In distributed computing, Cloud computing facilitates pay per model as per user demand and requirement.
Collection of virtual machines including both computational and storage resources will form the Cloud. In
Cloud computing, the main objective is to provide efficient access to remote and geographically distributed
resources. Cloud faces many challenges, one of them is scheduling/allocation problem. Scheduling refers to a
set of policies to control the order of work to be performed by a computer system. A good scheduler adapts its
allocation strategy according to the changing environment and the type of task. In this paper we will see FCFS,
Round Robin scheduling in addition to Linear Integer Programming an approach of resource allocation.
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.
Hybrid Based Resource Provisioning in CloudEditor IJCATR
The data centres and energy consumption characteristics of the various machines are often noted with different capacities.
The public cloud workloads of different priorities and performance requirements of various applications when analysed we had noted
some invariant reports about cloud. The Cloud data centres become capable of sensing an opportunity to present a different program.
In out proposed work, we are using a hybrid method for resource provisioning in data centres. This method is used to allocate the
resources at the working conditions and also for the energy stored in the power consumptions. Proposed method is used to allocate the
process behind the cloud storage.
ABSTRACT
Cloud computing utilizes large scale computing infrastructure that has been radically changing the IT landscape enabling remote access to computing resources with low service cost, high scalability , availability and accessibility. Serving tasks from multiple users where the tasks are of different characteristics with variation in the requirement of computing power may cause under or over utilization of resources.Therefore maintaining such mega-scale datacenter requires efficient resource management procedure to increase resource utilization. However, while maintaining efficiency in service provisioning it is necessary to ensure the maximization of profit for the cloud providers. Most of the current research works aims at how providers can offer efficient service provisioning to the user and improving system performance. There are comparatively fewer specific works regarding resource management which also deals with the economic section that considers profit maximization for the provider. In this paper we represent a model that deals with both efficient resource utilization and pricing of the resources. The joint resource management model combines the work of user assignment, task scheduling and load balancing on the fact of CPU power endorsement. We propose four algorithms respectively for user assignment, task scheduling, load balancing and pricing that works on group based resources offering reduction in task execution time(56.3%),activated physical machines(41.44%),provisioning cost(23%) . The cost is calculated over a time interval involving the number of served customer at this time and the amount of resources used within this time
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.
Survey on Dynamic Resource Allocation Strategy in Cloud Computing EnvironmentEditor IJCATR
Cloud computing becomes quite popular among cloud users by offering a variety of resources. This is an on demand service because it offers dynamic flexible resource allocation and guaranteed services in pay as-you-use manner to public. In this paper, we present the several dynamic resource allocation techniques and its performance. This paper provides detailed description of the dynamic resource allocation technique in cloud for cloud users and comparative study provides the clear detail about the different techniques
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
An Efficient Cloud Scheduling Algorithm for the Conservation of Energy throug...IJECEIAES
Method of broadcasting is the well known operation that is used for providing support to different computing protocols in cloud computing. Attaining energy efficiency is one of the prominent challenges, that is quite significant in the scheduling process that is used in cloud computing as, there are fixed limits that have to be met by the system. In this research paper, we are particularly focusing on the cloud server maintenance and scheduling process and to do so, we are using the interactive broadcasting energy efficient computing technique along with the cloud computing server. Additionally, the remote host machines used for cloud services are dissipating more power and with that they are consuming more and more energy. The effect of the power consumption is one of the main factors for determining the cost of the computing resources. With the idea of using the avoidance technology for assigning the data center resources that dynamically depend on the application demands and supports the cloud computing with the optimization of the servers in use.
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.
Hybrid Based Resource Provisioning in CloudEditor IJCATR
The data centres and energy consumption characteristics of the various machines are often noted with different capacities.
The public cloud workloads of different priorities and performance requirements of various applications when analysed we had noted
some invariant reports about cloud. The Cloud data centres become capable of sensing an opportunity to present a different program.
In out proposed work, we are using a hybrid method for resource provisioning in data centres. This method is used to allocate the
resources at the working conditions and also for the energy stored in the power consumptions. Proposed method is used to allocate the
process behind the cloud storage.
ABSTRACT
Cloud computing utilizes large scale computing infrastructure that has been radically changing the IT landscape enabling remote access to computing resources with low service cost, high scalability , availability and accessibility. Serving tasks from multiple users where the tasks are of different characteristics with variation in the requirement of computing power may cause under or over utilization of resources.Therefore maintaining such mega-scale datacenter requires efficient resource management procedure to increase resource utilization. However, while maintaining efficiency in service provisioning it is necessary to ensure the maximization of profit for the cloud providers. Most of the current research works aims at how providers can offer efficient service provisioning to the user and improving system performance. There are comparatively fewer specific works regarding resource management which also deals with the economic section that considers profit maximization for the provider. In this paper we represent a model that deals with both efficient resource utilization and pricing of the resources. The joint resource management model combines the work of user assignment, task scheduling and load balancing on the fact of CPU power endorsement. We propose four algorithms respectively for user assignment, task scheduling, load balancing and pricing that works on group based resources offering reduction in task execution time(56.3%),activated physical machines(41.44%),provisioning cost(23%) . The cost is calculated over a time interval involving the number of served customer at this time and the amount of resources used within this time
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.
Survey on Dynamic Resource Allocation Strategy in Cloud Computing EnvironmentEditor IJCATR
Cloud computing becomes quite popular among cloud users by offering a variety of resources. This is an on demand service because it offers dynamic flexible resource allocation and guaranteed services in pay as-you-use manner to public. In this paper, we present the several dynamic resource allocation techniques and its performance. This paper provides detailed description of the dynamic resource allocation technique in cloud for cloud users and comparative study provides the clear detail about the different techniques
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
An Efficient Cloud Scheduling Algorithm for the Conservation of Energy throug...IJECEIAES
Method of broadcasting is the well known operation that is used for providing support to different computing protocols in cloud computing. Attaining energy efficiency is one of the prominent challenges, that is quite significant in the scheduling process that is used in cloud computing as, there are fixed limits that have to be met by the system. In this research paper, we are particularly focusing on the cloud server maintenance and scheduling process and to do so, we are using the interactive broadcasting energy efficient computing technique along with the cloud computing server. Additionally, the remote host machines used for cloud services are dissipating more power and with that they are consuming more and more energy. The effect of the power consumption is one of the main factors for determining the cost of the computing resources. With the idea of using the avoidance technology for assigning the data center resources that dynamically depend on the application demands and supports the cloud computing with the optimization of the servers in use.
Dynamic resource allocation using virtual machines for cloud computing enviro...IEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
A survey of various scheduling algorithm 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 is an emerging technology. It process huge amount of data so scheduling mechanism
works as a vital role in the cloud computing. Thus my protocol is designed to minimize the switching time,
improve the resource utilization and also improve the server performance and throughput. This method or
protocol is based on scheduling the jobs in the cloud and to solve the drawbacks in the existing protocols.
