% This data is distributed under the terms of the Open Data Commons Attribution License (ODC-By) v1.0 - See more at: http://opendatacommons.org/licenses/by/1-0/ @Article{OJBD_2015v1i1n02_Teli, title = {An Efficient Approach for Cost Optimization of the Movement of Big Data}, author = {Prasad Teli and Manoj V. Thomas and K. Chandrasekaran}, journal = {Open Journal of Big Data (OJBD)}, issn = {2365-029X}, year = {2015}, volume = {1}, number = {1}, pages = {4--15}, url = {http://nbn-resolving.de/urn:nbn:de:101:1-201705194335}, urn = {urn:nbn:de:101:1-201705194335}, publisher = {RonPub}, bibsource = {RonPub}, abstract = {With the emergence of cloud computing, Big Data has caught the attention of many researchers in the area of cloud computing. As the Volume, Velocity and Variety (3 Vs) of big data are growing exponentially, dealing with them is a big challenge, especially in the cloud environment. Looking at the current trend of the IT sector, cloud computing is mainly used by the service providers to host their applications. A lot of research has been done to improve the network utilization of WAN (Wide Area Network) and it has achieved considerable success over the traditional LAN (Local Area Network) techniques. While dealing with this issue, the major questions of data movement such as from where to where this big data will be moved and also how the data will be moved, have been overlooked. As various applications generating the big data are hosted in geographically distributed data centers, they individually collect large volume of data in the form of application data as well as the logs. This paper mainly focuses on the challenge of moving big data from one data center to other. We provide an efficient algorithm for the optimization of cost in the movement of the big data from one data center to another for offline environment. This approach uses the graph model for data centers in the cloud and results show that the adopted mechanism provides a better solution to minimize the cost for data movement.} }