To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
A stochastic model to investigate data center performance and qo s in iaas cl...JPINFOTECH JAYAPRAKASH
This document proposes a stochastic model based on Stochastic Reward Nets (SRNs) to evaluate the performance and quality of service of Infrastructure as a Service (IaaS) cloud computing systems. The model can represent thousands of physical and virtual resources, and different cloud management strategies and configurations. It defines metrics like utilization, availability, response time and resilience to analyze system behavior from the perspective of both cloud providers and users. The model provides a flexible way to analyze cloud systems that is more scalable than simulation and provides more internal insight than field experiments.
International Journal of Engineering Research and DevelopmentIJERD Editor
This document summarizes a research paper on developing an efficient dynamic resource scheduling model called CRAM for cloud computing. The proposed model uses Stochastic Reward Nets to model cloud resources and client requests in an analytical way. It captures key concepts like virtualization, federation between clouds, and defines performance metrics from the perspective of both cloud providers and users. The model is scalable and can represent systems with thousands of resources to analyze the impact of different resource management strategies.
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.
IMPACT OF RESOURCE MANAGEMENT AND SCALABILITY ON PERFORMANCE OF CLOUD APPLICA...IJCSEA Journal
Cloud computing facilitates service providers to rent their computing capabilities for deploying
applications depending on user requirements. Applications of cloud have diverse composition,
configuration and deployment requirements. Quantifying the performance of applications in Cloud
computing environments is a challenging task. In this paper, we try to identify various parameters
associated with performance of
IMPACT OF RESOURCE MANAGEMENT AND SCALABILITY ON PERFORMANCE OF CLOUD APPLICA...IJCSEA Journal
Cloud computing facilitates service providers to rent their computing capabilities for deploying
applications depending on user requirements. Applications of cloud have diverse composition,
configuration and deployment requirements. Quantifying the performance of applications in Cloud
computing environments is a challenging task. In this paper, we try to identify various parameters
associated with performance of cloud applications and analyse the impact of resource management and
scalability among them.
A stochastic model to investigate data center performance and qo s in iaas cl...JPINFOTECH JAYAPRAKASH
This document proposes a stochastic model based on Stochastic Reward Nets (SRNs) to evaluate the performance and quality of service of Infrastructure as a Service (IaaS) cloud computing systems. The model can represent thousands of physical and virtual resources, and different cloud management strategies and configurations. It defines metrics like utilization, availability, response time and resilience to analyze system behavior from the perspective of both cloud providers and users. The model provides a flexible way to analyze cloud systems that is more scalable than simulation and provides more internal insight than field experiments.
International Journal of Engineering Research and DevelopmentIJERD Editor
This document summarizes a research paper on developing an efficient dynamic resource scheduling model called CRAM for cloud computing. The proposed model uses Stochastic Reward Nets to model cloud resources and client requests in an analytical way. It captures key concepts like virtualization, federation between clouds, and defines performance metrics from the perspective of both cloud providers and users. The model is scalable and can represent systems with thousands of resources to analyze the impact of different resource management strategies.
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.
IMPACT OF RESOURCE MANAGEMENT AND SCALABILITY ON PERFORMANCE OF CLOUD APPLICA...IJCSEA Journal
Cloud computing facilitates service providers to rent their computing capabilities for deploying
applications depending on user requirements. Applications of cloud have diverse composition,
configuration and deployment requirements. Quantifying the performance of applications in Cloud
computing environments is a challenging task. In this paper, we try to identify various parameters
associated with performance of
IMPACT OF RESOURCE MANAGEMENT AND SCALABILITY ON PERFORMANCE OF CLOUD APPLICA...IJCSEA Journal
Cloud computing facilitates service providers to rent their computing capabilities for deploying
applications depending on user requirements. Applications of cloud have diverse composition,
configuration and deployment requirements. Quantifying the performance of applications in Cloud
computing environments is a challenging task. In this paper, we try to identify various parameters
associated with performance of cloud applications and analyse the impact of resource management and
scalability among them.
