{"title":"A Comparative Study of Outranking MADM Algorithms in Network Selection","authors":"K. Anupama, S. Sri Gowri, B. Prabakara Rao","doi":"10.1109/ICCMC.2018.8487931","DOIUrl":null,"url":null,"abstract":"A variety of Multi Attribute Decision Making (MADM) algorithms have been applied to the problem of network selection in a heterogeneous wireless environment. As each kind of MADM approach has its own strong and weak points, it is quite difficult to ensure which MADM algorithm is more appropriate for network selection. Moreover, from decision making perspective, an algorithm that can provide minor improvement in network selection accuracy is more preferable, rather than applying classical approaches prevailing from decades. In this context, this paper makes an attempt to identify the most suitable MADM method among the established outranking PROMETHEE and ELECTRE algorithms. The algorithms are tested in a heterogeneous environment with four overlapping networks and their performance is compared in terms of Network Selection Accuracy and Network Congestion. PROMETHEE algorithm produced beneficial results when compared to ELECTRE.","PeriodicalId":6604,"journal":{"name":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","volume":"5 1 1","pages":"904-907"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Second International Conference on Computing Methodologies and Communication (ICCMC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCMC.2018.8487931","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
A variety of Multi Attribute Decision Making (MADM) algorithms have been applied to the problem of network selection in a heterogeneous wireless environment. As each kind of MADM approach has its own strong and weak points, it is quite difficult to ensure which MADM algorithm is more appropriate for network selection. Moreover, from decision making perspective, an algorithm that can provide minor improvement in network selection accuracy is more preferable, rather than applying classical approaches prevailing from decades. In this context, this paper makes an attempt to identify the most suitable MADM method among the established outranking PROMETHEE and ELECTRE algorithms. The algorithms are tested in a heterogeneous environment with four overlapping networks and their performance is compared in terms of Network Selection Accuracy and Network Congestion. PROMETHEE algorithm produced beneficial results when compared to ELECTRE.