Classification framework of MapReduce scheduling algorithms

Nidhi Tiwari, Santonu Sarkar, Umesh Bellur, Maria T Indrawan-Santiago

    Research output: Contribution to journalArticleResearchpeer-review

    47 Citations (Scopus)

    Abstract

    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.
    Original languageEnglish
    Pages (from-to)1 - 38
    Number of pages38
    JournalACM Computing Surveys
    Volume47
    Issue number3
    DOIs
    Publication statusPublished - 2015

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