The Community for Technology Leaders
Green Image
Issue No. 03 - March (2012 vol. 23)
ISSN: 1045-9219
pp: 444-451
Yichao Jin , Univeristy of Surrey, Guildford
Jiong Jin , The University of Melbourne, Parkville
Alexander Gluhak , Univeristy of Surrey, Guildford
Klaus Moessner , Univeristy of Surrey, Guildford
Marimuthu Palaniswami , The University of Melbourne, Parkville
Emerging applications in Multihop Wireless Networks (MHWNs) require considerable processing power which often may be beyond the capability of individual nodes. Parallel processing provides a promising solution, which partitions a program into multiple small tasks and executes each task concurrently on independent nodes. However, multihop wireless communication is inevitable in such networks and it could have an adverse effect on distributed processing. In this paper, an adaptive intelligent task mapping together with a scheduling scheme based on a genetic algorithm is proposed to provide real-time guarantees. This solution enables efficient parallel processing in a way that only possible node collaborations with cost-effective communications are considered. Furthermore, in order to alleviate the power scarcity of MHWN, a hybrid fitness function is derived and embedded in the algorithm to extend the overall network lifetime via workload balancing among the collaborative nodes, while still ensuring the arbitrary application deadlines. Simulation results show significant performance improvement in various testing environments over existing mechanisms.
Multihop wireless network, task allocation and scheduling, genetic algorithm.

Y. Jin, A. Gluhak, J. Jin, M. Palaniswami and K. Moessner, "An Intelligent Task Allocation Scheme for Multihop Wireless Networks," in IEEE Transactions on Parallel & Distributed Systems, vol. 23, no. , pp. 444-451, 2011.
88 ms
(Ver 3.3 (11022016))