Name
Abstract | ||
|---|---|---|
The energy efficiency of modern data centers has become a practical concern and has attracted significant attention in recent years. In contract to existing solutions that primarily focuses on only one specific aspect of management to reduce energy consumption, this paper explores the balance between server energy consumption and network energy consumption to present an energy-aware joint virtual machine (VM) placement. Given the definition of VM placement fairness, the basic algorithm of VM placement which fulfills server energy consumption constraints is conducted. Then, we further formulate the VM placement as an optimization problem which considers application dependencies to reduce network energy consumption. We design a joint algorithm that efficiently solves the VM placement problem for very large problem sizes. Using simulations, we conduct a comparative analysis on the impact of the data center architectures, server constraints and application dependencies on the potential performance gain of energy-aware VM placement. Compared to existing generic methods, we show a significant performance improvement such as efficiently reducing the number of physical machines used to save server energy consumption, decreasing the communication distance between VMs to obtain data center network energy consumption efficiency, improving scalability of data centers. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/GLOCOM.2012.6503614 | IEEE Global Communications Conference |
Field | DocType | Volume |
Virtual machine,Computer science,Efficient energy use,Computer network,Real-time computing,Data center,Energy consumption,Optimization problem,Performance improvement,Scalability | Conference | null |
Issue | ISSN | Citations |
null | 2334-0983 | 19 |
PageRank | References | Authors |
0.88 | 11 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Daochao Huang | 1 | 69 | 6.47 |
| Dong Yang | 2 | 211 | 20.38 |
| Hongke Zhang | 3 | 1637 | 142.17 |
| Lei Wu | 4 | 669 | 40.02 |