Big Data Migration between Data Centers in Online Cloud Environment. (2016)

• Record Type: Journal Article
• Authors: Teli, Prasad; Thomas, Manoj V.; Chandrasekaran, K.
• Is Part Of: Procedia technology. Volume 24(2016)
• Page Start: 1558
• Page End: 1565
• Publication Date: 2016
• Subjects: big data -- cloud -- data centers -- MapReduce; Technology -- Congresses; Technology -- Periodicals; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Technology; Conference proceedings; Periodicals; 605
• DOI: 10.1016/j.protcy.2016.05.135
• Languages: English
• ISSNs: 2212-0173

Abstract

Abstract: Big data has become one of the major areas of research for cloud service providers. Big data with its characteristics such as size, complexity etc. requires efficient methods for migration from one location to the geographically distant other location. Also, processing the big data located at different geographically distributed data centers using MapReduce like frameworks consume a lot of bandwidth. One of the solutions for reducing the cost of processing such geographically distributed big data is data aggregation. In this paper, we propose an online algorithm to find out optimal cost data aggregation site among the geographically distributed data centers. This proposed approach gives an optimal cost solution for the data aggregation from different geographically distributed data centers which can be efficiently processed at a single site using distributed frameworks. We propose a graph model of Geo-distributed data centers. Results are obtained in the online cloud environment, which show that proposed approach gives better results.