{"title":"The Use of a Hopfield Neural Network in Solving the Mobility Management Problem","authors":"J. Taheri, A. Zomaya","doi":"10.1109/perser.2004.1356786","DOIUrl":null,"url":null,"abstract":"This work presents a new approach to solve the location management problem by using the location areas approach. Hopfield Neural Network is used in this work to find the optimal configuration of location areas in a mobile network. Toward this end, the location areas configuration of the network is modeled so that the mobility management cost of the system is related to the energy value of this artificial neural network. Since a pure Hopfield Neural Network was not efficient enough to be used in solving this problem, some modifications applied to it to make it a reasonable approach. Basically, these modifications deal with randomness of selection in manipulating the cells during the solving process. Simulation results are very promising and they lead to network configurations that are unexpected.","PeriodicalId":222266,"journal":{"name":"The IEEE/ACS International Conference on Pervasive Services","volume":"8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The IEEE/ACS International Conference on Pervasive Services","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/perser.2004.1356786","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
This work presents a new approach to solve the location management problem by using the location areas approach. Hopfield Neural Network is used in this work to find the optimal configuration of location areas in a mobile network. Toward this end, the location areas configuration of the network is modeled so that the mobility management cost of the system is related to the energy value of this artificial neural network. Since a pure Hopfield Neural Network was not efficient enough to be used in solving this problem, some modifications applied to it to make it a reasonable approach. Basically, these modifications deal with randomness of selection in manipulating the cells during the solving process. Simulation results are very promising and they lead to network configurations that are unexpected.