Here we assign the priority to the job which gives better performance to the computer and try my best to
minimize the waiting time and switching time. Best effort has been made to manage the scheduling of jobs
for solving drawbacks of existing protocols and also improvise the efficiency and throughput of the server.
Linked List Implementation of Discount Pricing in Cloudpaperpublications3
Abstract: In the cloud computing environment computational resources are readily and elastically available to the customers. In order to attract customers with various demands, most Infrastructure-as-a-service (IaaS) cloud service providers offer several pricing strategies such as pay as you go, pay less per unit when you use more (so called volume discount), and pay even less when you reserve. In order to enjoy these discounts, the customers must be ready to adjust the time limits. By strategically scheduling multiple customers’ resource request, a cloud broker takes the responsibility of distributing the discounts offered by cloud service providers. Here the focus is on how a broker can help a group of customers to fully utilize the volume discount pricing strategy offered by cloud service providers through cost-efficient online resource scheduling. A randomized online stack-centric scheduling algorithm (ROSA) is implemented with linked list in order to maintain the status of the resource and to allocate resources without time constrains.
Management of context aware software resources deployed in a cloud environmen...ijdpsjournal
In cloud computing environments, context information is continuously created by context providers and
consumed by the applications on mobile devices. An important characteristic of cloud-based context aware
services is meeting the service level agreements (SLAs) to deliver a certain quality of service (Qos), such as
guarantees on response time or price. The response time to a request of context-aware software is affected
by loading extensive context data from multiple resources on the chosen server. Therefore, the speed of
such software would be decreased during execution time. Hence, proper scheduling of such services is
indispensable because the customers are faced with time constraints. In this research, a new scheduling
algorithm for context aware services is proposed which is based on classifying similar context consumers
and dynamically scoring the requests to improve the performance of the server hosting highly-requested
context-aware software while reducing costs of cloud provider. The approach is evaluated via simulation
and comparison with gi-FIFO scheduling algorithm. Experimental results demonstrate the efficiency of the
proposed approach.
A REVIEW ON LOAD BALANCING IN CLOUD USING ENHANCED GENETIC ALGORITHM IAEME Publication
“Cloud computing” is a term, which involves virtualization, distributed
computing, networking, software and net services. A cloudconsists of several partssuch as shoppers, datacenter and distributed servers. It includes fault tolerance, high
availability, scalability, flexibility, reduced overhead for users, reduced cost of
possession, on demand services etc. Central to these issues lies the institution of a
good load reconciliation algorithmic rule. The load can be CPU load, memory
capacity, delay or network load. Load balancing is the method of distributing the load
among varied nodes of a distributed system to boost each resource utilization and job
interval whereas additionally avoiding a state of affairs wherever a number of the
nodes area unit heavily loaded whereas different nodes area unit idle or doing little
work. Load balancing ensures that all the processors within the system or each node
within the network will require the equal quantity of labor at any instant of your time.
This technique will be sender initiated, receiver initiated or symmetric sort
(combination of sender initiated and receiver initiated types). Our objective is to
develop an effective load reconciliation algorithmic rule mistreatment divisible load
programming theorem to maximize or minimize completely different performance
parameters (throughput, latency for example) for the clouds of different sizes (virtualtopology de-pending on the appliance requirement).
Extending Grids with Cloud Resource Management for Scientific ComputingBharat Kalia
Grid computing gained high popularity in the field of scientific computing through the idea of distributed resource sharing among institutions and scientists. Scientific computing is traditionally a high-utilization workload, with production Grids often running at over 80% utilization (generating high and often unpredictable latencies), and with smaller national Grids offering a rather limited amount of high-performance resources. Running large-scale simulations in such overloaded Grid environments often becomes latency bound or suffers from well-known Grid reliability problems. Today, a new research direction coined by the term Cloud computing proposes an alternative attractive to scientific computing scientists primarily because of four main advantages.
Adaptive Offloading in Mobile Cloud Computing by automatic partitioning approach of tasks is the idea to augment execution through migrating heavy computation from mobile devices to resourceful cloud servers and then receive the results from them via wireless networks. Offloading is an effective way to
overcome the resources and functionalities constraints
of the mobile devices since it can release them from
intensive processing and increase performance of the
mobile applications, in terms of response time.
Offloading brings many potential benefits, such as
energy saving, performance improvement, reliability
improvement, ease for the software developers and
better exploitation of contextual information.
Parameters about method transitions, response times,
cost and energy consumptions are dynamically reestimated
at runtime during application executions.
An Efficient Queuing Model for Resource Sharing in Cloud Computingtheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
An efficient resource sharing technique for multi-tenant databases IJECEIAES
Multi-tenancy is a key component of Software as a Service (SaaS) paradigm. Multi-tenant software has gained a lot of attention in academics, research and business arena. They provide scalability and economic benefits for both cloud service providers and tenants by sharing same resources and infrastructure in isolation of shared databases, network and computing resources with Service level agreement (SLA) compliances. In a multitenant scenario, active tenants compete for resources in order to access the database. If one tenant blocks up the resources, the performance of all the other tenants may be restricted and a fair sharing of the resources may be compromised. The performance of tenants must not be affected by resource-intensive activities and volatile workloads of other tenants. Moreover, the prime goal of providers is to accomplish low cost of operation, satisfying specific schemas/SLAs of each tenant. Consequently, there is a need to design and develop effective and dynamic resource sharing algorithms which can handle above mentioned issues. This work presents a model referred as MultiTenant Dynamic Resource Scheduling Model (MTDRSM) embracing a query classification and worker sorting technique enabling efficient and dynamic resource sharing among tenants. The experiments show significant performance improvement over existing model.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Special Elements of a Ternary SemiringIJERA Editor
In this paper we study the notion of some special elements such as identity, zero, absorbing, additive
idempotent, idempotent, multiplicatively sub-idempotent, regular, Intra regular, completely regular, g–regular,
invertible and the ternary semirings such as zero sum free ternary semiring, zero ternary semiring, zero divisor
free ternary semiring, ternary semi-integral domain, semi-subtractive ternary semiring, multiplicative
cancellative ternary semiring, Viterbi ternary semiring, regular ternary semiring, completely ternary semiring
and characterize these ternary semirings.
Mathematics Subject Classification : 16Y30, 16Y99.