排隊理論_An Exploration of The Optimization of Executive Scheduling in The Cloud ...婉萍 蔡
This document summarizes research on optimizing executive scheduling in cloud computing. It outlines the cloud computing architecture and categories. It then discusses developing a scheduling model and system to simulate scheduling across multiple hosts using queuing theory models. The system is tested by varying service rates and scheduling parameters to analyze performance. It concludes the models can help classify the best scheduling approach to more closely match user computer resource needs. It suggests comparing the simulation to more cases and setting demand parameters closer to real situations.
Resource Monitoring Algorithms Evaluation For Cloud EnvironmentCSCJournals
Cloud computing is a type of distributed computing allowing to share many resources such as CPU, memory, storage ...etc. The status of these resources changes from time to time due to the dynamic adaptive ability of the cloud computing characteristics. Hence, the powerful and scalable monitoring algorithm is needed to monitor the status of these resources throughout the time. There are many models have been proposed for monitoring the distributed systems resources; the push-based, the pull-based, and the push/pull model. Most of the common monitoring systems are based on these models (e.g., Ganglia which based on push model and Nagios, which based on pull model). According to the work in this paper, a comparative study has been done to implement and evaluate these three models on the cloud environment. The implementation results showed that the push-based model outperforms the other two models due to its high scalability, stability, and efficiency.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
Energy aware load balancing and application scaling for the cloud ecosystemLeMeniz Infotech
Energy aware load balancing and application scaling for the cloud ecosystem
Do Your Projects With Technology Experts
To Get this projects Call : 9566355386 / 99625 88976
Visit : www.lemenizinfotech.com / www.ieeemaster.com
Mail : projects@lemenizinfotech.com
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
The Effects of Temperature Variation on Data Center IT SystemsRafael Roque
This document proposes using stochastic Petri net (SPN) models to evaluate the effect of temperature changes on data center IT systems availability. A case study models 8 configurations of different IT and cooling architectures for a hotel company's data center. The models calculate metrics like acquisition cost, operational cost, income, employees cost, profit, maintenance cost, and financial losses. The results show the financial losses from different temperature impacts on availability. The conclusion is that the SPN models can estimate financial losses from temperature variation effects.
Failure aware resource provisioning for hybrid cloud infrastructureFreddie Zhang
This paper proposes failure-aware resource provisioning policies for a hybrid cloud infrastructure to fulfill user request deadlines. The key contributions are:
1) A flexible and scalable hybrid cloud architecture is presented to solve the problem of resource provisioning.
2) Various provisioning policies are proposed based on workload and failure models to meet a common QoS requirement of request deadlines.
3) The policies are evaluated under realistic workloads and failures, considering metrics like deadline violation rate and job slowdown.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
The document discusses various scheduling techniques in cloud computing. It begins with an introduction to scheduling and its importance in cloud computing. It then covers traditional scheduling approaches like FCFS, priority queue, and shortest job first. The document also presents job scheduling frameworks, dynamic and fault-tolerant scheduling, deadline-constrained scheduling, and inter-cloud meta-scheduling. It concludes with the benefits of effective scheduling in improving service quality and resource utilization in cloud environments.
DYNAMIC TASK SCHEDULING BASED ON BURST TIME REQUIREMENT FOR CLOUD ENVIRONMENTIJCNCJournal
Cloud computing has an indispensable role in the modern digital scenario. The fundamental challenge of cloud systems is to accommodate user requirements which keep on varying. This dynamic cloud environment demands the necessity of complex algorithms to resolve the trouble of task allotment. The overall performance of cloud systems is rooted in the efficiency of task scheduling algorithms. The dynamic property of cloud systems makes it challenging to find an optimal solution satisfying all the evaluation metrics. The new approach is formulated on the Round Robin and the Shortest Job First algorithms. The Round Robin method reduces starvation, and the Shortest Job First decreases the average waiting time. In this work, the advantages of both algorithms are incorporated to improve the makespan of user tasks.
