Lifetime Optimization by Load-Balanced and Energy Efficient Tree in Wireless Sensor Networks

  • Authors:

  • Junhong Ye;Kai Peng;Chonggang Wang;Yake Wang;Liang Zhang;Xiaoqiang Ma;Hongbo Jiang

  • Affiliations:

  • Department of Electronics and Information Engineering, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China 430074;Department of Electronics and Information Engineering, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China 430074;InterDigital Communications Corp., King of Prussia, USA;Department of Electronics and Information Engineering, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China 430074;Department of Electronics and Information Engineering, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China 430074;Department of Electronics and Information Engineering, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China 430074;Department of Electronics and Information Engineering, Wuhan National Laboratory for Optoelectronics, Huazhong University of Science and Technology, Wuhan, China 430074

  • Venue:
  • Mobile Networks and Applications
  • Year:
  • 2013

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Abstract

Wireless sensor networks (WSNs), often composed of a large number of sensor nodes with limited power, have been widely used for environmental monitoring and battlefield surveillance. A basic operation in such networks is data gathering. In the applications of data gathering without aggregation, the 1-hop nodes always incur much heavier traffic load compared with other nodes, which determine the lifetime of the whole network. Due to the energy constrained nature of sensor devices, energy-efficient methods should be employed for data gathering. In this paper, we propose a Load-Balanced and energy-efficient Tree (LBT) algorithm to maximize the lifetime of WSNs, which takes into account the load balance and energy efficiency of 1-hop nodes. To the best of our knowledge, we are the first to present the upper bound of network lifetime for data gathering without aggregation with tree-based topology. Simulation results demonstrate that our algorithm utilizes up to 98 % of the total energy of the 1-hop nodes and outperforms the state-of-the-art algorithms in terms of network lifetime. Furthermore, LBT can achieve a lifetime consistently close to the upper bound.