{"title":"基于高斯-牛顿法和灰太狼优化算法的节能节点定位算法","authors":"","doi":"10.4018/ijfsa.296591","DOIUrl":null,"url":null,"abstract":"Node localization process is a crucial prerequisite in the area of Wireless Sensor Networks (WSNs). The algorithms for node localization process can either range-based or range-free. Range-free algorithms are preferred over range-based ones due to their cost-effectiveness. DV-Hop along with its variants is normally well-liked range-free algorithm because of its straightforwardness, scalability and distributed nature, but it has some disadvantages such as poor accuracy and high-power utilization. To deal with these limitations, this paper introduces an algorithm, called GWOGN-LA. GWOGN-LA improves accuracy by applying Grey-Wolf Optimization and Gauss-Newton method. The proposed algorithm restricts the forwarding of packets in order to limit energy consumption. Simulation results show that given proposal outperforms other state-of-art algorithms in terms of accuracy and power consumption.","PeriodicalId":38154,"journal":{"name":"International Journal of Fuzzy System Applications","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Energy Efficient Node Localization Algorithm based on Gauss-Newton Method and Grey Wolf Optimization Algorithm\",\"authors\":\"\",\"doi\":\"10.4018/ijfsa.296591\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Node localization process is a crucial prerequisite in the area of Wireless Sensor Networks (WSNs). The algorithms for node localization process can either range-based or range-free. Range-free algorithms are preferred over range-based ones due to their cost-effectiveness. DV-Hop along with its variants is normally well-liked range-free algorithm because of its straightforwardness, scalability and distributed nature, but it has some disadvantages such as poor accuracy and high-power utilization. To deal with these limitations, this paper introduces an algorithm, called GWOGN-LA. GWOGN-LA improves accuracy by applying Grey-Wolf Optimization and Gauss-Newton method. The proposed algorithm restricts the forwarding of packets in order to limit energy consumption. Simulation results show that given proposal outperforms other state-of-art algorithms in terms of accuracy and power consumption.\",\"PeriodicalId\":38154,\"journal\":{\"name\":\"International Journal of Fuzzy System Applications\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Fuzzy System Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/ijfsa.296591\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Fuzzy System Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/ijfsa.296591","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
Energy Efficient Node Localization Algorithm based on Gauss-Newton Method and Grey Wolf Optimization Algorithm
Node localization process is a crucial prerequisite in the area of Wireless Sensor Networks (WSNs). The algorithms for node localization process can either range-based or range-free. Range-free algorithms are preferred over range-based ones due to their cost-effectiveness. DV-Hop along with its variants is normally well-liked range-free algorithm because of its straightforwardness, scalability and distributed nature, but it has some disadvantages such as poor accuracy and high-power utilization. To deal with these limitations, this paper introduces an algorithm, called GWOGN-LA. GWOGN-LA improves accuracy by applying Grey-Wolf Optimization and Gauss-Newton method. The proposed algorithm restricts the forwarding of packets in order to limit energy consumption. Simulation results show that given proposal outperforms other state-of-art algorithms in terms of accuracy and power consumption.