IEEE Access · 2017 · 21 citations · 17 references
Cluster ComputingEngineeringCloud Resource ManagementResource WastageOperations ResearchSystems EngineeringCloud Data CenterCombinatorial OptimizationVirtual Machine DeploymentDeployment StrategyCloud SchedulingDistributed Resource ManagementVirtualized InfrastructureComputer EngineeringComputer ScienceInformation EntropyEnergy ManagementEdge ComputingCloud ComputingAnt Colony Optimization
With the recent rapid development of cloud computing technology, how to reduce the costs of a cloud data center effectively has become an important issue. The study on virtual machine deployment mainly aims at deploying virtual machine resources required by users on a physical server rationally and effectively. This paper proposes a multi-population ant colony algorithm to solve problems of virtual machine deployment. With resource wastage and energy consumption as optimization objectives, this algorithm uses multiple ant colonies for the solution and determines strategies for information exchange among ant colonies according to the information entropy of each population to guarantee the balance of its convergence and diversity. The simulation results show that this algorithm has better performance than the single-population ant colony algorithm and can reduce resource wastage and energy consumption effectively for high-demand virtual machine deployment.
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Michael Armbrust, Armando Fox, Rean Griffith et al. · Communications of the ACM · 2010 · 8.9K citations · Full text
The Case for Energy-Proportional Computing
Luiz André Barroso, Urs Hölzle · Computer · 2007 · 2.5K citations
Anton Beloglazov, Rajkumar Buyya · Concurrency and Computation Practice and Experience · 2011 · 1.8K citations