{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T12:36:22Z","timestamp":1777898182717,"version":"3.51.4"},"reference-count":24,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T00:00:00Z","timestamp":1709251200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Natural Science Foundation of China","award":["62266019"],"award-info":[{"award-number":["62266019"]}]},{"name":"National Natural Science Foundation of China","award":["62066016"],"award-info":[{"award-number":["62066016"]}]},{"name":"National Natural Science Foundation of China","award":["22B0549"],"award-info":[{"award-number":["22B0549"]}]},{"name":"National Natural Science Foundation of China","award":["22C0282"],"award-info":[{"award-number":["22C0282"]}]},{"name":"Scientific Research Project of Education Department of Hunan Province","award":["62266019"],"award-info":[{"award-number":["62266019"]}]},{"name":"Scientific Research Project of Education Department of Hunan Province","award":["62066016"],"award-info":[{"award-number":["62066016"]}]},{"name":"Scientific Research Project of Education Department of Hunan Province","award":["22B0549"],"award-info":[{"award-number":["22B0549"]}]},{"name":"Scientific Research Project of Education Department of Hunan Province","award":["22C0282"],"award-info":[{"award-number":["22C0282"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>For wireless sensor network (WSN) coverage problems, since the sensing range of sensor nodes is a circular area with symmetry, taking symmetry into account when deploying nodes will help simplify problem solving. In addition, in view of two specific problems of high node deployment costs and insufficient effective coverage in WSNs, this paper proposes a WSN coverage optimization method based on the improved grey wolf optimizer with multi-strategies (IGWO-MS). As far as IGWO-MS is concerned, first of all, it uses Sobol sequences to initialize the population so that the initial values of the population are evenly distributed in the search space, ensuring high ergodicity and diversity. Secondly, it introduces a search space strategy to increase the search range of the population, avoid premature convergence, and improve search accuracy. And then, it combines reverse learning and mirror mapping to expand the population richness. Finally, it adds Levy flight to increase the disturbance and improve the probability of the algorithm jumping out of the local optimum. To verify the performance of IGWO-MS in WSN coverage optimization, this paper rasterizes the coverage area of the WSN into multiple grids of the same size and symmetry with each other, thereby transforming the node coverage problem into a single-objective optimization problem. In the simulation experiment, not only was IGWO-MS selected, but four other algorithms were also selected for comparison, namely particle swarm optimization (PSO), grey wolf optimizer (GWO), grey wolf optimization based on drunk walk (DGWO), and grey wolf optimization led by two-headed wolves (GWO-THW). The experimental results demonstrate that when the number of nodes for WSN coverage optimization is 20 and 30, the optimal coverage rate and average coverage rate using IGWO-MS are both improved compared to the other four comparison algorithms. To make this clear, in the case of 20 nodes, the optimal coverage rate of IGWO-MS is increased by 13.19%, 1.68%, 4.92%, and 3.62%, respectively, compared with PSO, GWO, DGWO, and GWO-THW; while IGWO-MS performs even better in terms of average coverage rate, which is 16.45%, 3.13%, 11.25%, and 6.19% higher than that of PSO, GWO, DGWO, and GWO-THW, respectively. Similarly, in the case of 30 nodes, compared with PSO, GWO, DGWO, and GWO-THW, the optimal coverage rate of the IGWO-MS is increased by 15.23%, 1.36%, 5.55%, and 3.66%; the average coverage rate is increased by 16.78%, 1.56%, 10.91%, and 8.55%. Therefore, it can be concluded that IGWO-MS has certain advantages in solving WSN coverage problems, which is reflected in that not only can it effectively improve the coverage quality of network nodes, but it also has good stability.<\/jats:p>","DOI":"10.3390\/sym16030286","type":"journal-article","created":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T06:07:53Z","timestamp":1709273273000},"page":"286","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":59,"title":["An Improved Grey Wolf Optimizer with Multi-Strategies Coverage in Wireless Sensor Networks"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4052-1105","authenticated-orcid":false,"given":"Yun","family":"Ou","sequence":"first","affiliation":[{"name":"School of Communication and Electronic Engineering, Jishou University, Jishou 416000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2369-145X","authenticated-orcid":false,"given":"Feng","family":"Qin","sequence":"additional","affiliation":[{"name":"Faculty of Computing, Universiti Teknologi Malaysia, Skudai 81310, Malaysia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5779-7135","authenticated-orcid":false,"given":"Kai-Qing","family":"Zhou","sequence":"additional","affiliation":[{"name":"School of Communication and Electronic Engineering, Jishou University, Jishou 416000, China"}]},{"given":"Peng-Fei","family":"Yin","sequence":"additional","affiliation":[{"name":"Academic Affairs Office, Jishou University, Jishou 416000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4462-1565","authenticated-orcid":false,"given":"Li-Ping","family":"Mo","sequence":"additional","affiliation":[{"name":"College of Computer Science and Engineering, Jishou University, Jishou 416000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2004-3289","authenticated-orcid":false,"given":"Azlan","family":"Mohd Zain","sequence":"additional","affiliation":[{"name":"Faculty of Computing, Universiti Teknologi Malaysia, Skudai 81310, Malaysia"}]}],"member":"1968","published-online":{"date-parts":[[2024,3,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11227-013-1021-9","article-title":"Wireless sensor networks: A survey on recent developments and potential synergies","volume":"68","author":"Rawat","year":"2014","journal-title":"J. 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