Title: Improved genetic algorithm-based sensor nodes deployment for barrier coverage
Authors: Subash Harizan; Pratyay Kuila; Rajeev Kumar; Akhilendra Khare; Reeta Clonia; Ashwin Perti
Addresses: Department of Computer Science and Engineering, Galgotias University, Uttar Pradesh, 201310, India ' Department of Computer Science and Engineering, National Institute of Technology, Sikkim, 737139, India ' Department of Computer Science and Engineering, Nalanda College of Engineering, Nalanda, Bihar, 803108, India ' Department of Computer Science and Engineering, Galgotias University, Uttar Pradesh, 201310, India ' Department of Management, Maharishi Markandeshwar (Deemed to be University), Haryana, India ' Department of Computer Science and Engineering, Galgotias University, Uttar Pradesh, 201310, India
Abstract: Barrier coverage is widely used for an intruder detection. However, sensor nodes (SNs) are prone to failure. Hence it is very challenging to construct a barrier with an efficient coverage and connectivity with minimum number of SNs. From a given set of potential positions (PPs), finding minimum number of PPs for the placement of SNs to form a barrier is an NP-complete problem. In this paper, we propose an improved genetic algorithm (GA)-based approach to solve the aforesaid problem. For the better performance and fast convergence of the algorithm, a novel mutation operation is introduced. In our proposed approach chromosomes are efficiently represented along with an efficient fitness function to evaluate the quality. An extensive simulation is conducted on the various scenarios of the network. The efficiency of the proposed algorithm is shown by comparing the simulated results with traditional genetic algorithm (GA), differential evolution (DE) and GreedyCSC algorithms.
Keywords: wireless sensor networks; WSNs; barrier coverage; connectivity; genetic algorithm; novel mutation.
DOI: 10.1504/IJSNET.2023.134905
International Journal of Sensor Networks, 2023 Vol.43 No.3, pp.146 - 157
Received: 23 May 2023
Accepted: 04 Sep 2023
Published online: 16 Nov 2023 *