{"title":"基于VIKOR MADM的异构网络垂直切换优化方法","authors":"Silki Baghla, S. Bansal","doi":"10.25728/ASSA.2018.18.3.563","DOIUrl":null,"url":null,"abstract":"Optimum network selection is one of the major issues for vertical handover in heterogeneous networks so as to provide requisite quality of service (QoS) to the user. In this context, multiple attribute decision-making algorithms provide a promising solution. Normalization process used can play a vital role in selecting the most appropriate network during the handover process.In this work, vector normalized preferred performance based (V-VPP) normalization technique is proposed and applied to MADM based VIKOR algorithm. Performance of the proposed technique is analyzed extensively by varying QoS parameters and weighting methods for different traffic classes in a heterogeneous network The results obtained are compared with the available MAX, MAX-MIN and Vector normalization.The proposed method is also compared with the popular MADM algorithms. Performance of proposed method is quite optimistic in terms of lesser number of handovers, ranking abnormality, selection of appropriate network though with slight increase in handover latency in comparison to the available normalization methods.","PeriodicalId":39095,"journal":{"name":"Advances in Systems Science and Applications","volume":"18 1","pages":"90-110"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"VIKOR MADM Based Optimization Method For Vertical Handover In Heterogeneous Networks\",\"authors\":\"Silki Baghla, S. Bansal\",\"doi\":\"10.25728/ASSA.2018.18.3.563\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Optimum network selection is one of the major issues for vertical handover in heterogeneous networks so as to provide requisite quality of service (QoS) to the user. In this context, multiple attribute decision-making algorithms provide a promising solution. Normalization process used can play a vital role in selecting the most appropriate network during the handover process.In this work, vector normalized preferred performance based (V-VPP) normalization technique is proposed and applied to MADM based VIKOR algorithm. Performance of the proposed technique is analyzed extensively by varying QoS parameters and weighting methods for different traffic classes in a heterogeneous network The results obtained are compared with the available MAX, MAX-MIN and Vector normalization.The proposed method is also compared with the popular MADM algorithms. Performance of proposed method is quite optimistic in terms of lesser number of handovers, ranking abnormality, selection of appropriate network though with slight increase in handover latency in comparison to the available normalization methods.\",\"PeriodicalId\":39095,\"journal\":{\"name\":\"Advances in Systems Science and Applications\",\"volume\":\"18 1\",\"pages\":\"90-110\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Systems Science and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.25728/ASSA.2018.18.3.563\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Systems Science and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.25728/ASSA.2018.18.3.563","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Engineering","Score":null,"Total":0}
VIKOR MADM Based Optimization Method For Vertical Handover In Heterogeneous Networks
Optimum network selection is one of the major issues for vertical handover in heterogeneous networks so as to provide requisite quality of service (QoS) to the user. In this context, multiple attribute decision-making algorithms provide a promising solution. Normalization process used can play a vital role in selecting the most appropriate network during the handover process.In this work, vector normalized preferred performance based (V-VPP) normalization technique is proposed and applied to MADM based VIKOR algorithm. Performance of the proposed technique is analyzed extensively by varying QoS parameters and weighting methods for different traffic classes in a heterogeneous network The results obtained are compared with the available MAX, MAX-MIN and Vector normalization.The proposed method is also compared with the popular MADM algorithms. Performance of proposed method is quite optimistic in terms of lesser number of handovers, ranking abnormality, selection of appropriate network though with slight increase in handover latency in comparison to the available normalization methods.
期刊介绍:
Advances in Systems Science and Applications (ASSA) is an international peer-reviewed open-source online academic journal. Its scope covers all major aspects of systems (and processes) analysis, modeling, simulation, and control, ranging from theoretical and methodological developments to a large variety of application areas. Survey articles and innovative results are also welcome. ASSA is aimed at the audience of scientists, engineers and researchers working in the framework of these problems. ASSA should be a platform on which researchers will be able to communicate and discuss both their specialized issues and interdisciplinary problems of systems analysis and its applications in science and industry, including data science, artificial intelligence, material science, manufacturing, transportation, power and energy, ecology, corporate management, public governance, finance, and many others.