Name
Title | ||
|---|---|---|
Energy Efficient Resource Selection And Allocation Strategy For Virtual Machine Consolidation In Cloud Datacenters |
Abstract | ||
|---|---|---|
Virtual Machine Placement (VMP) plays an important role in ensuring efficient resource provisioning of physical machines (PMs) and energy efficiency in Infrastructure as a Service (IaaS) data centers. Efficient server consolidation assisted by virtual machine (VM) migration can promote the utilization level of the servers and switch the idle PMs to sleep mode to save energy. The trade-off between energy and performance is difficult, because consolidation may cause performance degradation, even service level agreement (SLA) violations. A novel residual available capacity (RAC) resource model is proposed to resolve the VM selection and allocation problem from the cloud service provider (CSP) perspective. Furthermore, a novel heuristic VM selection policy for server consolidation, named Minimized Square Root available Resource (MISR) is proposed. Meanwhile, an efficient VM allocation policy, named Balanced Selection (BS) based on RAC is proposed. The effectiveness validation of the BS-MISR combination is conducted on CloudSim with real workloads from the CoMon project. Evaluation results of experiments show that the proposed combination BS-MISR can significantly reduce the energy consumption, with an average of 36.35% compared to the Local Regression and Minimum Migration Time (LR-MMT) combination policy. Moreover, the BS-MISR ensures a reasonable level of SLAs compared to the benchmarks. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1587/transinf.2017EDP7321 | IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS |
Keywords | Field | DocType |
residual available capacity model, server consolidation, virtual machine migration, energy consumption, cloud computing | Computer vision,Efficient energy use,Computer science,Virtual machine consolidation,Artificial intelligence,Energy consumption,Cloud computing,Distributed computing | Journal |
Volume | Issue | ISSN |
E101D | 7 | 1745-1361 |
Citations | PageRank | References |
2 | 0.37 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yaohui Chang | 1 | 2 | 0.37 |
| Chunhua Gu | 2 | 5 | 3.10 |
| Fei Luo | 3 | 8 | 4.53 |
| Guisheng Fan | 4 | 91 | 25.45 |
| Wenhao Fu | 5 | 2 | 0.37 |