LOCALITY SIM: CLOUD SIMULATOR WITH DATA LOCALITY ijccsa
Cloud Computing (CC) is a model for enabling on-demand access to a shared pool of configurable computing resources. Testing and evaluating the performance of the cloud environment for allocating, provisioning, scheduling, and data allocation policy have great attention to be achieved. Therefore, using cloud simulator would save time and money, and provide a flexible environment to evaluate new research
work. Unfortunately, the current simulators (e.g., CloudSim, NetworkCloudSim, GreenCloud, etc..) deal with the data as for size only without any consideration about the data allocation policy and locality. On the other hand, the NetworkCloudSim simulator is considered one of the most common used simulators because it includes different modules which support needed functions to a simulated cloud environment,
and it could be extended to include new extra modules. According to work in this paper, the NetworkCloudSim simulator has been extended and modified to support data locality. The modified simulator is called LocalitySim. The accuracy of the proposed LocalitySim simulator has been proved by building a mathematical model. Also, the proposed simulator has been used to test the performance of the
three-tire data center as a case study with considering the data locality feature
iaas cloud architecture
introduction
virtulization plays an important role as establishing technology
virtual machine manager
network manager,
storage manager
image manager
information manager
federation manager
authentication and authorization
image manager
information manager
service manager
cloud federation
JPJ1403 A Stochastic Model To Investigate Data Center Performance And QoS I...chennaijp
We are good ieee java projects development center in chennai and pondicherry. We guided advanced java techonolgies projects of cloud computing, data mining, Secure Computing, Networking, Parallel & Distributed Systems, Mobile Computing and Service Computing (Web Service).
For More Details:
http://jpinfotech.org/final-year-ieee-projects/2014-ieee-projects/java-projects/
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
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
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
IMPACT OF RESOURCE MANAGEMENT AND SCALABILITY ON PERFORMANCE OF CLOUD APPLICA...IJCSEA Journal
Cloud computing facilitates service providers to rent their computing capabilities for deploying
applications depending on user requirements. Applications of cloud have diverse composition,
configuration and deployment requirements. Quantifying the performance of applications in Cloud
computing environments is a challenging task. In this paper, we try to identify various parameters
associated with performance of cloud applications and analyse the impact of resource management and
scalability among them.
IMPACT OF RESOURCE MANAGEMENT AND SCALABILITY ON PERFORMANCE OF CLOUD APPLICA...IJCSEA Journal
Resource management and scalability significantly impact the performance of cloud applications. Effective resource management is needed to optimize performance, functionality, and costs. Scalability is the ability to scale applications up or down based on demand. The literature identifies key factors like network resources, over-provisioning, under-provisioning, and information proxies that influence performance through their effects on resource management and scalability. Performance analysis requires understanding various attributes and is best done using model-based approaches.
Development of a Suitable Load Balancing Strategy In Case Of a Cloud Computi...IJMER
Cloud computing is an attracting technology in the field of computer science. In
Gartner’s report, it says that the cloud will bring changes to the IT industry. The cloud is changing
our life by providing users with new types of services. Users get service from a cloud without paying
attention to the details. NIST gave a definition of cloud computing as 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. More
and more people pay attention to cloud computing. Cloud computing is efficient and scalable but
maintaining the stability of processing so many jobs in the cloud computing environment is a very
complex problem with load balancing receiving much attention for researchers. Since the job
arrival pattern is not predictable and the capacities of each node in the cloud differ, for load
balancing problem, workload control is crucial to improve system performance and maintain
stability. Load balancing schemes depending on whether the system dynamics are important can be
either static or dynamic. Static schemes do not use the system information and are less complex
while dynamic schemes will bring additional costs for the system but can change as the system
status changes. A dynamic scheme is used here for its flexibility. The model has a main controller
and balancers to gather and analyze the information. Thus, the dynamic control has little influence
on the other working nodes. The system status then provides a basis for choosing the right load
balancing strategy. The load balancing model given in this research article is aimed at the public
cloud which has numerous nodes with distributed computing resources in many different
geographic locations. Thus, this model divides the public cloud into several cloud partitions. When
the environment is very large and complex, these divisions simplify the load balancing. The cloud
has a main controller that chooses the suitable partitions for arriving jobs while the balancer for
each cloud partition chooses the best load balancing strategy.
