Name
Abstract | ||
|---|---|---|
Virtual machine (VM) migration enables flexible and efficient resource management in modern data centers. Although various VM migration algorithms have been proposed to improve the utilization of physical resources in data centers, they generally focus on how to select VMs to be migrated only according to their resource requirements and ignore the relationship between the VMs and servers with respect to their varying resource usage as well as the time at which the VMs should be migrated. This may dramatically degrade the algorithm performance and increase the operating and the capital cost when the resource requirements of the VMs change dynamically over time. In this paper, we propose an integrated VM migration strategy to jointly consider and address these issues. First, we establish a service level agreement-based soft migration mechanism to significantly reduce the number of VM migrations. Then, we develop two algorithms to solve the VM and server selection issues, in which the correlation between the VMs and the servers is used to identify the appropriate VMs to be migrated and the destination servers for them. The experimental results obtained from extensive simulations show the effectiveness of the proposed algorithms compared to traditional schemes in terms of the rate of resource usage, the operating cost and the capital cost. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/s11107-015-0539-6 | Photonic Network Communications |
Keywords | Field | DocType |
Data center,Virtual machine migration,SLA,Correlation,Migration soft triggering | Resource management,Virtual machine,Capital cost,Computer science,Server,Service-level agreement,Computer network,Data center,Operating cost,Cloud computing,Distributed computing | Journal |
Volume | Issue | ISSN |
31 | 2 | 1572-8188(Series Online ISSN)1387-974X(Series Print ISSN) |
Citations | PageRank | References |
2 | 0.38 | 11 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Liu Liu | 1 | 14 | 2.01 |
| Shaoping Zheng | 2 | 2 | 0.38 |
| Hongfang Yu | 3 | 679 | 62.42 |
| Vishal Anand | 4 | 431 | 32.49 |
| Du Xu | 5 | 16 | 4.03 |