Coverage analysis and a new metaheuristic approach using the Elfes Probabilistic detection model in Wireless sensor networks

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Ali N. H., Özdağ R.

MEASUREMENT, vol.200, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 200
  • Publication Date: 2022
  • Doi Number: 10.1016/j.measurement.2022.111627
  • Journal Name: MEASUREMENT
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, INSPEC
  • Keywords: Area Coverage Problem, Electromagnetism-Like Algorithm, Elfes Probabilistic Detection Model, Sensor Dynamic Deployment, Threshold Detection Probability, Wireless Sensor Networks, DYNAMIC DEPLOYMENT, OPTIMIZATION, ALGORITHM
  • Van Yüzüncü Yıl University Affiliated: Yes

Abstract

The dynamic deployment of sensors in AoI (Area of Interest) plays an important role in ensuring the quality of services (QoS) of Wireless Sensor Networks (WSNs) by optimising the coverage and lifetime of the network. In this paper, a new dynamic deployment approach using metaheuristics based on Electromagnetism-Like (EM-L) algorithm and Elfes Probabilistic Detection Model (EPDM) was proposed to optimise the coverage of WSNs based on the sensor coverage problem, and coverage analysis of AoI was performed. A variable threshold detection probability (TDP) was defined instead of defining a fixed TDP as in the literature. Thus, a more realistic modelling environment was created by considering the signal-to-noise ratio (SNR) in the coverage calculation. The simulation results show that the sensors are always effectively deployed in different scenarios with variable TDPs by the proposed approach compared to a random distribution.