The Experts below are selected from a list of 5238 Experts worldwide ranked by ideXlab platform
Sunilkumar S. Manvi - One of the best experts on this subject based on the ideXlab platform.
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Virtual Resource prediction in cloud environment
Journal of Network and Computer Applications, 2016Co-Authors: Gopal Kirshna Shyam, Sunilkumar S. ManviAbstract:With increase in requirement for dynamic execution of user's application in cloud, Resource prediction techniques are gaining a lot of importance as the foundation for online capacity planning and Virtualized Resource management in data centers. There is a wide scope for the development of accurate Resource requirement prediction methods to ensure that the Virtualized Resources do not suffer from over or under-utilization. We propose a Bayesian model to determine short and long-term virtual Resource requirement of the CPU/memory intensive applications on the basis of workload patterns at several data centers in the cloud during several time intervals. However, the model is applied to predict Resource(s) of all applications in general.The parameters considered for prediction in the model are day of week, time-interval of application access, workload, benchmarks, and availability of virtual machines etc. The model is simulated by using the SamIam Bayesian network simulator and workload traces of Amazon EC2 and Google CE data centers in dynamic scenarios. The performance is evaluated by considering benchmarks of CPU intensive applications (web based). The proposed model is able to predict virtual Resources in a cloud environment with better accuracy as compared to other models.
Gopal Kirshna Shyam - One of the best experts on this subject based on the ideXlab platform.
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Virtual Resource prediction in cloud environment
Journal of Network and Computer Applications, 2016Co-Authors: Gopal Kirshna Shyam, Sunilkumar S. ManviAbstract:With increase in requirement for dynamic execution of user's application in cloud, Resource prediction techniques are gaining a lot of importance as the foundation for online capacity planning and Virtualized Resource management in data centers. There is a wide scope for the development of accurate Resource requirement prediction methods to ensure that the Virtualized Resources do not suffer from over or under-utilization. We propose a Bayesian model to determine short and long-term virtual Resource requirement of the CPU/memory intensive applications on the basis of workload patterns at several data centers in the cloud during several time intervals. However, the model is applied to predict Resource(s) of all applications in general.The parameters considered for prediction in the model are day of week, time-interval of application access, workload, benchmarks, and availability of virtual machines etc. The model is simulated by using the SamIam Bayesian network simulator and workload traces of Amazon EC2 and Google CE data centers in dynamic scenarios. The performance is evaluated by considering benchmarks of CPU intensive applications (web based). The proposed model is able to predict virtual Resources in a cloud environment with better accuracy as compared to other models.
Hanan Lutfiyya - One of the best experts on this subject based on the ideXlab platform.
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dcsim a data centre simulation tool for evaluating dynamic Virtualized Resource management
Conference on Network and Service Management, 2012Co-Authors: Michael Tighe, Gaston Keller, Michael Bauer, Hanan LutfiyyaAbstract:Computing today is shifting from hosting services in servers owned by individual organizations to data centres providing Resources to a number of organizations on a shared infrastructure. Managing such a data centre presents a unique set of goals and challenges. Through the use of virtualization, multiple users can run isolated virtual machines (VMs) on a single physical host, allowing for a higher server utilization. By consolidating VMs onto fewer physical hosts, infrastructure costs can be reduced in terms of the number of servers required, power consumption, and maintenance. To meet constantly changing workload levels, running VMs may need to be migrated (moved) to another physical host. Algorithms to perform dynamic VM reallocation, as well as dynamic Resource provisioning on a single host, are open research problems. Experimenting with such algorithms on the data centre scale is impractical. Thus, there is a need for simulation tools to allow rapid development and evaluation of data centre management techniques. We present DCSim, an extensible simulation framework for simulating a data centre hosting an Infrastructure as a Service cloud. We evaluate the scalability of DCSim, and demonstrate its usefulness in evaluating VM management techniques.
Daniel Duffy - One of the best experts on this subject based on the ideXlab platform.
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the virtual climate data server vcds an irods based data management software appliance supporting climate data services and virtualization as a service in the nasa center for climate simulation
2012Co-Authors: John L. Schnase, Glenn S. Tamkin, David W Ripley, Savannah Stong, Roger Gill, Daniel DuffyAbstract:Scientific data services are becoming an important part of the NASA Center for Climate Simulation's mission. Our technological response to this expanding role is built around the concept of a Virtual Climate Data Server (vCDS), repetitive provisioning, image-based deployment and distribution, and virtualization-as-a-service. The vCDS is an iRODS-based data server specialized to the needs of a particular data-centric application. We use RPM scripts to build vCDS images in our local computing environment, our local Virtual Machine Environment, NASA s Nebula Cloud Services, and Amazon's Elastic Compute Cloud. Once provisioned into one or more of these Virtualized Resource classes, vCDSs can use iRODS s federation capabilities to create an integrated ecosystem of managed collections that is scalable and adaptable to changing Resource requirements. This approach enables platform- or software-asa- service deployment of vCDS and allows the NCCS to offer virtualization-as-a-service: a capacity to respond in an agile way to new customer requests for data services.
Michael Tighe - One of the best experts on this subject based on the ideXlab platform.
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dcsim a data centre simulation tool for evaluating dynamic Virtualized Resource management
Conference on Network and Service Management, 2012Co-Authors: Michael Tighe, Gaston Keller, Michael Bauer, Hanan LutfiyyaAbstract:Computing today is shifting from hosting services in servers owned by individual organizations to data centres providing Resources to a number of organizations on a shared infrastructure. Managing such a data centre presents a unique set of goals and challenges. Through the use of virtualization, multiple users can run isolated virtual machines (VMs) on a single physical host, allowing for a higher server utilization. By consolidating VMs onto fewer physical hosts, infrastructure costs can be reduced in terms of the number of servers required, power consumption, and maintenance. To meet constantly changing workload levels, running VMs may need to be migrated (moved) to another physical host. Algorithms to perform dynamic VM reallocation, as well as dynamic Resource provisioning on a single host, are open research problems. Experimenting with such algorithms on the data centre scale is impractical. Thus, there is a need for simulation tools to allow rapid development and evaluation of data centre management techniques. We present DCSim, an extensible simulation framework for simulating a data centre hosting an Infrastructure as a Service cloud. We evaluate the scalability of DCSim, and demonstrate its usefulness in evaluating VM management techniques.