Utilizing Symbolic Programming in Analog Circuit Synthesis of Arbitrary Ratio...IJERA Editor
The employment of symbolic programming in analog circuit design for system interfaces is proposed. Given a
rational transfer function with a set of specifications and constraints, one may autonomously synthesize it into an
analog circuit. First, a classification of the target transfer function polynomials into 14 classes is performed. The
classes include both stable and unstable functions as required. A symbolic exhaustive search algorithm based on
a circuit configuration under investigation is then conducted where a polynomial in hand is to be identified. For
illustration purposes, a set of complete design equations for the primary rational transfer functions is obtained
targeting all classes of second order polynomials based on a proposed general circuit configuration. The design
consists of a single active element and four different circuit structures. Finally, an illustrative example with full
analysis and simulation is presented.
Bibliography, Background and Overview of UWB radar sensorIJERA Editor
Due to the lack of studies in the literature that address the issue of UWB radar sensors, and also because of the
great importance of this technology, which is gaining heavily in new application areas, such as the process
industry and automotive engineering. A brief summary of the biography of UWB radar sensors have been treated
and presented in this article, specifying the difference between pulsed radar sensors regarding CW radar sensor,
and two subcategories SFCW FMCW, and highlight the benefits of each.
Design and Optimization of Valveless Pulsejet EngineIJERA Editor
Simple design and efficiency make pulsejet engines attractive for aeronautical short-term operation applications.
An active control system extends the operating range and reduces the fuel consumption considerably so that this
old technology might gain a new interest. During the operations of these pulsejet engines the surfaces of engine
will get more heated. In order to cool the engine surface and to get more thrust we have attached an additional
component called secondary inlet in that valve less pulsejet engine. The pulsejet is the only jet engine combustor
that shows a net pressure gain between the intake and the exhaust. The pulsejet is the only jet engine combustor
that shows a net pressure gain between the intake and the exhaust. We choose the LOCKWOOD’s design of
pulsejet engine. By using the CFD analysis we have analysed the modified design of valveless pulsejet engine.
This project provides an overview of this unique process and the results of these design modifications are
reported.
Dynamic resource allocation using virtual machines for cloud computing enviro...IEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
A survey of various scheduling algorithm 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 is an emerging technology. It process huge amount of data so scheduling mechanism
works as a vital role in the cloud computing. Thus my protocol is designed to minimize the switching time,
improve the resource utilization and also improve the server performance and throughput. This method or
protocol is based on scheduling the jobs in the cloud and to solve the drawbacks in the existing protocols.
Here we assign the priority to the job which gives better performance to the computer and try my best to
minimize the waiting time and switching time. Best effort has been made to manage the scheduling of jobs
for solving drawbacks of existing protocols and also improvise the efficiency and throughput of the server.
Linked List Implementation of Discount Pricing in Cloudpaperpublications3
Abstract: In the cloud computing environment computational resources are readily and elastically available to the customers. In order to attract customers with various demands, most Infrastructure-as-a-service (IaaS) cloud service providers offer several pricing strategies such as pay as you go, pay less per unit when you use more (so called volume discount), and pay even less when you reserve. In order to enjoy these discounts, the customers must be ready to adjust the time limits. By strategically scheduling multiple customers’ resource request, a cloud broker takes the responsibility of distributing the discounts offered by cloud service providers. Here the focus is on how a broker can help a group of customers to fully utilize the volume discount pricing strategy offered by cloud service providers through cost-efficient online resource scheduling. A randomized online stack-centric scheduling algorithm (ROSA) is implemented with linked list in order to maintain the status of the resource and to allocate resources without time constrains.
Management of context aware software resources deployed in a cloud environmen...ijdpsjournal
In cloud computing environments, context information is continuously created by context providers and
consumed by the applications on mobile devices. An important characteristic of cloud-based context aware
services is meeting the service level agreements (SLAs) to deliver a certain quality of service (Qos), such as
guarantees on response time or price. The response time to a request of context-aware software is affected
by loading extensive context data from multiple resources on the chosen server. Therefore, the speed of
such software would be decreased during execution time. Hence, proper scheduling of such services is
indispensable because the customers are faced with time constraints. In this research, a new scheduling
algorithm for context aware services is proposed which is based on classifying similar context consumers
and dynamically scoring the requests to improve the performance of the server hosting highly-requested
context-aware software while reducing costs of cloud provider. The approach is evaluated via simulation
and comparison with gi-FIFO scheduling algorithm. Experimental results demonstrate the efficiency of the
proposed approach.
A REVIEW ON LOAD BALANCING IN CLOUD USING ENHANCED GENETIC ALGORITHM IAEME Publication
“Cloud computing” is a term, which involves virtualization, distributed
computing, networking, software and net services. A cloudconsists of several partssuch as shoppers, datacenter and distributed servers. It includes fault tolerance, high
availability, scalability, flexibility, reduced overhead for users, reduced cost of
possession, on demand services etc. Central to these issues lies the institution of a
good load reconciliation algorithmic rule. The load can be CPU load, memory
capacity, delay or network load. Load balancing is the method of distributing the load
among varied nodes of a distributed system to boost each resource utilization and job
interval whereas additionally avoiding a state of affairs wherever a number of the
nodes area unit heavily loaded whereas different nodes area unit idle or doing little
work. Load balancing ensures that all the processors within the system or each node
within the network will require the equal quantity of labor at any instant of your time.
This technique will be sender initiated, receiver initiated or symmetric sort
(combination of sender initiated and receiver initiated types). Our objective is to
develop an effective load reconciliation algorithmic rule mistreatment divisible load
programming theorem to maximize or minimize completely different performance
parameters (throughput, latency for example) for the clouds of different sizes (virtualtopology de-pending on the appliance requirement).
Extending Grids with Cloud Resource Management for Scientific ComputingBharat Kalia
Grid computing gained high popularity in the field of scientific computing through the idea of distributed resource sharing among institutions and scientists. Scientific computing is traditionally a high-utilization workload, with production Grids often running at over 80% utilization (generating high and often unpredictable latencies), and with smaller national Grids offering a rather limited amount of high-performance resources. Running large-scale simulations in such overloaded Grid environments often becomes latency bound or suffers from well-known Grid reliability problems. Today, a new research direction coined by the term Cloud computing proposes an alternative attractive to scientific computing scientists primarily because of four main advantages.
Adaptive Offloading in Mobile Cloud Computing by automatic partitioning approach of tasks is the idea to augment execution through migrating heavy computation from mobile devices to resourceful cloud servers and then receive the results from them via wireless networks. Offloading is an effective way to
overcome the resources and functionalities constraints
of the mobile devices since it can release them from
intensive processing and increase performance of the
mobile applications, in terms of response time.
Offloading brings many potential benefits, such as
energy saving, performance improvement, reliability
improvement, ease for the software developers and
better exploitation of contextual information.
Parameters about method transitions, response times,
cost and energy consumptions are dynamically reestimated
at runtime during application executions.
