ITM Web Conf.
Volume 17, 20184th Annual International Conference on Wireless Communication and Sensor Network (WCSN 2017)
|Number of page(s)||6|
|Section||Session 3: Smart City in Resource Management, Ecological and Environmental Data Processing|
|Published online||02 February 2018|
A large data processing algorithm for energy efficiency in a heterogeneous cluster
ICT Department, State Grid Liaoning Electric Power Co., Ltd, Shenyang, China
* Lei Wang: firstname.lastname@example.org
It is reportedi that the electricity cost to operate a cluster may well exceed its acquisition cost, and the processing of big data requires large scale cluster and long period. Therefore, energy efficient processing of big data is essential for the data owners and users. In this paper, we propose a novel algorithm MinBalance to processing I/O intensive big data tasks energy efficiently in heterogeneous cluster. In the former step, four greedy policies are used to select the proper nodes considering heterogeneity of the cluster. While in the latter step, the workloads of the selected nodes will be well balanced to avoid the energy wastes caused by waiting. MinBalance is a universal algorithm and cannot be affected by the data storage strategies. Experimental results indicate that MinBalance can achieve over 60% energy reduction for large sets over the traditional methods of powering down partial nodes.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (http://creativecommons.org/licenses/by/4.0/).
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