M. Ehsan, Yao Chen, Hui Kang, R. Sion, Jennifer L. Wong
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LiPS: A cost-efficient data and task co-scheduler for MapReduce
We introduce LiPS, a new cost-efficient data and task co-scheduler for MapReduce in a cloud environment. By using linear programming to simultaneously co-schedule data and tasks, LiPS helps to achieve minimized dollar cost globally. We evaluated LiPS both analytically and on Amazon EC2 in order to measure actual dollar charges. The results were significant; LiPS saved 62-81% of the dollar costs when compared with the Hadoop default scheduler and the delay scheduler, while also allowing users to fine-tune the cost-performance tradeoff.
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