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Journal of Applied Mathematics
Volume 2014, Article ID 170723, 10 pages
Research Article

REST-MapReduce: An Integrated Interface but Differentiated Service

1Department of Computer Engineering, Seoul National University of Science and Technology, 232 Gongneung-ro, Nowon-gu, Seoul 139-743, Republic of Korea
2Humanitas College, Kyunghee University, No. 26, Kyunghee-daero, Dongdaemun-gu, Seoul 130-701, Republic of Korea
3Department of Multimedia Engineering, Dongguk University, 30 Pildong-ro 1 Gil, Jung-gu, Seoul 100-715, Republic of Korea
4Department of Information and Communication Engineering, Chungbuk National University, 52 Naesudong-ro, Heungdeok-gu, Chungbuk, Cheongju 361-763, Republic of Korea

Received 16 March 2014; Accepted 3 April 2014; Published 11 June 2014

Academic Editor: Laurence T. Yang

Copyright © 2014 Jong-Hyuk Park et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


With the fast deployment of cloud computing, MapReduce architectures are becoming the major technologies for mobile cloud computing. The concept of MapReduce was first introduced as a novel programming model and implementation for a large set of computing devices. In this research, we propose a novel concept of REST-MapReduce, enabling users to use only the REST interface without using the MapReduce architecture. This approach provides a higher level of abstraction by integration of the two types of access interface, REST API and MapReduce. The motivation of this research stems from the slower response time for accessing simple RDBMS on Hadoop than direct access to RDMBS. This is because there is overhead to job scheduling, initiating, starting, tracking, and management during MapReduce-based parallel execution. Therefore, we provide a good performance for REST Open API service and for MapReduce, respectively. This is very useful for constructing REST Open API services on Hadoop hosting services, for example, Amazon AWS (Macdonald, 2005) or IBM Smart Cloud. For evaluating performance of our REST-MapReduce framework, we conducted experiments with Jersey REST web server and Hadoop. Experimental result shows that our approach outperforms conventional approaches.