New Manhattan distance-based fuzzy MADM method for the network selection

New Manhattan distance-based fuzzy MADM method for the network selection

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Mobile devices are increasingly developing, and more sophisticated wireless networks are available as well. Users nowadays want to access the best available technology anytime, following the always best-connected concept, which leads often to vertical handovers. It means changing the wireless access type and is an important research area in the next generation of networking. In contrast, when changing the point of attachment while using the same wireless technology, it is a ‘horizontal handover’. When handing over the communications, the transfer should be ‘seamless’, i.e. it should not cause delays or break the session and disconnect the user. Indeed, the vertical handover process is continuously improving, especially the network selection step, which is the most crucial one. Naturally, multi-attribute decision-making (MADM) methods fit this kind of issues, but they still produce some undesirable results sometimes, due to metrics imprecision and vagueness. The authors propose in this study a new network selection scheme, combining the fuzzy logic and a new MADM method, named fuzzy Manhattan distance to the ideal alternative. They compare through simulations this new technique, with the best known MADM methods, as well as with fuzzy grey relational analysis, to evaluate its performance in the same context.


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