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Research Article Open Access
Cloud computing allows business customers to increase and decrease their resource usage based on needs. Many of the endorse gains in the cloud model come from resource multiplexing by using virtualization technology. In this dissertation, we present a system that uses virtualization technology to allocate resources dynamically based on “cost based priority” and support green computing by optimizing the number of physical machines in use. We introduce the concept of “skewness” to measure the unevenness in the multi-dimensional resource utilization of physical machines. By minimizing skewness, we can combine different types of workloads nicely and improve the overall utilization of physical machine resources. We develop a set of heuristics that prevent overloaded physical machines in the system effectively by not allowing them in further cycles of resource allocation. We restrict overloaded machines in order to stop further carbon monoxide emission from that machine. Experiment results demonstrate that our algorithm achieves good performance.
VMM(Virtual Machine Monitor),APM(Actively used Physical Machine),LNM(Local Node Manager),IDV(Intelligent Desktop Virtualization), SLA(Service Level Agreement),EC(Elastic Computing), Green Chemistry