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Volume 2 Issue 3
Jul.  2015

IEEE/CAA Journal of Automatica Sinica

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Article Navigation >  IEEE/CAA Journal of Automatica Sinica  > 2015  >  2(3): 267-273
Zhixin Liu, Yazhou Yuan, Xinping Guan and Xinbin Li, "An Approach of Distributed Joint Optimization for Cluster-based Wireless Sensor Networks," IEEE/CAA J. of Autom. Sinica, vol. 2, no. 3, pp. 267-273, 2015.
Citation: Zhixin Liu, Yazhou Yuan, Xinping Guan and Xinbin Li, "An Approach of Distributed Joint Optimization for Cluster-based Wireless Sensor Networks," IEEE/CAA J. of Autom. Sinica, vol. 2, no. 3, pp. 267-273, 2015.
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An Approach of Distributed Joint Optimization for Cluster-based Wireless Sensor Networks

  • 1. Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China;

  • 2. School of Electronic, Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;

  • 3. Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China;

  • 4. School of Electronic, Information and Electrical Engineering, Shanghai Jiao Tong University, Shanghai 200240, China;

  • 5. Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China

Funds:

This work was supported partly by National Natural Science Foundation of China (61473247, 61104033, 61172095) and Hebei Provincial Natural Science Fund (F2012203109).

    Abstract
  • Wireless sensor networks (WSNs) are energyconstrained, so energy saving is one of the most important issues in typical applications. The clustered WSN topology is considered in this paper. To achieve the balance of energy consumption and utility of network resources, we explicitly model and factor the effect of power and rate. A novel joint optimization model is proposed with the protection for cluster head. By the mean of a choice of two appropriate sub-utility functions, the distributed iterative algorithm is obtained. The convergence of the proposed iterative algorithm is proved analytically. We consider general dual decomposition method to realize variable separation and distributed computation, which is practical in large-scale sensor networks. Numerical results show that the proposed joint optimal algorithm converges to the optimal power allocation and rate transmission, and validate the performance in terms of prolonging of network lifetime and improvement of throughput.

     

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