An Efficient Queuing Model for Resource Sharing in Cloud Computingtheijes
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
An efficient resource sharing technique for multi-tenant databases IJECEIAES
Multi-tenancy is a key component of Software as a Service (SaaS) paradigm. Multi-tenant software has gained a lot of attention in academics, research and business arena. They provide scalability and economic benefits for both cloud service providers and tenants by sharing same resources and infrastructure in isolation of shared databases, network and computing resources with Service level agreement (SLA) compliances. In a multitenant scenario, active tenants compete for resources in order to access the database. If one tenant blocks up the resources, the performance of all the other tenants may be restricted and a fair sharing of the resources may be compromised. The performance of tenants must not be affected by resource-intensive activities and volatile workloads of other tenants. Moreover, the prime goal of providers is to accomplish low cost of operation, satisfying specific schemas/SLAs of each tenant. Consequently, there is a need to design and develop effective and dynamic resource sharing algorithms which can handle above mentioned issues. This work presents a model referred as MultiTenant Dynamic Resource Scheduling Model (MTDRSM) embracing a query classification and worker sorting technique enabling efficient and dynamic resource sharing among tenants. The experiments show significant performance improvement over existing model.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Special Elements of a Ternary SemiringIJERA Editor
In this paper we study the notion of some special elements such as identity, zero, absorbing, additive
idempotent, idempotent, multiplicatively sub-idempotent, regular, Intra regular, completely regular, g–regular,
invertible and the ternary semirings such as zero sum free ternary semiring, zero ternary semiring, zero divisor
free ternary semiring, ternary semi-integral domain, semi-subtractive ternary semiring, multiplicative
cancellative ternary semiring, Viterbi ternary semiring, regular ternary semiring, completely ternary semiring
and characterize these ternary semirings.
Mathematics Subject Classification : 16Y30, 16Y99.
Utilizing Symbolic Programming in Analog Circuit Synthesis of Arbitrary Ratio...IJERA Editor
The employment of symbolic programming in analog circuit design for system interfaces is proposed. Given a
rational transfer function with a set of specifications and constraints, one may autonomously synthesize it into an
analog circuit. First, a classification of the target transfer function polynomials into 14 classes is performed. The
classes include both stable and unstable functions as required. A symbolic exhaustive search algorithm based on
a circuit configuration under investigation is then conducted where a polynomial in hand is to be identified. For
illustration purposes, a set of complete design equations for the primary rational transfer functions is obtained
targeting all classes of second order polynomials based on a proposed general circuit configuration. The design
consists of a single active element and four different circuit structures. Finally, an illustrative example with full
analysis and simulation is presented.
Bibliography, Background and Overview of UWB radar sensorIJERA Editor
Due to the lack of studies in the literature that address the issue of UWB radar sensors, and also because of the
great importance of this technology, which is gaining heavily in new application areas, such as the process
industry and automotive engineering. A brief summary of the biography of UWB radar sensors have been treated
and presented in this article, specifying the difference between pulsed radar sensors regarding CW radar sensor,
and two subcategories SFCW FMCW, and highlight the benefits of each.
Design and Optimization of Valveless Pulsejet EngineIJERA Editor
Simple design and efficiency make pulsejet engines attractive for aeronautical short-term operation applications.
An active control system extends the operating range and reduces the fuel consumption considerably so that this
old technology might gain a new interest. During the operations of these pulsejet engines the surfaces of engine
will get more heated. In order to cool the engine surface and to get more thrust we have attached an additional
component called secondary inlet in that valve less pulsejet engine. The pulsejet is the only jet engine combustor
that shows a net pressure gain between the intake and the exhaust. The pulsejet is the only jet engine combustor
that shows a net pressure gain between the intake and the exhaust. We choose the LOCKWOOD’s design of
pulsejet engine. By using the CFD analysis we have analysed the modified design of valveless pulsejet engine.
This project provides an overview of this unique process and the results of these design modifications are
reported.
Finite Element Simulation for Determining the Optimum Blank Shape for Deep Dr...IJERA Editor
Deep drawing is one of widely used sheet metal working process in industries to produce cup shaped
components at a very high rate. The present study aims to determine the optimum shape of blank for deep
drawing of cylindrical cup without ears. Earing is one of the major defects observed during deep drawing
process due to anisotropic nature of sheet metal. Earing is defined as formation of waviness on uppermost
portion of deep drawn cup. Earing defect occurs due to non-uniform material properties within plane of sheet
(i.e. planar anisotropy). Knowledge about ear formation in deep drawing process allows a prior modification of
process which can result in defect free final product with financial saving and time. In the present study efforts
have been made to study the earing problem in deep drawing of cylindrical cups by finite element modeling
software HYPERWORK-6.12. The blank material as EN10130Fe01 mild steel sheet of 1mm thickness has been
considered as it has wide application a fabricating critical automobile parts. Mechanical parameters of mild steel
are incorporated in finite element simulation of deep drawing process. Significant earing was observed at rolling
and transverse direction on deformed cup form circular blank. Modification of initial blank is done to find the
optimum blank to reduce the earing defect. Optimal blank shows significant reduction of % earing height,
reduction in drawing load & improvement in maximum thickness variations.
Road Safety Audit: A Case Study for Wardha Road in Nagpur CityIJERA Editor
India has a road network of an estimated 3.3 million km, which carries nearly 65 per cent of freight and 85 per
cent of passenger traffic. The road traffic is estimated to be growing at an annual rate of 7-10 per cent, while the
vehicle population is growing at a rate of 12 per cent per year.
A Road Safety Audit (RSA) qualitatively estimates and reports on potential road safety issues and identifies
opportunities for improvements in safety for all road users. The Road Safety Audit consists of safety principles
to the design of a new or a rehabilitated road section, to prevent frequent occurrence of accidents or to reduce
their severity.
In this project analysis of one of the major arterial street of Nagpur city will be undertaken. The location of
interest for the analysis is Wardha Road from Morris College Square to Airport Intersection. The roadway
carries considerable amount of traffic throughout the day and it has number of conflict points such as merging of
traffic from flyover. A detailed analysis of Wardha Road will be carried out from the point of view of safety and
supplemental analysis regarding the traffic growth and accident analysis will also be performed.
The project aims to identify deficiencies, developing mitigating strategies, improving public
relations,enhancing credibility of the roads and calculating the crash rate of intersection or length of roads.
Graphical Password by Watermarking for securityIJERA Editor
The most common authentication method is to use alphanumerical usernames and passwords. This method has
been shown to have considerable disadvantage. For example, users tend to pick passwords that can be easily
guessed. On the other hand, if a password is very difficult to guess, then it is often difficult to remember. To
address this problem, some researchers have developed authentication methods that use pictures as passwords.
Graphical Password based on the fact that humans tend to remember images better. In this paper, we will
propose a new algorithm that using watermarking technique as the solution to solving image gallery attacks and
using the random character set generation for each image for resistance to shoulder surfing attack to provide
better system security. All the information images in registration phase will be process by copy right protection
of watermarking where the login page will check this information for security purposes.
