Abstract
AbstractPresent Dynamic VM Consolidation (DVMC) algorithms assume that optimal energy efficiency can be achieved via maximum load on Physical Machines (PMs). Such assumption has become invalid with the advent of the highly energy proportional PMs. Additionally, these algorithms consider only varying resource demand, ignoring dissimilarity of workload finishing time, aka the VM Release Time (VMRT), whereas both aspects are strongly associated with energy consumption. Consequently, traditional algorithms fail to proffer optimal performance under real Cloud scenarios. Although minimization of VM migration brings massive benefit for Cloud Data Center (CDC), it is complete opposite of what is needed to minimize energy consumption through DVMC. As such, our proposed multi-objective Stochastic Release Time aware DVMC (SRTDVMC) algorithm is unique in addressing concomitant minimization of energy consumption and VM migration in the presence of state-of-the-art PMs and heterogeneous workloads.KeywordsHighly energy proportional serversCloud data center energy efficiencyDynamic VM consolidation
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