Shinji Sakamoto, Admir Barolli, L. Barolli, M. Takizawa
{"title":"基于粒子群优化、爬坡和分布式遗传算法的WMNs节点放置混合智能系统的设计与实现","authors":"Shinji Sakamoto, Admir Barolli, L. Barolli, M. Takizawa","doi":"10.1109/AINA.2018.00103","DOIUrl":null,"url":null,"abstract":"The Wireless Mesh Networks (WMNs) have low cost and high speed wireless Internet connectivity, therefore they are becoming an important networking infrastructure. In our previous work, we implemented a hybrid intelligent system based on Particle Swarm Optimization (PSO) and Hill Climbing (HC), called WMN-PSOHC, and a simulation system based on Genetic Algorithm (GA), called WMN-GA, for solving node placement problem in WMNs. In this paper, we implement a new hybrid simulation system based on PSOHC and distributed GA (DGA), called WMN-PSOHC-DGA. We evaluate WMN-PSOHC-DGA system by computer simulations. The simulation results show that the WMN-PSOHC-DGA system has a better performance compared with WMN-PSODGA.","PeriodicalId":239730,"journal":{"name":"2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Design and Implementation of a Hybrid Intelligent System Based on Particle Swarm Optimization, Hill Climbing and Distributed Genetic Algorithm for Node Placement Problem in WMNs: A Comparison Study\",\"authors\":\"Shinji Sakamoto, Admir Barolli, L. Barolli, M. Takizawa\",\"doi\":\"10.1109/AINA.2018.00103\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Wireless Mesh Networks (WMNs) have low cost and high speed wireless Internet connectivity, therefore they are becoming an important networking infrastructure. In our previous work, we implemented a hybrid intelligent system based on Particle Swarm Optimization (PSO) and Hill Climbing (HC), called WMN-PSOHC, and a simulation system based on Genetic Algorithm (GA), called WMN-GA, for solving node placement problem in WMNs. In this paper, we implement a new hybrid simulation system based on PSOHC and distributed GA (DGA), called WMN-PSOHC-DGA. We evaluate WMN-PSOHC-DGA system by computer simulations. The simulation results show that the WMN-PSOHC-DGA system has a better performance compared with WMN-PSODGA.\",\"PeriodicalId\":239730,\"journal\":{\"name\":\"2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA)\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AINA.2018.00103\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 32nd International Conference on Advanced Information Networking and Applications (AINA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AINA.2018.00103","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Design and Implementation of a Hybrid Intelligent System Based on Particle Swarm Optimization, Hill Climbing and Distributed Genetic Algorithm for Node Placement Problem in WMNs: A Comparison Study
The Wireless Mesh Networks (WMNs) have low cost and high speed wireless Internet connectivity, therefore they are becoming an important networking infrastructure. In our previous work, we implemented a hybrid intelligent system based on Particle Swarm Optimization (PSO) and Hill Climbing (HC), called WMN-PSOHC, and a simulation system based on Genetic Algorithm (GA), called WMN-GA, for solving node placement problem in WMNs. In this paper, we implement a new hybrid simulation system based on PSOHC and distributed GA (DGA), called WMN-PSOHC-DGA. We evaluate WMN-PSOHC-DGA system by computer simulations. The simulation results show that the WMN-PSOHC-DGA system has a better performance compared with WMN-PSODGA.