Thermal Stress Analysis of a Speculative IC Engine Piston using CAE ToolsIJERA Editor
This paper deals with the pressure due to expanding combustion gases in the combustion chamber space at the
top of the cylinder which generate thermal stresses due to presence of heat involved on the reciprocating masses.
The present work deals with the use of different materials for IC engine piston and a comparative study is made
to achieve the best possible result. Piston parameters are taken using the conventional formulas and are constant
throughout the analysis. Moreover the boundary conditions are chosen such that the piston does not moves
sideways except in the direction of line of action of the piston itself.
A typical Realization of the process with linear recovery of AldosteroneIJERA Editor
Hypercortisolism as a sign of hypothamamus-pituitary-adrenocortical (HPA) axis overactivity and sleep EEG
changes are frequently observed in depression. Closely related to the
HPA axis is the renin-angiotensin-aldosterone system (RAAS) as 1. adrenocorticotropic hormone (ACTH) is a
common stimulus for cortisol and aldosterone, 2. cortisol release is suppressed by mineralocorticoid receptor
(MR) agonists 3. angiotensin II (ATII) releases CRH and vasopressin from the hypothalamus. The first passage
time and the bounds of the survival functions for the application are also obtained
Complexity of pilgering in nuclear applicationsIJERA Editor
Nuclear reactors use various types and sections of tubes manufactured with exotic materials meeting special
requirements. These Tubes are manufactured using a Cold working process of Pilgering. Pilgering process is
influenced by a lot of factors making it a highly complex process. In this paper the various influencing factors
are compiled, segregated and briefly discussed.
Cateva reguli de urmat pentru ingrijirea tenului in perioadele reci de iarna, pentru mentinerea tenului tanar si elastic, pentru prevenirea aparitiei acneei, ridurilor si a eczemelor. Sfaturi antiimbatranire
Michaelis-Menten Kinetics in Transient State: Proposal for Reversible Inhibit...IJERA Editor
The enzymatic processes according Michaelis-Menten kinetics have been studied from various approaches to
describe the inhibition state. Proposals for inhibition were compared from a generic process, where kinetic
constants have received unitary values, and the numeric value of the concentration of substrate was ten (10)
times higher than the numerical value of the concentration of enzyme. For each inhibition model proposed,
numerical solutions were obtained from nonlinear system of ordinary differential equations, generating results
presents by graphs showing the variation of the enzyme and enzyme complexes, also the variation of substrate
and product of the reaction. Also, was designed a model with performance, indicating similar behavior to that
seen in the Michaelis-Menten kinetics, where complex of reaction is rapidly formed and throughout the process,
tends to decay to zero. Thus, in this new proposed model, the effect of inhibition starts at zero and, throughout
the process, tends to the nominal value of the initial enzyme concentration. Such responses have proved to be
valid for different values of enzyme concentration and process time, showing robustness. The proposed model
was applied to the hydrolysis of disaccharides, providing a setting with conservation of mass of the model at the
end of the process regarding the responses of the carbohydrate concentration.
A survey on various resource allocation policies in cloud computing environmenteSAT Journals
Abstract Cloud computing is bringing a revolution in computing environment replacing traditional software installations, licensing issues into complete on-demand services through internet. In Cloud computing multiple cloud users can request number of cloud services simultaneously. So there must be a provision that all resources are made available to requesting user in efficient manner to satisfy their need. Resource allocation is based on quality of service and service level agreement. In cloud computing environment, to allocate resources to the user there are several methods but provider should consider the efficient way to guarantee that the applications’ requirements are attended to correctly and satisfy the user’s need This paper survey different resource allocation policies used in cloud computing environment. Keywords: Cloud computing, Resource allocation
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.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Efficient Resource Sharing In Cloud Using Neural NetworkIJERA Editor
In cloud computing, collaborative cloud computing(CCC) is the emerging technology where globally-dispersed cloud resource belonging to different organization are collectively used in a cooperative manner to provide services. In previous research, Harmony enables a node to locate its desired resources and also find the reputation of the located resources, so that a client can choose resource providers not only by resource availability but also by the provider’s reputation of providing the resource. In proposed system to reform resource utilization based on optimal time period to allocate resources to the neural network training and to load factor calculation the dynamic priority scheduling technique is used to assign the priority to the cloud users according to their load. The dynamic priority scheduling algorithm strikes the right balance between performance and power efficiency.
GROUP BASED RESOURCE MANAGEMENT AND PRICING MODEL IN CLOUD COMPUTINGijcsit
Cloud computing utilizes large scale computing infrastructure that has been radically changing the IT landscape enabling remote access to computing resources with low service cost, high scalability , availability and accessibility. Serving tasks from multiple users where the tasks are of different characteristics with variation in the requirement of computing power may cause under or over utilization of resources.Therefore maintaining such mega-scale datacenter requires efficient resource management procedure to increase resource utilization. However, while maintaining efficiency in service provisioning it is necessary to ensure the maximization of profit for the cloud providers. Most of the current research works aims at how providers can offer efficient service provisioning to the user and improving system performance. There are comparatively fewer specific works regarding resource management which also deals with the economic section that considers profit maximization for the provider. In this paper we represent a model that deals with both efficient resource utilization and pricing of the resources. The joint resource management model combines the work of user assignment, task scheduling and load balancing on the fact of CPU power endorsement. We propose four algorithms respectively for user assignment, task scheduling, load balancing and pricing that works on group based resources offering reduction in task execution time(56.3%),activated physical machines(41.44%),provisioning cost(23%) . The cost is calculated over a time interval involving the number of served customer at this time and the amount of resources used within this time.
Prediction Based Efficient Resource Provisioning and Its Impact on QoS Parame...IJECEIAES
The purpose of this paper is to provision the on demand resources to the end users as per their need using prediction method in cloud computing environment. The provisioning of virtualized resources to cloud consumers according to their need is a crucial step in the deployment of applications on the cloud. However, the dynamical management of resources for variable workloads remains a challenging problem for cloud providers. This problem can be solved by using a prediction based adaptive resource provisioning mechanism, which can estimate the upcoming resource demands of applications. The present research introduces a prediction based resource provisioning model for the allocation of resources in advance. The proposed approach facilitates the release of unused resources in the pool with quality of service (QoS), which is defined based on prediction model to perform the allocation of resources in advance. In this work, the model is used to determine the future workload prediction for user requests on web servers, and its impact toward achieving efficient resource provisioning in terms of resource exploitation and QoS. The main contribution of this paper is to develop the prediction model for efficient and dynamic resource provisioning to meet the requirements of end users.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
The papers for publication in The International Journal of Engineering& Science are selected through rigorous peer reviews to ensure originality, timeliness, relevance, and readability.
