V. Berrocal-Plaza, M. A. Vega-Rodríguez, J. M. Sánchez-Pérez
{"title":"在现实的移动环境中研究报告单元策略","authors":"V. Berrocal-Plaza, M. A. Vega-Rodríguez, J. M. Sánchez-Pérez","doi":"10.1109/NaBIC.2014.6921900","DOIUrl":null,"url":null,"abstract":"In this paper, we optimize the Reporting Cells Planning Problem in a realistic mobile network. To the best of our knowledge, this is the first work in the literature in which the Reporting Cells Planning Problem is studied in a realistic mobile environment. This problem is based on a mobile location management strategy where the network cells can be in two possible states: Reporting Cells and non-Reporting Cells. In this location management strategy, a mobile station only updates its location when moving to a new Reporting Cell, and it is free to move among non-Reporting Cells without updating its location. The Reporting Cells Planning Problem can be classified as a multiobjective optimization problem with two objective functions: minimize the number of location updates and minimize the number of paging messages. With the aim of finding the best possible set of non-dominated solutions, we have implemented a well-known multiobjective evolutionary algorithm: the Non-dominated Sorting Genetic Algorithm II (NSGAII). Experimental results show that our proposal is able to achieve good sets of non-dominated solutions and, at the same time, to improve the results obtained with other optimization techniques.","PeriodicalId":209716,"journal":{"name":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Studying the Reporting Cells strategy in a realistic mobile environment\",\"authors\":\"V. Berrocal-Plaza, M. A. Vega-Rodríguez, J. M. Sánchez-Pérez\",\"doi\":\"10.1109/NaBIC.2014.6921900\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we optimize the Reporting Cells Planning Problem in a realistic mobile network. To the best of our knowledge, this is the first work in the literature in which the Reporting Cells Planning Problem is studied in a realistic mobile environment. This problem is based on a mobile location management strategy where the network cells can be in two possible states: Reporting Cells and non-Reporting Cells. In this location management strategy, a mobile station only updates its location when moving to a new Reporting Cell, and it is free to move among non-Reporting Cells without updating its location. The Reporting Cells Planning Problem can be classified as a multiobjective optimization problem with two objective functions: minimize the number of location updates and minimize the number of paging messages. With the aim of finding the best possible set of non-dominated solutions, we have implemented a well-known multiobjective evolutionary algorithm: the Non-dominated Sorting Genetic Algorithm II (NSGAII). Experimental results show that our proposal is able to achieve good sets of non-dominated solutions and, at the same time, to improve the results obtained with other optimization techniques.\",\"PeriodicalId\":209716,\"journal\":{\"name\":\"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/NaBIC.2014.6921900\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Sixth World Congress on Nature and Biologically Inspired Computing (NaBIC 2014)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NaBIC.2014.6921900","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Studying the Reporting Cells strategy in a realistic mobile environment
In this paper, we optimize the Reporting Cells Planning Problem in a realistic mobile network. To the best of our knowledge, this is the first work in the literature in which the Reporting Cells Planning Problem is studied in a realistic mobile environment. This problem is based on a mobile location management strategy where the network cells can be in two possible states: Reporting Cells and non-Reporting Cells. In this location management strategy, a mobile station only updates its location when moving to a new Reporting Cell, and it is free to move among non-Reporting Cells without updating its location. The Reporting Cells Planning Problem can be classified as a multiobjective optimization problem with two objective functions: minimize the number of location updates and minimize the number of paging messages. With the aim of finding the best possible set of non-dominated solutions, we have implemented a well-known multiobjective evolutionary algorithm: the Non-dominated Sorting Genetic Algorithm II (NSGAII). Experimental results show that our proposal is able to achieve good sets of non-dominated solutions and, at the same time, to improve the results obtained with other optimization techniques.