WSN coverage optimization based on Improved Firefly Algorithm
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1.College of Civil Engineering, Xi'an University of Architecture and Technology,Xi’an Shaanxi 710055,China;2.College of Information and Control Engineering, Xi'an University of Architecture and Technology,Xi’an Shaanxi 710055,China;3.College of Building Equipment Science and Engineering, Xi'an University of Architecture and Technology,Xi’an Shaanxi 710055,China

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    Abstract:

    Aiming at the problem of low network coverage caused by uneven deployment and distribution of Wireless Sensor Network nodes, with the goal of maximizing wireless sensor network coverage, a network coverage optimization strategy based on Improved Firefly Algorithm(IFA) is proposed. This method uses the good point set method to initialize the population, improve the diversity of the population and lay the foundation for the global search. Simultaneously, it uses the sigmoid function with non-linear exponential decline as the inertia weight to balance the global and local search capabilities of the algorithm. Then, Gaussian disturbance strategy is employed to perturb individual position update and avoid the premature of the algorithm. The simulation results indicate that compared with Artificial Fish Swarm Algorithm(AFSA), seed Hybrid Particle Swarm Optimization(HSPSO) and Chaotic Glowworm Swarm Optimization(CGSO), this algorithm effectively enhance the network coverage rate and make the WSN more evenly distributed.

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董振平,陈亚州,于军琪,隋龑.基于改进萤火虫算法的WSN覆盖优化[J]. Journal of Terahertz Science and Electronic Information Technology ,2023,21(2):225~234

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History
  • Received:January 20,2020
  • Revised:December 21,2020
  • Adopted:
  • Online: March 06,2023
  • Published: