, the price could be
determined by the cloud provider and remains static.
Customer pays a fixed price and reserves resources due to
the paid period. On the contrary, the customer may utilize
the resource improperly i.e. the consumer gets less
benefit.[8]
Subscription Model: here, the price depends on
subscription period. If the consumer utilizes resources
extensively, the underprovisioning problem will occur.
Also, the overprovisioning problem occurs when the
customer is not consuming the resources extensively. [8]
Pricing algorithm for cloud computing Resources: this is
a real-time approach, in which provider can maximize
revenues and minimize cost. This approach is just a
theoretical, and not yet applied. [12]
Dynamic resource pricing on federated clouds: it is a fair
theoretical approach for both provider and consumers
because it is dynamic – the price depends on the level of
supply and demand. [10]
Competition-based pricing model: it is a dynamic
approach because the determined price depends on
competition. This approach could be implemented easily,
but it neglects the customers. [13]
3. RELATED WORK
This section discusses several existing works, presents weak
points, and finally compares some of the pricing models.
In [9] the authors proposed a novel financial economic model,
in which customers can gain a high level of QoS. The authors
noted that the optimal price by which service provider can
recover the initial cost, which was defined between two
boundaries. They use the financial option theory to define the
lower boundary and the Moor's law to define the upper
boundary. However, it disregards the maintenance costs. In
[6, 8, 11] the authors implemented pay-as-you-go pricing
model, by which service provider can determine a fixed price.
Here, if there is a high demand, the service provider is not
allowed to change the period of (resource reservation) or raise
a price. On the other side if the demand is low, the consumer
negatively pays more than his/her real usage. In [6, 8, 11], the
authors implemented subscription pricing model, by which the
price determined according to a period of subscription. This
model is good if the customer consumes the service
extensively. However, a consumer may do not consume
service properly (pay more than use).
In [12], authors introduced Pricing algorithm for cloud
computing resources, that could be used for minimizing cost
as well as maximizing profits for the service provider.
However, this is a fixed model and not suitable on
supply/demand changes.
Dynamic resource pricing on federated clouds was introduced
in [10], by which the price could be determined depending on
the level of supply and demand. However, this model does not
support a good scalability during high demand period.
In [13], authors implemented Competition-based pricing
model, by which provider sets the price according to
competitors. However, in this model, consumers are not taken
into consideration.
Customer-based pricing model in [2] was introduced that; the
price could be specified according to the customers' needs
(what the consumer ready to pay). However, the consumer
does not know what he/she is ready to pay at every time.
Table2 shows a comparison among several cloud pricing
models, considering the following criteria: the mechanism to
determine the price, whether the model is static or dynamic,
and the advantages and disadvantages.
Table2. Comparison of several cloud pricing models
4. International Journal of Computer Applications Technology and Research
Volume 5– Issue 3, 126 - 131, 2016, ISSN:- 2319–8656
www.ijcat.com 129
# Pricing Model Type
(Static/
Dynamic)
Nature (
Implemented/
theoretical )
Mechanism Advantages Disadvantages
1
Subscription
Model [8, 11]
Static Implemented Cloud provider defines
Resource/Service prices
depending on lease period
It is good for consumer
when
Resources/Services are
utilized extensively
Consumer may pay
more than the real
utilization cost when
he/she does not use
Resources/Services
properly
2
Pay-as-you-go
Model [8, 11]
Static Implemented Cloud provider
determines a constant
Resource/Service price
Resources/Services are
available during
reservation period, and
the price is known
Overprovisioning
and
underprovisioning
problems may occur.
The price is
unchangeable
3
Pay-for-
resources
model [8, 11]
Static Implemented Cloud provider
determines
Resource/Service prices
according to the cost.
Maximizes resource
utilization
Difficult to be
implemented
4 Dynamic
resource
pricing on
federated
clouds [12]
Dynamic Theoretical Cloud provider uses
current level of supply/
demand to determine
Resource/Service prices
Increases consumers'
satisfaction and
maximizes the number
of their profitable
requests
It does not support a
good scalability
during high demand
period
5 Value-based
pricing [20]
Dynamic Implemented Resource/ Service prices
are defined depending on
the customer's point of
view
Increases revenues Hard to implement
6 Competition-
based pricing
[13]
Dynamic Implemented Cloud provider uses
competitors' prices to
determine the current
price for service/resource
Easy to implement Ignores the cloud
customers
7 Datacenter net
profit
optimization
with
individual job
deadlines [18]
Dynamic Theoretical Cloud provider uses job
scheduling mechanisms to
set Resource/ Service
prices
Maximizes cloud
provider's revenues,
minimizes power
consumption cost
It doesn't take in
consideration the
heterogeneous
servers.
