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S<SUP align='right'>3R: storage-sensitive services redeployment in the cloud

Authors :
Huaimin Wang
Haibo Mi
Bo Ding
Huining Yan
Yiming Zhang
Source :
International Journal of Big Data Intelligence. 4:250
Publication Year :
2017
Publisher :
Inderscience Publishers, 2017.

Abstract

Services redeployment is one of the critical techniques for energy-efficiency in cloud data centres. In recent years, cloud providers have been providing local storage for cloud services, since it offers a better performance with identified price. Nevertheless, most existing work did not consider the problems introduced by utilising local storage, e.g., migrating much more data, and therefore consuming much more migration time and network bandwidth. Meanwhile, instance migration is a costly operation, the number of migrated instances must be considered. However, the data size and the number of instances on servers are not often accordant, and therefore a tradeoff should be made. To address this problem, this paper proposes S3R, a storage-sensitive services redeployment approach. S3R firstly builds a tradeoff model to estimate the release cost for each server, and then adopts a FFD-based heuristic algorithm to migrate/redeploy instances. Evaluation results on production traces demonstrate the effectiveness of S3R.

Details

ISSN :
20531397 and 20531389
Volume :
4
Database :
OpenAIRE
Journal :
International Journal of Big Data Intelligence
Accession number :
edsair.doi.dedup.....0fb269658bbd8dc5be8570f3dd0564ee