排隊理論_An Exploration of The Optimization of Executive Scheduling in The Cloud ...婉萍 蔡
This document summarizes research on optimizing executive scheduling in cloud computing. It outlines the cloud computing architecture and categories. It then discusses developing a scheduling model and system to simulate scheduling across multiple hosts using queuing theory models. The system is tested by varying service rates and scheduling parameters to analyze performance. It concludes the models can help classify the best scheduling approach to more closely match user computer resource needs. It suggests comparing the simulation to more cases and setting demand parameters closer to real situations.
Resource Monitoring Algorithms Evaluation For Cloud EnvironmentCSCJournals
Cloud computing is a type of distributed computing allowing to share many resources such as CPU, memory, storage ...etc. The status of these resources changes from time to time due to the dynamic adaptive ability of the cloud computing characteristics. Hence, the powerful and scalable monitoring algorithm is needed to monitor the status of these resources throughout the time. There are many models have been proposed for monitoring the distributed systems resources; the push-based, the pull-based, and the push/pull model. Most of the common monitoring systems are based on these models (e.g., Ganglia which based on push model and Nagios, which based on pull model). According to the work in this paper, a comparative study has been done to implement and evaluate these three models on the cloud environment. The implementation results showed that the push-based model outperforms the other two models due to its high scalability, stability, and efficiency.
For further details contact:
N.RAJASEKARAN B.E M.S 9841091117,9840103301.
IMPULSE TECHNOLOGIES,
Old No 251, New No 304,
2nd Floor,
Arcot road ,
Vadapalani ,
Chennai-26.
Energy aware load balancing and application scaling for the cloud ecosystemLeMeniz Infotech
Energy aware load balancing and application scaling for the cloud ecosystem
Do Your Projects With Technology Experts
To Get this projects Call : 9566355386 / 99625 88976
Visit : www.lemenizinfotech.com / www.ieeemaster.com
Mail : projects@lemenizinfotech.com
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
The Effects of Temperature Variation on Data Center IT SystemsRafael Roque
This document proposes using stochastic Petri net (SPN) models to evaluate the effect of temperature changes on data center IT systems availability. A case study models 8 configurations of different IT and cooling architectures for a hotel company's data center. The models calculate metrics like acquisition cost, operational cost, income, employees cost, profit, maintenance cost, and financial losses. The results show the financial losses from different temperature impacts on availability. The conclusion is that the SPN models can estimate financial losses from temperature variation effects.
Failure aware resource provisioning for hybrid cloud infrastructureFreddie Zhang
This paper proposes failure-aware resource provisioning policies for a hybrid cloud infrastructure to fulfill user request deadlines. The key contributions are:
1) A flexible and scalable hybrid cloud architecture is presented to solve the problem of resource provisioning.
2) Various provisioning policies are proposed based on workload and failure models to meet a common QoS requirement of request deadlines.
3) The policies are evaluated under realistic workloads and failures, considering metrics like deadline violation rate and job slowdown.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
The document discusses various scheduling techniques in cloud computing. It begins with an introduction to scheduling and its importance in cloud computing. It then covers traditional scheduling approaches like FCFS, priority queue, and shortest job first. The document also presents job scheduling frameworks, dynamic and fault-tolerant scheduling, deadline-constrained scheduling, and inter-cloud meta-scheduling. It concludes with the benefits of effective scheduling in improving service quality and resource utilization in cloud environments.
