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Energy-Efficient Tree-Based Multipath Power Control for Underwater Sensor Networks
Nov. 2012 (vol. 23 no. 11)
pp. 2107-2116
Junfeng Xu, Dalian University of Technology, Dalian
Keqiu Li, Dalian University of Technology, Dalian
Geyong Min, Universit of Bradford, Bradford
Kai Lin, Dalian University of Technology, Dalian
Wenyu Qu, Dalian Maritime University, Dalian
Due to the use of acoustic channels with limited available bandwidth, Underwater Sensor Networks (USNs) often suffer from significant performance restrictions such as low reliability, low energy-efficiency, and high end-to-end packet delay. The provisioning of reliable, energy-efficient, and low-delay communication in USNs has become a challenging research issue. In this paper, we take noise attenuation in deep water areas into account and propose a novel layered multipath power control (LMPC) scheme in order to reduce the energy consumption as well as enhance reliable and robust communication in USNs. To this end, we first formalize an optimization problem to manage transmission power and control data rate across the whole network. The objective is to minimize energy consumption and simultaneously guarantee the other performance metrics. After proving that this optimization problem is NP-complete, we solve the key problems of LMPC including establishment of the energy-efficient tree and management of energy distribution and further develop a heuristic algorithm to achieve the feasible solution of the optimization problem. Finally, the extensive simulation experiments are conducted to evaluate the network performance under different working conditions. The results reveal that the proposed LMPC scheme outperforms the existing mechanism significantly.
Index Terms:
Noise,Optimization,Energy consumption,Acoustics,Peer to peer computing,Oceans,Logic gates,optimization,Underwater sensor networks,multipath communication,energy efficiency,packet delay
Citation:
Junfeng Xu, Keqiu Li, Geyong Min, Kai Lin, Wenyu Qu, "Energy-Efficient Tree-Based Multipath Power Control for Underwater Sensor Networks," IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 11, pp. 2107-2116, Nov. 2012, doi:10.1109/TPDS.2012.49
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