• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

A Novel Method for Virtual Machine Placement Based on Euclidean Distance

Vol. 10, No. 7, July 30, 2016
10.3837/tiis.2016.07.003, Download Paper (Free):

Abstract

With the increasing popularization of cloud computing, how to reduce physical energy consumption and increase resource utilization while maintaining system performance has become a research hotspot of virtual machine deployment in cloud platform. Although some related researches have been reported to solve this problem, most of them used the traditional heuristic algorithm based on greedy algorithm and only considered effect of single-dimensional resource (CPU or Memory) on energy consumption. With considerations to multi-dimensional resource utilization, this paper analyzed impact of multi-dimensional resources on energy consumption of cloud computation. A multi-dimensional resource constraint that could maintain normal system operation was proposed. Later, a novel virtual machine deployment method (NVMDM) based on improved particle swarm optimization (IPSO) and Euclidean distance was put forward. It deals with problems like how to generate the initial particle swarm through the improved first-fit algorithm based on resource constraint (IFFABRC), how to define measure standard of credibility of individual and global optimal solutions of particles by combining with Bayesian transform, and how to define fitness function of particle swarm according to the multi-dimensional resource constraint relationship. The proposed NVMDM was proved superior to existing heuristic algorithm in developing performances of physical machines. It could improve utilization of CPU, memory, disk and bandwidth effectively and control task execution time of users within the range of resource constraint.


Statistics

Show / Hide Statistics

Statistics (Cumulative Counts from December 1st, 2015)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article

[IEEE Style]
S. Liu and W. Jia, "A Novel Method for Virtual Machine Placement Based on Euclidean Distance," KSII Transactions on Internet and Information Systems, vol. 10, no. 7, pp. 2914-2935, 2016. DOI: 10.3837/tiis.2016.07.003.

[ACM Style]
Shukun Liu and Weijia Jia. 2016. A Novel Method for Virtual Machine Placement Based on Euclidean Distance. KSII Transactions on Internet and Information Systems, 10, 7, (2016), 2914-2935. DOI: 10.3837/tiis.2016.07.003.