Difficult to
implement
8 Genetic model
for pricing in
cloud
computing
markets [17]
Dynamic Theoretical Price is specified by cloud
provider depending on the
state of a real time
market.
Maximizes revenues,
flexible implementation
Very critical during
the (rise and fall)
demand period.
9 A novel
financial
economic
model [9]
Dynamic Theoretical Cloud provider sets
Resource/Service prices
between upper and lower
boundaries
Maximizes profits for
cloud provider and
improves QoS for cloud
consumer
Maintenance costs
are not taken in
consideration.
10 Customer-
based pricing
[13]
Dynamic Implemented Cloud consumers define
the current price
Cloud consumer is
taken into consideration
Difficult to set price
11 Cost-based
pricing [19]
Dynamic Implemented Cloud provider specifies
profit level to set
Resource/Service prices
Cloud provider can
define the price easily
It doesn't considers
cloud consumer
12 Pricing
algorithm for
cloud
computing
Resources
[10]
Dynamic Theoretical Resource/Service prices
are set according to the
current market state.
It is better for cloud
provider because it
maximizes revenues by
reducing cost
Useless when
supply/demand differ
quickly
5. International Journal of Computer Applications Technology and Research
Volume 5– Issue 3, 126 - 131, 2016, ISSN:- 2319–8656
www.ijcat.com 130
4. CONCLUSION
In this paper, we surveyed different types of cloud pricing models.
We compared static pricing model versus dynamic pricing model.
Based on this comparison, we conclude that on one hand the static
model is easy for both understand-ability and profit estimation but
some problems such as under provisioning and over provisioning
may occur. On the other hand the dynamic pricing model is fair for
consumers because it supports them to pay depending on the QoS
required; also it is fair for the provider so it help him to maximize
profits.
Also, during this survey, we presented detailed comparison among
twelve pricing models based on the following factors: the type
(static/dynamic), nature (theoretical/implemented), the mechanism
to determine price, the advantages, and disadvantages. Depending
on this comparison we note that all of the static models are
implemented but some of the dynamic models are theoretical, on
the static models the provider defines the price but on the dynamic
models the price could be defined by the provider to maximize
revenues and rarely optimized for the consumers.
In summary, due to the fact that cloud computing services have
dynamic behavior with pay-as-you-go models, it is necessary to
conclude that the dynamic pricing models are much more adequate
for the consumers because they adapt to different variable needs.
Also, they are batter for the providers because they need to support
Multi-Tenants and change (increase/decrease) in the price
depending on the market state. Finally, we noted that most of
pricing models favor the providers over the consumers. Our
research suggests that there is a need for new pricing models that
take the two stakeholders, the provider and the consumer, in its
consideration.
5. REFERENCES
[1] Jin, L. J., and Machiraju, V. A. Analysis on Service Level
Agreement of Web Services, (June 2002).
[2] C. S. Yeoa, S. Venugopalb, X. Chua and R. Buyyaa,
“Autonomic Metered Pricing for a Utility Computing
Service”, Future Generation Computer Syst., vol. 26, no. 8,
(2010).
[3] Foster I, Yong Z, Raicu I, Lu S Cloud computing and grid
computing 360-degree compared. In: Proc 2008 grid
computing environments workshop, pp 1–10, (2008).
[4] Buyya, R., and Alexida. D. A Case for Economy Grid
Architecture for Service Oriented Grid Computing. In
Proceedings of the 10th International Heterogeneous
Computing Workshop (HCW), San Francisco, CA, (2001).
[5] W. Voorsluys, J. Broberg, and R. Buyya, Introduction to
Cloud Computing,” Cloud Computing: Principles and
Paradigms, chapter 1, pp. 1–41.Technical Report HPL-
2002-180, Software Technology Laboratories, HP
Laboratories, (2011).
[6] Varia, J. Architecting Applications for the Amazon Cloud.
Cloud Computing: Principles and Paradigms, Buyya, R.,
Broberg, J., Goscinski, A. (eds), ISBN-13: 978-
0470887998, Wiley Press, New York, USA. Web -
http://aws.amazon.com. (2010).
[7] A. Osterwalder, “The Business Model Ontology – A
Proposition in a Design Science Approach”, Doctoral
thesis, University of Lausanne, (2004).
[8] Google App Engine, https://appengine.google.com/.(2015)
[9] B. Sharma, R. K. Thulasiram, P. Thulasiraman, S. K. Garg
and R. Buyya, “Pricing Cloud Compute Commodities: A
Novel Financial Economic Model”, Proc. of IEEE/ACM
Int. Symp. on Cluster, Cloud and Grid Computing, (2012).
