A Load Balancing Method For Massive Data Processing Under Cloud Computing Environment. Issue 4 (2nd October 2017)

• Record Type: Journal Article
• Authors: Peng, Jianhua; Tang, Ming; Li, Ming; Zha, Zhiqin
• Is Part Of: Intelligent automation & soft computing. Volume 23:Issue 4(2017)
• Page Start: 547
• Page End: 553
• Publication Date: 2017-10-02
• Subjects: Relatively free rate -- load balancing -- cloud computing -- data processing efficiency; Artificial intelligence -- Periodicals; Intelligent control systems -- Periodicals; 003.5
• DOI: 10.1080/10798587.2017.1316072
• Languages: English
• ISSNs: 1079-8587

Abstract

Abstract: High processing efficiency and equalization are needed when a cloud computing system is used to deal with massive data. Better load balancing methods can further improve the data processing ability of the cloud computing system. In this paper, we first defined the data process efficiency (DPE) and relatively free rate (RFR). Then based on the DPE and RFR, we proposed a load balancing method for massive data (LBMM). And we further described the flow of the LBMM method. Finally, we compared the LBMM method and the consistent hashing method through experiments. The experimental results showed that the LBMM method had better data processing equalization and higher data processing efficiency.