A Novel Task Scheduling Approach for Reducing Energy Consumption of MapReduce Cluster
Jie Song, Xuebing Liu, Zhiliang Zhu, Dazhe Zhao, Ge Yu · IETE Technical Review · 2014
In recent years, data processing technologies like MapReduce in cloud computing have been widely used. However, the problem of high energy consumption (EC) is an obstacle for further development of cloud computing. We believe that EC could be reduced not only by hardware reinforcement but also by software improvement, especially, by energy-aware task scheduling. In this paper, the Best resources assignment model (Bram) is proposed. On this basis, a scheduling approach, concerning resource usage of nodes and different kinds of resource intensive tasks running on them, is proposed to avoid resource idleness, and then reduce energy consumption. The experimental results show that the new method could reduce the energy consumption of MapReduce cluster.