DYNAMIC TASK SCHEDULING BASED ON BURST TIME REQUIREMENT FOR CLOUD ENVIRONMENTIJCNCJournal
Cloud computing has an indispensable role in the modern digital scenario. The fundamental challenge of cloud systems is to accommodate user requirements which keep on varying. This dynamic cloud environment demands the necessity of complex algorithms to resolve the trouble of task allotment. The overall performance of cloud systems is rooted in the efficiency of task scheduling algorithms. The dynamic property of cloud systems makes it challenging to find an optimal solution satisfying all the evaluation metrics. The new approach is formulated on the Round Robin and the Shortest Job First algorithms. The Round Robin method reduces starvation, and the Shortest Job First decreases the average waiting time. In this work, the advantages of both algorithms are incorporated to improve the makespan of user tasks.
LOCALITY SIM: CLOUD SIMULATOR WITH DATA LOCALITY ijccsa
Cloud Computing (CC) is a model for enabling on-demand access to a shared pool of configurable computing resources. Testing and evaluating the performance of the cloud environment for allocating, provisioning, scheduling, and data allocation policy have great attention to be achieved. Therefore, using cloud simulator would save time and money, and provide a flexible environment to evaluate new research
work. Unfortunately, the current simulators (e.g., CloudSim, NetworkCloudSim, GreenCloud, etc..) deal with the data as for size only without any consideration about the data allocation policy and locality. On the other hand, the NetworkCloudSim simulator is considered one of the most common used simulators because it includes different modules which support needed functions to a simulated cloud environment,
and it could be extended to include new extra modules. According to work in this paper, the NetworkCloudSim simulator has been extended and modified to support data locality. The modified simulator is called LocalitySim. The accuracy of the proposed LocalitySim simulator has been proved by building a mathematical model. Also, the proposed simulator has been used to test the performance of the
three-tire data center as a case study with considering the data locality feature
iaas cloud architecture
introduction
virtulization plays an important role as establishing technology
virtual machine manager
network manager,
storage manager
image manager
information manager
federation manager
authentication and authorization
image manager
information manager
service manager
cloud federation
JPJ1403 A Stochastic Model To Investigate Data Center Performance And QoS I...chennaijp
We are good ieee java projects development center in chennai and pondicherry. We guided advanced java techonolgies projects of cloud computing, data mining, Secure Computing, Networking, Parallel & Distributed Systems, Mobile Computing and Service Computing (Web Service).
For More Details:
http://jpinfotech.org/final-year-ieee-projects/2014-ieee-projects/java-projects/
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
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
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
IMPACT OF RESOURCE MANAGEMENT AND SCALABILITY ON PERFORMANCE OF CLOUD APPLICA...IJCSEA Journal
Cloud computing facilitates service providers to rent their computing capabilities for deploying
applications depending on user requirements. Applications of cloud have diverse composition,
configuration and deployment requirements. Quantifying the performance of applications in Cloud
computing environments is a challenging task. In this paper, we try to identify various parameters
associated with performance of cloud applications and analyse the impact of resource management and
scalability among them.
IMPACT OF RESOURCE MANAGEMENT AND SCALABILITY ON PERFORMANCE OF CLOUD APPLICA...IJCSEA Journal
Resource management and scalability significantly impact the performance of cloud applications. Effective resource management is needed to optimize performance, functionality, and costs. Scalability is the ability to scale applications up or down based on demand. The literature identifies key factors like network resources, over-provisioning, under-provisioning, and information proxies that influence performance through their effects on resource management and scalability. Performance analysis requires understanding various attributes and is best done using model-based approaches.
