Variable-sized map and locality-aware reduce on public-resource grids

Yen Liang Su, Po Cheng Chen, Jyh Biau Chang, Ce Kuen Shieh

研究成果: Article同行評審

11 引文 斯高帕斯(Scopus)

摘要

This paper presents a grid-enabled MapReduce framework called "Ussop". Ussop provides its users with a set of C-language based MapReduce APIs and an efficient runtime system for exploiting the computing resources available on public-resource grids. Considering the volatility nature of the grid environment, Ussop introduces two novel task scheduling algorithms, namely, Variable-Sized Map Scheduling (VSMS) and Locality-Aware Reduce Scheduling (LARS). VSMS dynamically adjusts the size of map tasks according to the computing power of grid nodes. Moreover, LARS minimizes the data transfer cost of exchanging the intermediate data over a wide-area network. The experimental results indicate that both VSMS and LARS achieved superior performance than the conventional scheduling algorithms.

原文English
頁(從 - 到)843-849
頁數7
期刊Future Generation Computer Systems
27
發行號6
DOIs
出版狀態Published - 2011 六月

All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

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