Heterogeneity and thermal aware adaptive heuristics for energy efficient consolidation of virtual machines in infrastructure clouds
作者：
Highlights：
• Metrics to classify servers in a heterogeneous cloud environment based on server's power consumption and performance.
• Adaptive heterogeneous and thermal aware heuristic approaches for energy efficient dynamic consolidation of VMs.
• Accounted for server processor sleep states and state transition time latencies in a heterogeneous cloud environment.
• Hybrid heuristics approach, which works with both homogeneous and heterogeneous server cloud.
• Extensive simulation-based evaluation and analysis of the proposed algorithms.
摘要
•Metrics to classify servers in a heterogeneous cloud environment based on server's power consumption and performance.•Adaptive heterogeneous and thermal aware heuristic approaches for energy efficient dynamic consolidation of VMs.•Accounted for server processor sleep states and state transition time latencies in a heterogeneous cloud environment.•Hybrid heuristics approach, which works with both homogeneous and heterogeneous server cloud.•Extensive simulation-based evaluation and analysis of the proposed algorithms.
论文关键词：IaaS Cloud,Data center energy efficiency,Processor SLEEP states,Processor SLEEP state transition latency
论文评审过程：Received 15 February 2015, Revised 6 July 2015, Accepted 15 July 2015, Available online 14 August 2015, Version of Record 27 November 2015.
论文官网地址：https://doi.org/10.1016/j.jcss.2015.07.005