Development of a Suitable Load Balancing Strategy In Case Of a Cloud Computi...IJMER
Cloud computing is an attracting technology in the field of computer science. In
Gartner’s report, it says that the cloud will bring changes to the IT industry. The cloud is changing
our life by providing users with new types of services. Users get service from a cloud without paying
attention to the details. NIST gave a definition of cloud computing as 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. More
and more people pay attention to cloud computing. Cloud computing is efficient and scalable but
maintaining the stability of processing so many jobs in the cloud computing environment is a very
complex problem with load balancing receiving much attention for researchers. Since the job
arrival pattern is not predictable and the capacities of each node in the cloud differ, for load
balancing problem, workload control is crucial to improve system performance and maintain
stability. Load balancing schemes depending on whether the system dynamics are important can be
either static or dynamic. Static schemes do not use the system information and are less complex
while dynamic schemes will bring additional costs for the system but can change as the system
status changes. A dynamic scheme is used here for its flexibility. The model has a main controller
and balancers to gather and analyze the information. Thus, the dynamic control has little influence
on the other working nodes. The system status then provides a basis for choosing the right load
balancing strategy. The load balancing model given in this research article is aimed at the public
cloud which has numerous nodes with distributed computing resources in many different
geographic locations. Thus, this model divides the public cloud into several cloud partitions. When
the environment is very large and complex, these divisions simplify the load balancing. The cloud
has a main controller that chooses the suitable partitions for arriving jobs while the balancer for
each cloud partition chooses the best load balancing strategy.
The document proposes a three-stage model for energy utilization in cloud environments. The first stage defines cloud server capabilities using quantitative vectors. The second stage performs clustering to categorize cloud servers based on a cost analysis. The final stage maps user requests to cloud server clusters to identify the most efficient allocation based on energy and resource constraints.
International Refereed Journal of Engineering and Science (IRJES)irjes
International Refereed Journal of Engineering and Science (IRJES) is a leading international journal for publication of new ideas, the state of the art research results and fundamental advances in all aspects of Engineering and Science. IRJES is a open access, peer reviewed international journal with a primary objective to provide the academic community and industry for the submission of half of original research and applications
International Refereed Journal of Engineering and Science (IRJES)irjes
International Refereed Journal of Engineering and Science (IRJES) is a leading international journal for publication of new ideas, the state of the art research results and fundamental advances in all aspects of Engineering and Science. IRJES is a open access, peer reviewed international journal with a primary objective to provide the academic community and industry for the submission of half of original research and applications
This document summarizes a research paper on dynamic consolidation of virtual machines in cloud data centers to manage overloaded hosts while maintaining quality of service constraints. It proposes using a Markov chain model and control algorithm to optimally detect host overloads by maximizing the average time between VM migrations, while meeting a specified QoS goal. The algorithm handles unknown workloads using a multisize sliding window approach. Evaluation shows the algorithm efficiently solves the problem of host overload detection as part of dynamic VM consolidation in cloud computing systems.
ieee projects is the most important projects for engineering students like BE Projects and ME Projects, MCA students Projects, BCA students Projects, MPhile Projects
The document discusses resource allocation and scheduling (RAS) in cloud computing. It identifies five major topics in cloud RAS: locality-aware task scheduling, reliability-aware scheduling, energy-aware RAS, Software as a Service (SaaS) layer RAS, and workflow scheduling. These topics are classified into three parts: performance-based RAS, cost-based RAS, and performance- and cost-based RAS. Existing RAS policies and algorithms are discussed for each topic in terms of parameters like execution efficiency, cost-effectiveness, reliability, and resource utilization.
This document proposes a new Cloud Elasticity as a Service (CES) framework in OpenStack for efficiently managing cloud infrastructure utilization. CES allows cloud administrators to define policies with configurable quality-of-service parameters. It periodically validates policies by collecting monitoring data and automatically scales resources up or down using templates when policy conditions are met, without human intervention. The framework was tested by increasing load on a virtual machine and observing CES scale it up by triggering the policy template as CPU usage exceeded thresholds.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
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
A hierarchical correlation model for evaluating reliability, performance, and...ieeepondy
The document presents a new hierarchical correlation model for evaluating reliability, performance, and power consumption of cloud services. The model uses Markov models, queuing theory, and Bayesian approaches to analyze how these metrics are correlated. It accounts for characteristics of cloud systems like virtual machines hosted on servers, common cause failures from server issues, and multicore CPU mapping. The model also develops a tradeoff parameter and profit optimization approach to evaluate performance versus power consumption tradeoffs.
