Classification Framework of MapReduce Scheduling Algorithms
DSpace at IIT Bombay
View Archive InfoField | Value | |
Title |
Classification Framework of MapReduce Scheduling Algorithms
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Creator |
TIWARI, N
SARKAR, S BELLUR, U INDRAWAN, M |
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Subject |
ENVIRONMENTS
MapReduce Scheduling Algorithms Analysis Distributed computing distributed data scheduling MapReduce big-data Hadoop |
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Description |
A MapReduce scheduling algorithm plays a critical role in managing large clusters of hardware nodes and meeting multiple quality requirements by controlling the order and distribution of users, jobs, and tasks execution. A comprehensive and structured survey of the scheduling algorithms proposed so far is presented here using a novel multidimensional classification framework. These dimensions are (i) meeting quality requirements, (ii) scheduling entities, and (iii) adapting to dynamic environments; each dimension has its own taxonomy. An empirical evaluation framework for these algorithms is recommended. This survey identifies various open issues and directions for future research.
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Publisher |
ASSOC COMPUTING MACHINERY
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Date |
2016-01-15T09:56:43Z
2016-01-15T09:56:43Z 2015 |
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Type |
Article
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Identifier |
ACM COMPUTING SURVEYS, 47(3)
0360-0300 1557-7341 http://dx.doi.org/10.1145/2693315 http://dspace.library.iitb.ac.in/jspui/handle/100/18308 |
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Language |
en
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