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BioMed Research International
Volume 2018, Article ID 7501042, 17 pages
https://doi.org/10.1155/2018/7501042
Research Article

Parallel MapReduce: Maximizing Cloud Resource Utilization and Performance Improvement Using Parallel Execution Strategies

1Department of Smart Computing, Kyungdong University, Global Campus, 46 4-gil, Gosung, Gangwondo 24764, Republic of Korea
2Faculty of Computer and Information Technology, Al-Madinah International University, 2 Jalan Tengku Ampuan Zabedah E/9E, 40100 Shah Alam, Selangor, Malaysia
3Department of Computer & Information Engineering, Dongseo University, 47 Jurye-ro, Sasang-gu, Busan 47011, Republic of Korea

Correspondence should be addressed to Dae-Ki Kang; rk.ca.oesgnod@gnakkd

Received 12 April 2018; Accepted 30 September 2018; Published 17 October 2018

Academic Editor: Gerald J. Wyckoff

Copyright © 2018 Ahmed Abdulhakim Al-Absi 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.

How to Cite this Article

Ahmed Abdulhakim Al-Absi, Najeeb Abbas Al-Sammarraie, Wael Mohamed Shaher Yafooz, and Dae-Ki Kang, “Parallel MapReduce: Maximizing Cloud Resource Utilization and Performance Improvement Using Parallel Execution Strategies,” BioMed Research International, vol. 2018, Article ID 7501042, 17 pages, 2018. https://doi.org/10.1155/2018/7501042.