This document discusses various cloud computing architectures including workload distribution, cloud bursting, elastic disk provisioning, resource pooling, dynamic failure detection and recovery, and capacity planning architectures. It also covers cloud mechanisms like automated scaling listeners, load balancers, pay-per-use monitors, audit monitors, service level agreements (SLAs), and fail-over systems that are important components of cloud architectures. The key cloud architectures aim to optimize resource utilization, enable horizontal and vertical scaling, provide high availability, and implement billing and monitoring functions.
THRESHOLD BASED VM PLACEMENT TECHNIQUE FOR LOAD BALANCED RESOURCE PROVISIONIN...IJCNCJournal
The unbalancing load issue is a multi-variation, multi-imperative issue that corrupts the execution and productivity of processing assets. Workload adjusting methods give solutions of load unbalancing circumstances for two bothersome aspects over-burdening and under-stacking. Cloud computing utilizes planning and workload balancing for a virtualized environment, resource partaking in cloud foundation. These two factors must be handled in an improved way in cloud computing to accomplish ideal resource sharing. Henceforth, there requires productive resource, asset reservation for guaranteeing load advancement in the cloud. This work aims to present an incorporated resource, asset reservation, and workload adjusting calculation for effective cloud provisioning. The strategy develops a Priority-based Resource Scheduling Model to acquire the resource, asset reservation with threshold-based load balancing for improving the proficiency in cloud framework. Extending utilization of Virtual Machines through the suitable and sensible outstanding task at hand modifying is then practiced by intensely picking a job from submitting jobs using Priority-based Resource Scheduling Model to acquire resource asset reservation. Experimental evaluations represent, the proposed scheme gives better results by reducing execution time, with minimum resource cost and improved resource utilization in dynamic resource provisioning conditions.
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.
QOS WITH RELIABILITY AND SCALABILITY IN ADAPTIVE SERVICE-BASED SYSTEMScscpconf
Service-based systems that are dynamically composed at runtime to provide complex, adaptive
functionality are currently one of the main development paradigms in software engineering.
However, the Quality of Service (QoS) delivered by these systems remains an important
concern, and needs to be managed in an equally adaptive and predictable way. To address this
need, we introduce a novel, tool-supported framework for the development of adaptive servicebased
systems called QoSMOS (QoS Management and Optimization of Service-based systems). QoSMOS can be used to develop service-based systems that achieve their QoS requirements through dynamically adapting to changes in the system state, environment, and workload. QoSMOS service-based systems translate high-level QoS requirements specified by their administrators into probabilistic temporal logic formulae, which are then formally and automatically analyzed to identify and enforce optimal system configurations. The QoSMOS self-adaptation mechanism can handle reliability and performance-related QoS requirements, and can be integrated into newly developed solutions or legacy systems. The effectiveness and scalability of the approach are validated using simulations and a set of experiments based on an implementation of an adaptive service-based system for remote medical assistance.
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JAVA 2013 IEEE CLOUDCOMPUTING PROJECT A stochastic model to investigate data center performance and qo s in iaas cloud computing systems
1. CG
A Stochastic Model to Investigate Data Center Performance and QoS
in IaaS Cloud Computing Systems
ABSTRACT:
Cloud data center management is a key problem due to the numerous and heterogeneous
strategies that can be applied, ranging from the VM placement to the federation with other
clouds. Performance evaluation of Cloud Computing infrastructures is required to predict and
quantify the cost-benefit of a strategy portfolio and the corresponding Quality of Service (QoS)
experienced by users. Such analyses are not feasible by simulation or on-the-field
experimentation, due to the great number of parameters that have to be investigated. In this
paper, we present an analytical model, based on Stochastic Reward Nets (SRNs), that is both
scalable to model systems composed of thousands of resources and flexible to represent
different policies and cloud-specific strategies. Several performance metrics are defined and
evaluated to analyze the behavior of a Cloud data center: utilization, availability, waiting time,
and responsiveness. A resiliency analysis is also provided to take into account load bursts.