A latency-aware max-min algorithm for resource allocation in cloud IJECEIAES
Cloud computing is an emerging distributed computing paradigm. However, it requires certain initiatives that need to be tailored for the cloud environment such as the provision of an on-the-fly mechanism for providing resource availability based on the rapidly changing demands of the customers. Although, resource allocation is an important problem and has been widely studied, there are certain criteria that need to be considered. These criteria include meeting user’s quality of service (QoS) requirements. High QoS can be guaranteed only if resources are allocated in an optimal manner. This paper proposes a latency-aware max-min algorithm (LAM) for allocation of resources in cloud infrastructures. The proposed algorithm was designed to address challenges associated with resource allocation such as variations in user demands and on-demand access to unlimited resources. It is capable of allocating resources in a cloud-based environment with the target of enhancing infrastructure-level performance and maximization of profits with the optimum allocation of resources. A priority value is also associated with each user, which is calculated by analytic hierarchy process (AHP). The results validate the superiority for LAM due to better performance in comparison to other state-of-the-art algorithms with flexibility in resource allocation for fluctuating resource demand patterns.
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
Challenges in Dynamic Resource Allocation and Task Scheduling in Heterogeneou...rahulmonikasharma
Resource Allocation and Task scheduling are the most important key words in today’s dynamic cloud based applications. Task scheduling involves assigning tasks to available processors with the aim of producing minimum execution time, whereas resource allocation involves deciding on an allocation policy to allocate resources to various tasks so as to have maximum resource utilization. Algorithms used for scheduling resources for virtual machines are designed for both homogeneous and heterogeneous environments. Majority of the algorithms focus on processing ability often neglecting other features such as network bandwidth and actual resource requirements. One of the major pitfalls in cloud computing is related to optimizing the resources being allocated. Because of the uniqueness of the model, resource allocation is performed with the objective of minimizing the costs associated with it. The other challenges of resource allocation are meeting customer demands and application requirements. In this paper we will focus on the challenges faced in task scheduling and resource allocation in dynamic heterogeneous clouds.
PROPOSED ONTOLOGY FRAMEWORK FOR DYNAMIC RESOURCE PROVISIONING ON PUBLIC CLOUDIAEME Publication
Cloud computing is an essential ingredient of today’s modern information technology. Cloud computing is totally based on internet. With the use of cloud computing resources can be shared from anywhere and anytime. In cloud computing there are multiple users simultaneously requests for the number of services and its important to provision all resources to user in efficient manner to satisfy their requirements. To come out this problem in this paper we had reviwed the different types of resource allocation strategies and proposed an ontology based resource management framwork for dynamic resource allocation. Ontology Framework contain four sections, each section equipped with functionality to collect information regarding all resources available in actual cloud deployment based on signed SLA agreement, and then replies to the user with appropriate allocation.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
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Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Hybrid optimization of pumped hydro system and solar- Engr. Abdul-Azeez.pdffxintegritypublishin
Advancements in technology unveil a myriad of electrical and electronic breakthroughs geared towards efficiently harnessing limited resources to meet human energy demands. The optimization of hybrid solar PV panels and pumped hydro energy supply systems plays a pivotal role in utilizing natural resources effectively. This initiative not only benefits humanity but also fosters environmental sustainability. The study investigated the design optimization of these hybrid systems, focusing on understanding solar radiation patterns, identifying geographical influences on solar radiation, formulating a mathematical model for system optimization, and determining the optimal configuration of PV panels and pumped hydro storage. Through a comparative analysis approach and eight weeks of data collection, the study addressed key research questions related to solar radiation patterns and optimal system design. The findings highlighted regions with heightened solar radiation levels, showcasing substantial potential for power generation and emphasizing the system's efficiency. Optimizing system design significantly boosted power generation, promoted renewable energy utilization, and enhanced energy storage capacity. The study underscored the benefits of optimizing hybrid solar PV panels and pumped hydro energy supply systems for sustainable energy usage. Optimizing the design of solar PV panels and pumped hydro energy supply systems as examined across diverse climatic conditions in a developing country, not only enhances power generation but also improves the integration of renewable energy sources and boosts energy storage capacities, particularly beneficial for less economically prosperous regions. Additionally, the study provides valuable insights for advancing energy research in economically viable areas. Recommendations included conducting site-specific assessments, utilizing advanced modeling tools, implementing regular maintenance protocols, and enhancing communication among system components.
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Event Management System Vb Net Project Report.pdfKamal Acharya
In present era, the scopes of information technology growing with a very fast .We do not see any are untouched from this industry. The scope of information technology has become wider includes: Business and industry. Household Business, Communication, Education, Entertainment, Science, Medicine, Engineering, Distance Learning, Weather Forecasting. Carrier Searching and so on.
My project named “Event Management System” is software that store and maintained all events coordinated in college. It also helpful to print related reports. My project will help to record the events coordinated by faculties with their Name, Event subject, date & details in an efficient & effective ways.
In my system we have to make a system by which a user can record all events coordinated by a particular faculty. In our proposed system some more featured are added which differs it from the existing system such as security.
Vaccine management system project report documentation..pdfKamal Acharya
The Division of Vaccine and Immunization is facing increasing difficulty monitoring vaccines and other commodities distribution once they have been distributed from the national stores. With the introduction of new vaccines, more challenges have been anticipated with this additions posing serious threat to the already over strained vaccine supply chain system in Kenya.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
Gen AI Study Jams _ For the GDSC Leads in India.pdf
Allocation Strategies of Virtual Resources in Cloud-Computing Networks
1. K.Delhi Babu Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 11(Version - 5), November 2014, pp.51-55
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Allocation Strategies of Virtual Resources in Cloud-Computing Networks 1K.Delhi Babu,2D.Giridhar Kumar Department of Computer Science and Engineering, SreeVidyanikethanEngg.College , Tirupati . Abstract— In distributed computing, Cloud computing facilitates pay per model as per user demand and requirement. Collection of virtual machines including both computational and storage resources will form the Cloud. In Cloud computing, the main objective is to provide efficient access to remote and geographically distributed resources. Cloud faces many challenges, one of them is scheduling/allocation problem. Scheduling refers to a set of policies to control the order of work to be performed by a computer system. A good scheduler adapts its allocation strategy according to the changing environment and the type of task. In this paper we will see FCFS, Round Robin scheduling in addition to Linear Integer Programming an approach of resource allocation. Index Terms--Cloud Computing, Virtual Machine, Resource Allocation, Linear Integer Programming
I. INRTODUCTION
Cloud computing can be seen as an innovation in different ways. From a technological perspective it is an advancement of computing, which’s history can be traced back to the construction of the calculating machine. While from a technical perspective, cloud computing seems to pose manageable challenges, it rather incorporates a number of challenges on a business level, both from an operational as well as from a strategic point of view. One fundamental advantage of the cloud paradigm is computation outsourcing, where the computational power of cloud customers is no longer limited by their resource-constraint devices. By outsourcing the workloads into the cloud, customers could enjoy the literally unlimited computing resources in a pay-per-use manner without committing any large capital outlays in the purchase of hardware and software and/or the operational overhead there in. It enables customers with limited computational resources to outsource their large computation workloads to the cloud, and economically enjoy the massive computational power, bandwidth, storage, and even appropriate software that can be shared in a pay-per-use manner.
