
Resource over provisioning in cloud computing consumes energy excessively. Energy-aware dynamic virtual machine consolidation (DVMC) reduces energy consumption without compromising service level agreement. In this paper, we put forward a new framework of DVMC for green cloud computing. In particular, we propose a new virtual machine (VM) placement policy, namely, space aware best fit decreasing (SABFD) and a new migration VM selection policy, namely, high CPU utilization-based migration VM selection (called HS). Thorough simulations are carried out to evaluate the performances of different energy-aware DVMC plans based on real-world workload traces, with DVMC plans as various combinations of host overload detection, migration VM selection, and VM placement policies. The simulation results show that DVMC plans with SABFD policy or with HS policy outperforms alternative DVMC plans. What is more, a DVMC plan with both SABFD and HS policies makes the best performance.
General Computer Science, cloud computing, General Engineering, TK1-9971, dynamic virtual machine consolidation, green cloud computing, Cloud computing, virtual machine placement, General Materials Science, SDG 7 - Affordable and Clean Energy, Electrical engineering. Electronics. Nuclear engineering, cloud datacenter
General Computer Science, cloud computing, General Engineering, TK1-9971, dynamic virtual machine consolidation, green cloud computing, Cloud computing, virtual machine placement, General Materials Science, SDG 7 - Affordable and Clean Energy, Electrical engineering. Electronics. Nuclear engineering, cloud datacenter
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 84 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 1% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 1% |
