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Chuanqing Chen 1 and Li Feng 2 and Xin Gu 1 and Jiguo Yu 1 and Dongxiao Yu 3 and Baogui Huang 1
Academic Editor:Houbing Song
1, School of Information Science and Engineering, Qufu Normal University, Rizhao, Shandong 276826, China
2, Faculty of Information Technology, Macau University of Science and Technology, Macau, China
3, Department of Computer Science, The University of Hong Kong, Pokfulam, Hong Kong
Received 6 October 2014; Revised 10 January 2015; Accepted 11 January 2015; 30 August 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
A wireless sensor network (WSN) consists of plentiful low-power sensor nodes capable of sensing, processing, and communicating. These sensor nodes observe the environment phenomenon at different points in the field, collaborate with each other, and send the monitored data to the base station (BS). As sensor networks have limited and nonrechargeable energy resources, energy efficiency is a very important issue in designing the network topology, which affects the lifetime of WSNs greatly. Thus, how to minimize energy consumption and maximize network lifetime are the central concerns when designing protocols for WSNs.
In recent years, clustering has been proved to be an important way to decrease the energy consumption and extend lifetime of WSNs. In clustering scheme, sensor nodes are grouped into clusters, in each cluster, a node is selected as the leader named as the cluster head (CH) and the other nodes are called cluster members (CMs). Each CM measures physical variables related to its environment and then sends them to their CHs. When the data from all CMs arrive, CHs aggregate data and send it to the BS. Since CHs are responsible for receiving and aggregating data from their CMs and then transmitting the aggregated data to the specified destination, the energy consumption of which is much higher than that of CMs. To solve this problem, most clustering algorithms divide the operation into rounds and periodically rotate the roles of CHs in the network to balance the unequal energy consumption among nodes. However, there exists another problem; that is, energy consumption among CHs is also imbalanced due to the distance to...