A Survey on Data Placement in Heterogeneous Cloud Environment for Big Data

  Shah Dhairya Vipulkumar,  Hinal Somani

Big-Data is a term for data sets that are so large or complex that traditional data processing tools are inadequate to process or manage them. Apache Hadoop is an open-source software framework for distibuted storage and distributed processing of very large data sets on computer clusters built from commodity hardware. The core of Apache Hadoop consists of a storage part, known as Hadoop Distributed File System(HDFS), and a processing part called MapReduce. The default Hadoop data placement strategy is suitable for homogeneous environment. But it doesn’t cater well to the need for heterogeneous data intensive computing in cloud clusters. There are various data placement schemes available for heterogeneous Hadoop clusters, but each of them have their own advantages and disadvantages. This survey paper studies some of the novel data placement strategies which can be applied in heterogeneous cloud environment to speed up big data processing by enhancing the response times.

Keywords- Big Data, Cloud Computing, Data Placement, Data-Locality, Hadoop, MapReduce.

Unique Identification Number - IJEDR1604085
Page Number(s) - 583-588
Pubished in - Volume 4 | Issue 4 | November 2016
DOI (Digital Object Identifier) -   
Publisher - IJEDR (ISSN - 2321-9939)

  Shah Dhairya Vipulkumar,  Hinal Somani,   "A Survey on Data Placement in Heterogeneous Cloud Environment for Big Data", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.4, Issue 4, pp.583-588, November 2016, Available at :http://www.ijedr.org/papers/IJEDR1604085.pdf