A Modified Particle Swarm Optimization Approach for Latency of Wireless Sensor Networks

In time-sensitive applications, such as detecting environmental and individual nuclear radiation exposure, wireless sensor networks are employed.. Such application requires timely detection of radiation levels so that appropriate emergency measures are applied to protect people and the environment from radiation hazards. In these networks, collision and interference in communication between sensor nodes cause more end-to-end delay and reduce the network's performance. A time-division multiple-access (TDMA) media access control protocol guarantees minimum latency and low power consumption. It also overcomes the problem of interference. TDMA scheduling problem determines the minimum length conflict-free assignment of slots in a TDMA frame where each node or link is activated at least once. This paper proposes a meta-heuristic centralized contention-free approach based on TDMA, a modified particle swarm optimization. This approach realizes the TDMA scheduling more efficiently compared with other existing algorithms. Extensive simulations were performed to evaluate the modified approach. The simulation results prove that the proposed scheduling algorithm has a better performance in wireless sensor networks than the interference degree leaves order algorithm and interference degree remaining leaves order algorithm. The results demonstrate also that integrating the proposed algorithm in TDMA protocols significantly optimizes the communication latency reduction and increases the network reliability.

@article{Elrefaei2021,
  title     = {A Modified Particle Swarm Optimization Approach for Latency of Wireless Sensor Networks},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {12},
  number    = {6},
  year      = {2021},
  publisher = {The Science and Information Organization},
  author    = {Jannat H. Elrefaei and Ahmed Yahya and Mouhamed K. Shaat and Ahmed H. Madian and Refaat M. Fikry},
  doi       = {10.14569/IJACSA.2021.0120679},
  url       = {https://doi.org/10.14569/IJACSA.2021.0120679}
}