A LNS-based data placement strategy for data-intensive e-science applications. (1st January 2014)

• Record Type: Journal Article
• Authors: Zhang, Tiantian; Cui, Lizhen; Xu, Meng
• Is Part Of: International journal of grid and utility computing. Volume 5:Number 4(2014)
• Page Start: 249
• Page End: 262
• Publication Date: 2014-01-01
• Subjects: LNS -- large neighbourhood search -- data-intensive -- e-science -- data placement strategy -- big data -- gird computing -- utility computing -- data transfer -- bandwidth cost -- time delay -- overall performance; Electronic data processing -- Distributed processing -- Periodicals; Electronic commerce -- Management -- Computer programs -- Periodicals; 004.605
• Languages: English
• ISSNs: 1741-847X

Abstract

With the growth of data, the era of big data comes. Big data requires a huge amount of storage and new data placement methods. For data-intensive e-science applications in grid and utility computing, they need to process large data sets resided in different data centres. The data transfer across data centres leads to bandwidth cost and time delay. It is more important to solve the data placement problem for these applications. The existing data placement approaches can only reduce the data transfer frequency, but not improve overall performance. In this paper, we propose a data placement strategy based on large neighbourhood search (LNS). The strategy has initial strategy generation stage and relaxation and re-insertion stage. Our strategy offers the improvements in overall performance, especially in reducing time delay.