@inproceedings{262749ad3be342099ff7ea888ee3bd09,
title = "Computation capability deduction architecture for MapReduce on cloud computing",
abstract = "MapReduce gradually becomes the de facto programming standard of applications on cloud computing. However, MapReduce needs a cloud administrator to manually configure parameters of the run-time system such as slot numbers for Map and Reduce tasks in order to get the best performance. Because the manual configuration has a risk of performance degradation, MapReduce should utilize the Computation Capability Deduction Architecture (CCDA) proposed in this paper to avoid the risk. MapReduce can use CCDA to help the run-time system to distribute appropriate numbers of tasks over computers in a cloud at run time without any manual configuration made by a cloud administrator. According to experiment observations in this paper, MapReduce can get great performance improvement with the help of CCDA in data-intensive applications such as Inverted Index and Word Count that are usually required to process big data on cloud computing.",
author = "Huang, \{Tzu Chi\} and Chu, \{Kuo Chih\} and Huang, \{Guo Hao\} and Shen, \{Yan Chen\} and Shieh, \{Ce Kuen\}",
note = "Funding Information: ACKNOWLEDGMENT We thank the Taiwan Ministry of Science and Technology for the supports of this research project under grant number MOST 106-2221-E-262-004. Besides, we want to thank Lunghwa University of Science and Technology for providing us with various devices. We further offer our special thanks to the reviewers for their valuable comments and suggestions. Publisher Copyright: {\textcopyright} 2017 IEEE.; 18th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2017 ; Conference date: 18-12-2017 Through 20-12-2017",
year = "2017",
month = jul,
day = "2",
doi = "10.1109/PDCAT.2017.00067",
language = "English",
series = "Parallel and Distributed Computing, Applications and Technologies, PDCAT Proceedings",
publisher = "IEEE Computer Society",
pages = "368--375",
editor = "Shi-Jinn Horng",
booktitle = "Proceedings - 18th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2017",
address = "United States",
}