A Study on Load Balancing Techniques for Task Allocation in Big Data Processing

被引：0
|
作者：
Jin Xiaohong [1 ]
Li Hui [1 ]
Liu Yanjun [1 ]
Fan Yanfang [1 ]
机构：
[1] Beijing Inst Sci & Technol Informat, Beijing 100048, Peoples R China
来源：
PROCEEDINGS OF THE 2016 INTERNATIONAL FORUM ON MECHANICAL, CONTROL AND AUTOMATION (IFMCA 2016) | 2017年 / 113卷
关键词：
Big Data; Job Schedule; Distributed Computing; Clustering; Load Balancing;
D O I：
暂无
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
This paper introduces the task allocation techniques with clustering and load balancing in the field of Internet to the field of image processing job allocation of alternative big data. It designs and realizes a load balancing cluster architecture for the alternative big data, and an improved load balancing algorithm applicable to large-scale image processing. The experimental results show that the cluster architecture can execute task allocation and data processing continuously and stably, and the improved load balancing algorithm could improve the processing efficiency about 10% and more.
引用
收藏
页码：212 / 218
页数：7
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