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An Efficient Resource Aware Scheduling Algorithm for Mapreduce Clusters

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  • Sharmilarani D
  • Vinothini K
  • Ramya V
  • Shobika R

Abstract

MapReduce has become a popular model for data-intensive computation in recent years. The schedulers are critical in enhancing the performance of MapReduce/Hadoop in presence of multiple jobs with different characteristics and performance goals. The propose improve the resource aware scheduling technique for Hadoop map-reduce multiple jobs running that aims to improving resource utilization across multiple virtual machines while observing completion time goals. The propose algorithm influences job profiling information to dynamically adjust the number of slots allocation based on job profile and resource utilization on each machine, as well as workload placement across them, to maximize the resource utilization of the cluster. This single node experimental result show the resource aware scheduling that improves job running time and reduce the resource utilization without introducing stragglers.

Suggested Citation

  • Sharmilarani D & Vinothini K & Ramya V & Shobika R, 2017. "An Efficient Resource Aware Scheduling Algorithm for Mapreduce Clusters," International Journal of Scientific Research in Computer Science, Engineering and Information Technology, International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 2(2), pages 517-523, April.
    • Handle: RePEc:jbh:ijsrcs:v2:y2017:i2:id:hcseit1722182
    Note: Article URL: https://ijsrcseit.com/CSEIT1722182
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