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Context-aware scheduling in MapReduce: a compact review
Citation
Idris, M and Hussain, S and Ali, M and Abdulali, A and Siddiqi, MH and Kang, BH, Context-aware scheduling in MapReduce: a compact review, Concurrency and Computation: Practice and Experience, 27, (17) pp. 5332-5349. ISSN 1532-0626 (2015) [Refereed Article]
Copyright Statement
Copyright 2015 John Wiley & Sons, Ltd.
DOI: doi:10.1002/cpe.3578
Abstract
It is a fact that the attention of research community in computer science, business executives, and
decision makers is drastically drawn by big data. As the volume of data becomes bigger, it needs
performance-oriented data-intensive processing frameworks such as MapReduce, which can scale
computation on large commodity clusters. Hadoop MapReduce processes data in Hadoop Distributed
File System as jobs scheduled according to YARN fair scheduler and capacity scheduler. However, with
advancement and dynamic changes in hardware and operating environments, the performance of clusters
is greatly affected. Various efforts in literature have been made to address the issues of heterogeneity (i.e.,
clusters consisting of virtual machines and machines with different hardware), network communication, data
locality, better resource utilization, and run-time scheduling. In this paper, we present a survey to discuss
various research efforts made so far to improve Hadoop MapReduce scheduling. We classify scheduling
algorithms and techniques proposed in the literature so far based on their addressing areas and present a
taxonomy. Furthermore, we also discuss various aspects of open issues and challenges in the scheduling of
MapReduce to improve its performance.
Item Details
Item Type: | Refereed Article |
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Keywords: | scheduling, task scheduling, job scheduling, data-intensive computing, big data, cloud |
Research Division: | Information and Computing Sciences |
Research Group: | Information systems |
Research Field: | Information systems philosophy, research methods and theory |
Objective Division: | Information and Communication Services |
Objective Group: | Information systems, technologies and services |
Objective Field: | Information systems, technologies and services not elsewhere classified |
UTAS Author: | Kang, BH (Professor Byeong Kang) |
ID Code: | 106686 |
Year Published: | 2015 |
Web of Science® Times Cited: | 6 |
Deposited By: | Information and Communication Technology |
Deposited On: | 2016-02-17 |
Last Modified: | 2017-11-20 |
Downloads: | 0 |
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