The main cloud computing attributes are pay per use, elastic self provisioning through software, simple scalable services, virtualized physical resources. Models, such as cloud computing based on Virtual technologies enables the user to access storage resources and charge according to the resources access. Cloud computing platforms are based on utility model that enhances the reliability, scalability, performance and need based configurability and all these capabilities are provided at relatively low costs as compared to the dedicated infrastructures. This new model of infrastructure sharing is being widely adopted by the industries. Industries experts predict that cloud Computing has right future in spite of changing technology that faces significant challenge. Cloud computing is a complex distributed environment and it relies heavily on strong algorithms for allocating properly CPU, RAM and hard disk operations to end users and core processes in a mutual and shared system. Here comes the matter of resource accounting and there are two distinct alternatives. The first one is strictly usage- oriented where you have a limited number of units. Such units can be connected to CPU and/or Memory usage, time or they can be a compound indicator. This covers generally the idea of utility computing. As a whole it gives some flexibility but it is more expensive in the long term. The second alternative is capacity pre-allocation. In this case there are different plans with predefined constant resources dedicated CPU and Memory. This still gives flexibility to upgrade resources on demand but it also allows lower price for higher resource usage in the long term.
When talking about a cloud computing system, it's helpful to divide it into two sections: the front end and the back end. They connect to each other through a network, usually the Internet. The front end is the side the computer user, or client, sees. The back end is the "cloud" section of the system. The front end includes the client's computer (or computer network)
RESEARCH ARTICLE OPEN ACCESS
2. K.Delhi Babu Int. Journal of Engineering Research and Applications www.ijera.com
ISSN : 2248-9622, Vol. 4, Issue 11(Version - 5), November 2014, pp.51-55
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and the application required to access the cloud computing system. Not all cloud computing systems have the same user interface. In cloud computing environment, resource allocation or load balancing takes place at two levels. First, when an application is uploaded to the cloud, the load balancer assigns the requested process to physical computers, attempting to balance the computational load of multiple applications across physical computers. Second, when an application receives multiple incoming requests, these requests should be each assigned to a specific requested application instance to balance the computational load across a set of instances of the same requested application.
II. SIGNIFICANCE OF RESOURCE ALLOCATION
In cloud computing, Resource Allocation (RA) is the process of assigning available resources to the needed cloud applications over the internet. Resource allocation starves services if the allocation is not managed precisely. Resource provisioning solves that problem by allowing the service providers to manage the resources for each individual module. Resource Allocation Strategy (RAS) is all about integrating cloud provider activities for utilizing and allocating scarce resources within the limit of cloud environment so as to meet the needs of the cloud application. It requires the type and amount of resources needed by each application in order to complete a user job. The order and time of allocation of resources are also an input for an optimal RAS. An optimal RAS should avoid the following criteria as follows: a) Resource contention situation arises when two applications try to access the same resource at the same time. b) Scarcity of resources arises when there are limited resources. c) Resource fragmentation situation arises when the resources are isolated. [There will be enough resources but not able to allocate to the needed application.] d) Over-provisioning of resources arises when the application gets surplus resources than the demanded one. e) Under-provisioning of resources occurs when the application is assigned with fewer numbers of resources than the demand.
Resource users’ (cloud users) estimates of resource demands to complete a job before the estimated time may lead to an over-provisioning of resources. Resource providers’ allocation of resources may lead to an under-provisioning of resources. From the cloud user’s angle, the application requirement and Service Level Agreement (SLA) are major inputs to RAS. The offerings, resource status and available resources are the inputs required from the other side to manage and allocate resources to host applications [1] by RAS. The outcome of any optimal RAS must satisfy the parameters such as throughput, latency and response time. Even though cloud provides reliable resources, it also poses a crucial problem in allocating and managing resources dynamically across the applications. From the perspective of a cloud provider, predicting the dynamic nature of users, user demands, and application demands are impractical. For the cloud users, the job should be completed on time with minimal cost. Hence due to limited resources, resource heterogeneity, locality restrictions, environmental necessities and dynamic nature of resource demand, we need an efficient resource allocation system that suits cloud environments. Cloud resources consist of physical and virtual resources. The physical resources are shared across multiple compute requests through virtualization and provisioning [1]. The request for virtualized resources is described through a set of parameters detailing the processing, memory and disk needs. Provisioning satisfies the request by mapping virtualized resources to physical ones. The hardware and software resources are allocated to the cloud applications on-demand basis. For scalable computing, Virtual Machines are rented. The complexity of finding an optimum resource allocation is exponential in huge systems like big clusters, data centers or Grids. Since resource demand and supply can be dynamic and uncertain, various strategies for resource allocation are proposed. This paper puts forth various resource allocation strategies deployed in cloud environments. A. Task Scheduling User assigns the task to be executed over cloud. The task is received by cloud coordinator (CC). Cloud coordinator forwards the task over datacenters (DC). Datacenters contains number of unfixed hosts consisting of pool of virtual machines (VM). These hosts can be configured or deleted as per the demand.[2] B. Resources Allocation VMM asks for resources from the resource provider by sending the task requirements. Resource provider checks the availability of resources with Resource Owner.
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Fig.1 Task Execution
If the resources are available, the resource owner
grants the access permission to use the resources to
resource provider. Resource provider further provides
access of the resources for creation of virtual
machines.[5]
III. FIRST COME FIRST SERVE vs
ROUND ROBIN
FCFS for parallel processing and is aiming at the
resource with the smallest waiting queue time and is
selected for the incoming task. Allocation of
application-specific VMs to Hosts in a Cloud-based
data center is the responsibility of the virtual machine
provisioned component. The default policy
implemented by the VM provisioned is a
straightforward policy that allocates a VM to the
Host in First-Come-First-Serve (FCFS) basis. The
disadvantages of FCFS is that it is non preemptive.
The shortest tasks which are at the back of the queue
have to wait for the long task at the front to finish .Its
turnaround and response is quite low. [6]
Round Robin (RR) algorithm focuses on the
fairness. RR uses the ring as its queue to store jobs.
