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GLBR: A novel global load balancing routing scheme based on intelligent computing in partially disconnected wireless sensor networks

Author

Listed:
  • Zeyu Sun
  • Guisheng Liao
  • Cao Zeng
  • Lan Lan
  • Guozeng Zhao

Abstract

Load balancing is of great significance to extend the longevity of wireless sensor networks, due to the inherent imbalanced energy overhead in such networks. However, existing solutions cannot balance the load distribution in partially disconnected wireless sensor networks. For example, if a network is partitioned into several segments with different area sizes, some areas have much more traffic load than other areas. In this article, we propose a load-balanced routing scheme, which aims to balance energy consumption within each segment and among different segments. First, we adopt unequal transmission distances to build initial routing for intrasegment load balancing. Second, we adopt the genetic algorithm to build extra routing between different segments for intersegment load balancing. The unique character of our work is twofold. On one hand, we investigate partitioned wireless sensor networks where there are several isolated segments. On the other hand, we pursue load balancing from a global perspective rather than from a local one. Some simulations verify the effectiveness and the advantages of our scheme in terms of extra deployment cost, system longevity, and load balancing degree.

Suggested Citation

  • Zeyu Sun & Guisheng Liao & Cao Zeng & Lan Lan & Guozeng Zhao, 2022. "GLBR: A novel global load balancing routing scheme based on intelligent computing in partially disconnected wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 18(4), pages 15501329221, April.
    • Handle: RePEc:sae:intdis:v:18:y:2022:i:4:p:15501329221090458
    DOI: 10.1177/15501329221090458
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    References listed on IDEAS

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    1. Surjit Singh & Rajeev Mohan Sharma, 2018. "HSCA: a novel harmony search based efficient clustering in heterogeneous WSNs," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 67(4), pages 651-667, April.
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