PAReS: A Proactive and Adaptive Redundant System for MapReduce

Jia Chun Lin, Fang Yie Leu, Ying-Ping Chen

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Recently, MapReduce has been a key and popular technology for tackling data-intensive applications. But its two master servers in current MapReduce implementations have a single-failure problem, which may interrupt MapReduce operations and filesystem services. In this paper, we propose a hybrid takeover scheme, called the Proactive and Adaptive Redundant System (PAReS for short), which employs three service-quality improvement mechanisms, including a proactive synchronization and replication method, a mutual monitoring algorithm, and an adaptive warm-up mechanism, to mitigate the above problems. The extensive experiments show that PAReS enhances service quality at acceptable energy consumption level and synchronization cost as compared with four stateof-the-art schemes.

Original languageEnglish
Pages (from-to)1797-1815
Number of pages19
JournalJournal of Information Science and Engineering
Volume31
Issue number5
DOIs
StatePublished - 1 Sep 2015

Keywords

  • Adaptive warm-up mechanism
  • MapReduce
  • Mutual monitoring
  • Proactive synchronization and replication
  • Redundant System
  • Service downtime
  • Takeover

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