Tees: A Novel Multiple Criteria Optimization Scheme For Temperature-Constrained Energy Efficient Storage

Keywords

Energy-efficient storage; Fuzzy control; Temperature-constrained

Abstract

Existing energy saving schemes that have been developed for Energy Efficient Storage funnel I/O traffic on a few disks while allowing the rest idle. These schemes can cause long standing disks to overburden, resulting in a higher rate of disk failure and reliability degradation. In this paper, we develop a novel multiple criteria optimization scheme based on Fuzzy Decision Making theory, for the Temperature-constrained Energy Efficient Storage System called TEES. TEES aims to enforce a temperature constraint as well as performance requirements while also keeping energy consumption to a minimum. This is achieved by developing an online temperature prediction model and aggregating all the decision criteria, such as I/O performance, power consumption, estimated temperature and frequency of disk-status transition. The experimental results show that TEES is able to reduce disk temperature by 20-30% as compared with existing control methods, while obtaining comparable performance and power consumption.

Publication Date

10-1-2016

Publication Title

Journal of Parallel and Distributed Computing

Volume

96

Number of Pages

152-162

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.jpdc.2016.05.010

Socpus ID

84974794975 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84974794975

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