Title

A Reliable Power Management Scheme For Consistent Hashing Based Distributed Key Value Storage Systems

Keywords

Consistent hash table (CHT); Key value storage system; Power management; Reliability; Replication

Abstract

Distributed key value storage systems are among the most important types of distributed storage systems currently deployed in data centers. Nowadays, enterprise data centers are facing growing pressure in reducing their power consumption. In this paper, we propose GreenCHT, a reliable power management scheme for consistent hashing based distributed key value storage systems. It consists of a multi-tier replication scheme, a reliable distributed log store, and a predictive power mode scheduler (PMS). Instead of randomly placing replicas of each object on a number of nodes in the consistent hash ring, we arrange the replicas of objects on nonoverlapping tiers of nodes in the ring. This allows the system to fall in various power modes by powering down subsets of servers while not violating data availability. The predictive PMS predicts workloads and adapts to load fluctuation. It cooperates with the multi-tier replication strategy to provide power proportionality for the system. To ensure that the reliability of the system is maintained when replicas are powered down, we distribute the writes to standby replicas to active servers, which ensures failure tolerance of the system. GreenCHT is implemented based on Sheepdog, a distributed key value storage system that uses consistent hashing as an underlying distributed hash table. By replaying 12 typical real workload traces collected from Microsoft, the evaluation results show that GreenCHT can provide significant power savings while maintaining a desired performance. We observe that GreenCHT can reduce power consumption by up to 35%–61%.

Publication Date

10-1-2016

Publication Title

Frontiers of Information Technology and Electronic Engineering

Volume

17

Issue

10

Number of Pages

994-1007

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1631/FITEE.1601162

Socpus ID

84991396668 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84991396668

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