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Energy-aware self-organisation algorithms with heterogeneous connectivity in wireless sensor networks

Author

Listed:
  • Xiaojuan Luo
  • Huiqun Yu
  • Xiang Wang

Abstract

Heterogeneity of node energy is a common phenomenon in wireless sensor networks. In such node energy heterogeneous sensor network, how to balance the energy consumption is the key problem on extending the lifetime of the sensor network system. An energy-efficient self-organisation algorithm with heterogeneous connectivity based on energy-awareness is proposed. Each sensor node in the network adjusts its own transmission radius based on the local energy information during the constructing and operating phase. Thus heterogeneous network topology, in which the nodes can choose different transmission radius, is formed. In contrast to the homogeneous network model, in which the node carries the same radius, simulation and analysis are conducted to explore the topology characteristics and robustness with different node energy distribution. The degree distribution shows the scale-free property in the heterogeneous model. The proposed network model enjoys higher efficiency of transmitting data, less clustering, higher robustness under node random failures and longer network lifetime than those in the homogeneous ones.

Suggested Citation

  • Xiaojuan Luo & Huiqun Yu & Xiang Wang, 2013. "Energy-aware self-organisation algorithms with heterogeneous connectivity in wireless sensor networks," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(10), pages 1857-1866.
  • Handle: RePEc:taf:tsysxx:v:44:y:2013:i:10:p:1857-1866
    DOI: 10.1080/00207721.2012.670297
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    Cited by:

    1. Liang, Yuanyuan & Xia, Yongxiang & Yang, Xu-Hua, 2022. "Hybrid-radius spatial network model and its robustness analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 591(C).
    2. Qiang Zhang & Chaojie Zhang & Meiqin Liu & Senlin Zhang, 2015. "Local node selection for target tracking based on underwater wireless sensor networks," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(16), pages 2918-2927, December.

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