Title
Context-aware task allocation for fast parallel big data processing in optical-wireless networks
Abstract
MapReduce architecture has been considered as one of the most promising candidates for efficient and reliable big data mining. While current MapReduce is basically designed for data center and enterprise networks, in which a number of servers are interconnected with optical fiber cables, prospective MapReduce would be applied in optical-wireless environment such as optical-wireless data center network, fiber-wireless (FiWi) access network, and so forth. To modify MapReduce for opticalwireless hybrid network, we need to answer the fundamental research problem, “How does MapReduce architecture use optical and wireless resources for task allocation?” To answer this question, this paper reveals some challenging issues and proposes a context-aware task allocation scheme that is designed by considering characteristics of both optical and wireless communications. Our proposed task allocation scheme can minimize the completion time of big data processing. Numerical results are presented to demonstrate the effectiveness of our proposed method compared with existing task allocation schemes.
Year
DOI
Venue
2014
10.1109/IWCMC.2014.6906394
Wireless Communications and Mobile Computing Conference
Keywords
DocType
ISSN
computer centres,computer networks,data mining,optical cables,optical fibre networks,radio access networks,resource allocation,ubiquitous computing,FiWi access network,MapReduce architecture,context-aware task allocation scheme,data mining,data processing,enterprise networks,fiber-wireless access network,optical communications,optical fiber cables,optical resources,optical-wireless data center network,optical-wireless environment,optical-wireless hybrid network,wireless communications,wireless resources,Context-aware task allocation,MapReduce,minimizing completion time,optical-wireless network
Conference
2376-6492
Citations 
PageRank 
References 
0
0.34
0
Authors
3
Name
Order
Citations
PageRank
Katsuya Suto112211.03
Hiroki Nishiyama2128592.61
Nei Kato33982263.66