Each job in a queue has the same execution time and
it will be executed in turn. If a job can’t be completed
during its turn, it will be stored back to the queue
waiting for the next turn. The advantage of RR
algorithm is that each job will be executed in turn and
they don’t have to be waited for the previous one to
get completed. But if the load is found to be heavy,
RR will take a long time to complete all the jobs. The
drawback of RR is that the largest job takes enough
time for completion.
IV. LINEAR INTEGER PROGRAMMING
Linear programming is used for optimization
problems and it is applied on specific problems with
a particular formulation described in [7]. Best
solutions like maximum gain or minimum cost is
found through a mathematical model by the help of
domain constraints encoded as linear equations.
Linear programming methodology is widely used in
operations research. Elements of linear programming
are given below:
Linear Objective Function: Value to be
optimized is called objective function. This
function should be represented as a linear
equation, such as:
Maximize: 1 1 2 2 c x c x
Constraints: Linear inequalities of the
problem domain that bounds the solution
space are called constraints. An optimum
solution that meets these constraints’
requirements is searched by objective
function. Each constraint should be
represented as a linear equation, such as:
1,1 1 1,2 2 1 a x a x b
2,1 1 2,2 2 2 a x a x b
3,1 1 3,2 2 3 a x a x b
Decision Variables: Both objective function and
constraints are based on decision variables i x whose
optimal values are searched with simplex methods in
linear programming.
Simplex Method: Basic algorithm generally used for
linear programming is the simplex method [3]. It was
proven to solve linear formulated problems of
acceptable size in a reasonable time. The simplex
method works by finding a feasible solution, and then
moving from that point to any vertex of the feasible
set that improves the cost function. Eventually a
corner is reached from which any movement does not
improve the cost function. This is the optimal
solution. [3] The problem is usually formulated in
matrix form, and represented as:
Maximize: c x T
Subject to: Ax b, x 0
where x represents the vector of variables (to be
determined), c and b are vectors of (known)
coefficients and A is a (known) matrix of coefficients
[4]. In this formulation, a vector x is a feasible
solution of the linear programming problem if it
satisfies the given constraints. Problems defined in
this formulation have three different types [3]:
Infeasible: None of the vectors in solution
space can satisfy the given constraints.
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Unbounded: Given constraints are not enough for bounding objective function parameters in the solution space. So, a better solution with an improved objective function value can exist.
Optimal: Problem formulated in linear programming has an optimum value for the objective function and there exists vector(s)
that can create such optimum value with satisfying the given constraints.
Integer linear programming is a customized version of linear programming where all decision variables of objective function are integers. As resource allocation problem requires integer results, only integer linear programming can be used for finding the solution.
Fig 2: Elapsed Time for Integer Linear Programming Algorithm
V. ADVANTAGES AND LIMITATIONS
There are many benefits in resource allocation while using cloud computing irrespective of size of the organization and business markets. But there are some limitations as well, since it is an evolving technology. Let’s have a comparative look at the advantages and limitations of resource allocation in cloud. A. Advantages: 1) The biggest benefit of resource allocation is that user neither has to install software nor hardware to access the applications, to develop the application and to host the application over the internet. 2) The next major benefit is that there is no limitation of place and medium. We can reach our applications and data anywhere in the world, on any system. 3) The user does not need to expend on hardware and software systems. 4) Cloud providers can share their resources over the internet during resource scarcity. B. Limitations 1) Since users rent resources from remote servers for their purpose, they don’t have control over their resources.
2) Migration problem occurs, when the users wants to switch to some other provider for the better storage of their data. It’s not easy to transfer huge data from one provider to the other. 3) In public cloud, the clients’ data can be susceptible to hacking or phishing attacks. Since the servers on cloud are interconnected, it is easy for malware to spread. 4) Peripheral devices like printers or scanners might not work with cloud. Many of them require software to be installed locally. Networked peripherals have lesser problems. 5) More and deeper knowledge is required for allocating and managing resources in cloud, since all knowledge about the working of the cloud mainly depends upon the cloud service provider.
VI. CONCLUSIONS
Cloud computing technology is increasingly being used in enterprises and business markets. A review shows that dynamic resource allocation is growing need of cloud providers for more number of users and with the less response time. In cloud paradigm, an effective resource allocation strategy is required for achieving user satisfaction and maximizing the profit for cloud service providers.
This paper summarizes the main types of RAS and its impacts in cloud system. Some of the
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strategies discussed above mainly focus on memory resources but are lacking in other factors. Hence this survey paper will hopefully motivate future researchers to come up with smarter and secured optimal resource allocation algorithms and framework to strengthen the cloud computing paradigm. REFERENCES [1] Patricia Takako Endo et al. :Resource allocation for distributed cloud :Concept and Research challenges(IEEE,2011),pp.42-46 . [2] Daniel Warneke and Odej Kao, Exploiting dynamic resource allocation for efficient parallel data processing in the cloud, IEEE Transactions On Parallel And Distributed Systems, 2011.
[3] G. Dantzig, Linear Programming and Extensions. Princeton University Press, 1963. [Online]. Available: http://www.worldcat.org/isbn/0691059136 [4] N. Meggido, “Pathways to the optimal set in linear programming,” Progress in Mathematical Programming Interior-point and related methods, pp. 131–158, 1988. [5] Q. Cao, W. Gong and Z. Wei, “An Optimized Algorithm for Task Scheduling Based On Activity Based Costing in Cloud Computing,” In Proceedings of Third International Conference on Bioinformatics and Biomedical Engineering, 2009, pp. 1-3 [6] V. Vinothina, Dr. R. Shridaran, and Dr. Padmavathi Ganpathi, A survey on resource allocation strategies in cloud computing, International Journal of Advanced Computer Science and Applications, 3(6):97--104, 2012. [7] C. Papagianni, A. Leivadeas, S. Papavassiliou, V. Maglaris, C. Cervello- Pastor, A. Monje, “On the Optimal Allocation of Virtual Resources in Cloud- Computing Networks,” IEEE Teans. Computers, vol. 62, no. 6, pp. 1060-1071, Jun. 2013, doi: 10.1109/TC.2013.31.
K.Delhi Babu received the MS from BITS Pilani in Software Systems and PhD degree in Software Architecture from Sri Venkateswara University Tirupati, 2011. He is currently Working as Professor in Computer Science Department at Sree Vidyanikethan Engineering College, Tirupati , Andhra Pradesh. His current research interests include Software testing, Software Architecture and Software Engineering.
D.Giridhar Kumar received the B.Tech degree in Computer Science and Engineering, from Sree Vidyanikethan Engineering College affiliated to JNTUA, Tirupati, Andhra Pradesh, in 2011. He received M.Tech degree in Computer Science from the Department of Computer Science and Engineering, Sree Vidyanikethan Engineering College, Tirupati, Andhra Pradesh, 2014. His current research interests include network security and cloud computing.