Optimization of Sensor Deployment for k-coverage in Wireless Sensor Networks

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Özdağ R., Canayaz M.

International Conference on Advanced Technologies, Computer Engineering and Science (ICATCES’18), Karabük, Turkey, 11 - 13 May 2018, pp.755-760

  • Publication Type: Conference Paper / Full Text
  • City: Karabük
  • Country: Turkey
  • Page Numbers: pp.755-760
  • Van Yüzüncü Yıl University Affiliated: Yes


 Wireless Sensor Networks (WSN) are used for the monitoring of objects in various fields of application as well as the monitoring of military and civilian environments. The energy consumption of sensors and the optimization of network lifetime in WSNs are among the important problems that are constantly investigated and for which solutions are developed by linear programming method. Furthermore, different algorithmic solutions have been developed to perform the dynamic deployment of the nodes efficiently for the solution of this problem. The proposed solutions require that the targets in the network are covered by a minimum number of sensors. k-coverage, that determines the degrees of coverage of the targets in the area of interest, is an important criterion in determining the number of sensors covering each target after the deployment of the sensors. Because the coverage of the targets by a minimum number of sensors and the minimization of the intersection area of the sensor increase the lifetime of the network by optimizing the energy consumptions of the sensors.

In this study, the dynamic deployment approach based on the Whale Optimization Algorithm was proposed to provide the optimum solution to the k-coverage problem of WSNs by ensuring that the targets in the area are covered by a minimum number of sensors. This approach, that performs the effective dynamic deployment of sensors by covering the maximum number of target points and ensuring the minimum degree of k-coverage, was compared with the MADA-EM in the literature. Simulation results have shown that this approach is optimum and can be recommended in the solution of the k-coverage problem by ensuring that the targets are covered by a minimum number of nodes.