TY - GEN
T1 - Context-aware task allocation for fast parallel big data processing in optical-wireless networks
AU - Suto, Katsuya
AU - Nishiyama, Hiroki
AU - Kato, Nei
PY - 2014/9/22
Y1 - 2014/9/22
N2 - 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.
AB - 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.
KW - Context-aware task allocation
KW - MapReduce
KW - minimizing completion time
KW - optical-wireless network
UR - http://www.scopus.com/inward/record.url?scp=84908611738&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84908611738&partnerID=8YFLogxK
U2 - 10.1109/IWCMC.2014.6906394
DO - 10.1109/IWCMC.2014.6906394
M3 - Conference contribution
AN - SCOPUS:84908611738
T3 - IWCMC 2014 - 10th International Wireless Communications and Mobile Computing Conference
SP - 423
EP - 428
BT - IWCMC 2014 - 10th International Wireless Communications and Mobile Computing Conference
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th International Wireless Communications and Mobile Computing Conference, IWCMC 2014
Y2 - 4 August 2014 through 8 August 2014
ER -