[10] M. Mihailescu and Y. M. Teo, “Dynamic Resource Pricing
on Federated Clouds”, Proc. 10th IEEE/ACM Int. Symp. on
Cluster. Cloud and Grid Computing, (2010).
[11] Windows Azure, http://www.windowsazure.com/en-us/.
[12] H. Li, J. Liu and G. Tang, “A Pricing Algorithm for Cloud
Computing Resources”, Proc. Int. Conference on Network
Computing and Inform. Security, (2011).
[13] J. Rohitratana and J. Altmann, “Agent-Based Simulations
of the Software Market under Different Pricing Schemes for
Software-as-a-Service and Perpetual Software”, Economics
of Grids, Clouds, Systems, and Services, ser. Lecture Notes
in Computer Science, Altmann et al., Eds. Springer
Berlin/Heidelberg, pp. 6296. (2010).
[14] A. Monaco, “A View inside the Cloud”,
http://theinstitute.ieee.org/technology-focus/technology-
topic/a-view-inside-the-cloud.
[15] S. Dutta, M. Zbaracki and M. Bergen, “Pricing Process as a
Capability: A Resource-Based Perspective”, Strategic
Management Journal, vol. 27, no. 7, (2003).
[16] M. Macias and J. Guitart, “A Genetic Model for Pricing in
Cloud Computing Markets”, Proc. 26th Symp. of Applied
Computing, (2011).
[17] W. Wang, P. Zhang, T. Lan and V. Aggarwal, “Datacenter
Net Profit Optimization with Individual Job Deadlines”,
Proc. Conference on Inform. Sciences and Systems, (2012).
[18] S. Lehmann and P. Buxmann, “Pricing Strategies of
Software Vendors”, Business and Information Systems
Engineering, (2009).
[19] P. Nähring, “Value-Based Pricing”, Bachelor Thesis,
Linnaeus University, (2011).
[20] M. Mihailescu and Y. M. Teo, “On economic and
computational-efficient resource pricing in large distributed
systems,” in Cluster, Cloud and Grid Computing (CCGrid),
2010 10th IEEE/ACM International Conference on, may
2010, pp. 838 –843.
[21] Samimi, P.; Patel, A.; , "Review of pricing models for grid
& cloud computing," Computers & Informatics (ISCI),
2011 IEEE Symposium on , vol., no., pp.634-639, 20-23
(March 2011).
6. AUTHRORS BIOGRAPHIES
Taj Eldin Suliman M. Ali: B.Sc. in Computer science at Sudan
University (SUST), and M.Sc.in Computer science at Khartoum
University. From 2009 to 2015 he was work as a lecturer and
academic coordinator, College of Computer Studies at National
Ribat University, now he is a lecturer. From 2010 to 2015 he was
work as a lecturer and academic coordinator, College of Computing
and Health informatics at National University – SUDAN, now he
is a lecturer. During 2006 to 2008 he was work as a lecturer at
Bayan Collage, 2008 to 2009 he was work as Dean of IT
department at Bayan Collage. From 2002 to 2005 he was work as
TA at Bayan Collage and also works as a programmer. Currently,
he is a Ph.D. student at Sudan University of Science and
Technology, College of Computer Science and Information
Technology (SUST), my research interests in Pricing models and
Cloud Computing.
Hany H. Ammar BSEE, BS Physics, MSEE and Ph.D. EE, is a
Professor of Computer Engineering in the Lane Computer Science
and Electrical Engineering department at West Virginia University.
He has published over 170 articles in prestigious international
journals and conference proceedings. He is currently the Editor in
Chief of the Communications of the Arab Computer Society On-
Line Magazine. He is serving and has served as the Lead Principal
Investigator in the projects funded by the Qatar National Research
Fund under the National Priorities Research Program. In 2010, he
was awarded a Fulbright Specialist Scholar Award in Information
Technology funded by the US State Department - Bureau of
6. International Journal of Computer Applications Technology and Research
Volume 5– Issue 3, 126 - 131, 2016, ISSN:- 2319–8656
www.ijcat.com 131
Education and Cultural Affairs. He has been the Principal
Investigator on a number of research projects on Software Risk
Assessment and Software Architecture Metrics funded by NASA
and NSF, and projects on Automated Identification Systems funded
by NIJ and NSF. He has been teaching in the areas of Software
Engineering and Computer Architecture since 1987.In 2004, he co-
authored a book entitled Pattern-Oriented Analysis and Design:
Composing Patterns to Design Software Systems, Addison-
Wesley. In 2006, he co-authored a book entitled Software
Engineering: Technical, Organizational and Economic Aspects, an
Arabic Textbook.