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DC Field | Value | Language |
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dc.contributor.author | Raghunath, B.R. | |
dc.contributor.author | Annappa, B. | |
dc.date.accessioned | 2020-03-31T08:18:32Z | - |
dc.date.available | 2020-03-31T08:18:32Z | - |
dc.date.issued | 2019 | |
dc.identifier.citation | International Journal of Internet Technology and Secured Transactions, 2019, Vol.9, 4, pp.491-516 | en_US |
dc.identifier.uri | http://idr.nitk.ac.in/jspui/handle/123456789/10020 | - |
dc.description.abstract | Virtualisation enables multiples virtual machines (VMs) to co-locate on a same physical machine with total isolation. Hence using VMs to launch web services or applications is the common trend nowadays in enterprise information technology (IT). Data centre provides infrastructure to create, configure and manage VMs. It has seen as a utility that clients can pay for only as needed. The growing complexity of modern networked computer systems with virtualisation technology necessitates the needs efficient resource management. We have proposed an intelligent resource manager to control the resource allocation in Xen virtualised environment for dynamically allocating resources to individual VM. Our resource management architecture comprises of fuzzy logic based controller. Experimental results shows that with the proposed system data centre can efficiently allocate CPU resources to VMs that have been produced by customers. The scaling of CPU resources is automatically done in accordance with dynamically changing workload at a minimum granularity of 2 seconds. It improves the resource utilisation by 30% as compared to the ideal method while maintaining throughput as equivalent to the ideal workload allocation. 2019 Inderscience Enterprises Ltd. | en_US |
dc.title | Autonomic resource management framework for virtualised environments | en_US |
dc.type | Article | en_US |
Appears in Collections: | 1. Journal Articles |
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