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dc.contributor.authorMishra, S K-
dc.contributor.authorDeswal, R-
dc.contributor.authorSahoo, S-
dc.contributor.authorSahoo, Bibhudatta-
dc.identifier.citation12th Annual IEEE India Conference (INDICON 2015), Jamia Nagar, New Delhi, 17-20 Dec 2015en_US
dc.descriptionCopyright for this paper belongs to proceeding publisheren_US
dc.description.abstractTo meet the service level agreement (SLA) between the cloud user and the cloud service provider, the service provider has to pay more. The cloud resources are allocated not only to satisfy the quality of services (QoS) those are specified in SLA, but also need to reduce energy utilization. Therefore, task consolidation plays an important role in cloud computing, which map users service requests to appropriate resources resulting in proper utilization of various cloud resources. The enhancement of overall performance of cloud computing also depends on the Task Consolidation approaches. Here, for task consolidation problem, we present an energy aware model which includes description of physical hosts, virtual machines and service requests (tasks) submitted by users. For the proposed model, an Energy Aware Task Consolidation (EATC) algorithm is developed where heterogeneity also affects the performance and show significant improvement in energy savings.en_US
dc.subjectCloud Computingen_US
dc.titleImproving Energy Consumption in Clouden_US
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