Finally, a general approach is presented that, starting from the concept of system capacity, can
help system managers to opportunely set the data center parameters under different working
conditions.
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2. EXISTING SYSTEM:
In order to integrate business requirements and application level needs, in terms of Quality of
Service (QoS), cloud service provisioning is regulated by Service Level Agreements (SLAs):
contracts between clients and providers that express the price for a service, the QoS levels
required during the service provisioning, and the penalties associated with the SLA violations.
In such a context, performance evaluation plays a key role allowing system managers to
evaluate the effects of different resource management strategies on the data center functioning
and to predict the corresponding costs/benefits.
Cloud systems differ from traditional distributed systems. First of all, they are characterized by
a very large number of resources that can span different administrative domains. Moreover, the
high level of resource abstraction allows to implement particular resource management
techniques such as VM multiplexing or VM live migration that, even if transparent to final
users, have to be considered in the design of performance models in order to accurately
understand the system behavior. Finally, different clouds, belonging to the same or to different
organizations, can dynamically join each other to achieve a common goal, usually represented
by the optimization of resources utilization. This mechanism, referred to as cloud federation,
allows to provide and release resources on demand thus providing elastic capabilities to the
whole infrastructure.
DISADVANTAGES OF EXISTING SYSTEM:
On-the-field experiments are mainly focused on the offered QoS, they are based on a
black box approach that makes difficult to correlate obtained data to the internal resource
management strategies implemented by the system provider.
Simulation does not allow to conduct comprehensive analyses of the system performance
due to the great number of parameters that have to be investigated.
PROPOSED SYSTEM:
3. In this paper, we present a stochastic model, based on Stochastic Reward Nets (SRNs), that
exhibits the above mentioned features allowing to capture the key concepts of an IaaS cloud
system. The proposed model is scalable enough to represent systems composed of thousands of
resources and it makes possible to represent both physical and virtual resources exploiting cloud
specific concepts such as the infrastructure elasticity. With respect to the existing literature, the
innovative aspect of the present work is that a generic and comprehensive view of a cloud
system is presented. Low level details, such as VM multiplexing, are easily integrated with
cloud based actions such as federation, allowing to investigate different mixed strategies. An
exhaustive set of performance metrics are defined regarding both the system provider (e.g.,
utilization) and the final users (e.g., responsiveness).
ADVANTAGES OF PROPOSED SYSTEM:
To provide a fair comparison among different resource management strategies, also taking into
account the system elasticity, a performance evaluation approach is described. Such an
approach, based on the concept of system capacity, presents a holistic view of a cloud system
and it allows system managers to study the better solution with respect to an established goal
and to opportunely set the system parameters.
4. SYSTEM ARCHITECTURE:
SYSTEM CONFIGURATION:-
HARDWARE CONFIGURATION:-
Processor - Pentium –IV
Speed - 1.1 Ghz
RAM - 256 MB(min)
Hard Disk - 20 GB
Key Board - Standard Windows Keyboard
Mouse - Two or Three Button Mouse
Monitor - SVGA
SOFTWARE CONFIGURATION:-
5. Operating System : Windows XP
Programming Language : JAVA
Java Version : JDK 1.6 & above.
REFERENCE:
Dario Bruneo, Member, IEEE-“ A Stochastic Model to Investigate Data Center Performance
and QoS in IaaS Cloud Computing Systems”- IEEE TRANSACTIONS ON PARALLEL
AND DISTRIBUTED SYSTEMS 2013.
DOMAIN: WIRELESS NETWORK PROJECTS