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Deyu Lin 1 and Quan Wang 1 and Deqin Lin 2 and Yong Deng 3
Academic Editor:Donatella Darsena
1, School of Computer Science and Technology, Xidian University, No. 2, South Taibai Road, Yanta District, Xi'an, Shannxi 710071, China
2, Faculty of Business, City University of Macau, Macau
3, School of Electro-Mechanical Engineering, Xidian University, No. 2, South Taibai Road, Yanta District, Xi'an, Shannxi 710071, China
Received 2 May 2015; Revised 8 September 2015; Accepted 14 September 2015; 3 November 2015
This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
1. Introduction
Due to the rapid development of the technology of microelectric-mechanical system (MEMS) and the great progress in wireless communication, wireless sensor networks (WSNs) have gained worldwide attention and application. At present, wireless sensor networks are found to be applied in a variety of fields, such as environmental monitoring, habitat monitoring, industrial control, battlefield surveillance [1-4], structural health monitoring [5, 6], infrastructure and facility diagnosis, and other commercial applications [2, 7, 8]. One of the basic functions of WSNs is to report the event data sensed by nodes to the sink for further analysis.
WSNs consist of hundreds or even thousands of communication nodes featuring limited sensing, processing, computing capabilities, and especially constraint energy supply. It is expected to be well functional for several months or even longer according to specific applications. However, the nodes are usually deployed in harsh and inaccessible areas, which makes it impossible or impracticable to recharge energy or replace batteries. Consequently, some nodes run out of energy and network partition emerges. To prolong the lifetime of WSNs as long as possible, great attention should be paid to the energy efficiency. Besides, due to the nonuniform generation of the event data in some applications such as habitat monitoring, the unbalance traffic flows in some network areas, the monitoring of the migration of a herb of animals [2], and so on. Some nodes will use up their energy earlier than expected. This is known as hot spots problem and means the end of life of the network. It will definitely affect the performance of the network. For instance, [1] pointed out...