An advanced load balancing strategy for cloud environment

Jiadong Zhang, Qiongxin Liu, Jiayu Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

The rapid development of cloud computing, bring great convenience to developers. Recently the resource management of the cloud platform has become a hot research topic, especially the load balancing problem in data center is very important for cloud provider. In this paper, a load balancing framework is proposed for cloud platform, it use the threshold window strategy and an advanced AR prediction model to reduce the migration of VMs. Experiments show that this method can effectively achieve load balancing, promote the utilization of the physical machines, and solve the frequent migration problem caused by high instantaneous peak values significantly.

Original languageEnglish
Title of host publicationProceedings - 17th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2016
EditorsHong Shen, Hong Shen, Yingpeng Sang, Hui Tian
PublisherIEEE Computer Society
Pages240-243
Number of pages4
ISBN (Electronic)9781509050819
DOIs
Publication statusPublished - 2 Jul 2016
Event17th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2016 - Guangzhou, China
Duration: 16 Dec 201618 Dec 2016

Publication series

NameParallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings
Volume0

Conference

Conference17th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2016
Country/TerritoryChina
CityGuangzhou
Period16/12/1618/12/16

Keywords

  • Cloud computing
  • Load balancing
  • Threshold window

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