计算机与现代化

• 算法设计与分析 • 上一篇    下一篇

#br# 基于遗传算法的大数据节能优化模型

  

  1. 国网信通亿力科技有限责任公司,福建福州350001
  • 收稿日期:2016-03-15 出版日期:2016-10-15 发布日期:2016-10-14
  • 作者简介:许元斌(1970-),男,福建龙岩人,国网信通亿力科技有限责任公司经理,高级工程师,硕士,研究方向:计算机技术,电力信息化。

Energysaving Optimization Model Under Big Data Environment #br# Based on Genetic Algorithm

  1. State Grid Info-Telecom Great Power Science and Technology Co., Ltd, Fuzhou 350001, China
  • Received:2016-03-15 Online:2016-10-15 Published:2016-10-14

摘要:
摘要:针对云计算环境下能源消耗严重以及服务器能耗相对较高的问题,本文基于遗传算法提出一种大数据节能优化模型对任务调度进行优化,从而降低服务器能耗,并设计相关的算法对模型进行形式化描述,最后设计相关实验对本文所提算法进行验证。实验结果表明,本文所提出的模型和算法能够有效降低服务器能耗开销,极大地提高系统的资源利用率。

关键词: 大数据, 云计算, MapReduce, 遗传算法, 能耗模型

Abstract: To overcome the problem of the high power consumption of the servers in the cloud computing environment, this paper proposed an energysaving optimization model under big data environment based on genetic algorithm, which optimized the task scheduling to reduce the server power consumption, and then this paper designed some algorithms to formally indicate the model. We test the algorithm in real world, the experiment result shows the proposed model and the algorithms can effectively reduce server power consumption, which improved the system resource utilization.

Key words: big data, cloud computing, MapReduce, GA, energy consumption model

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