Hadoop Job Scheduling Based on Hybrid Ant-Genetic Algorithm

被引：1

作者：

Huang, Xiaofei ^{[1
,2
]}

Zhou, Hui ^{[2
]}

Wu, Wei ^{[2
,3
]}

机构：

[1] Hainan Coll Software Technol, Qionghai 571400, Peoples R China

[2] Hainan Univ, Coll Informat Sci & Technol, Haikou 570228, Peoples R China

[3] Chinese Acad Sci, Inst Deep Sea Sci & Engn, Sanya 572000, Peoples R China

来源：

2015 INTERNATIONAL CONFERENCE ON CYBER-ENABLED DISTRIBUTED COMPUTING AND KNOWLEDGE DISCOVERY | 2015年

关键词：

Ant Algorithm; Genetic Algorithm; Hadoop job scheduling; optimization;

D O I：

10.1109/CyberC.2015.48

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Massive job scheduling problem is an important research area in big data research era. This paper proposed self-adaptive job scheduling mechanism based on Ant-Genetic Algorithm aiming at improving convergence speed and accuracy by mutation strategy based on Ant Algorithm and efficient refinement within Genetic Algorithm. The experimental results show that the proposed algorithm can find the most suitable nodes for current jobs and improve efficiency of job scheduling on Hadoop clusters effectively.

引用

页码：226 / 229

页数：4

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