Soft computing technique based parametric optimization for automatic vertical handover in next generation wireless communication networks

Abstract

A seamless vertical handover between heterogeneous networks is very newlineimportant in the next generation wireless networks which aim at the provision newlineof uninterrupted network connections anywhere and at any time. The next newlinegeneration of wireless communication is expected to integrate a potentially newlinelarge number of heterogeneous wireless technologies in what could be newlineconsidered a huge step forward toward universal seamless access. One of the newlinemain challenges for seamless mobility is the availability of reliable vertical newline(intersystem) handoff schemes. Efficient handoff schemes enhance quality of newlineservice and provide flawless mobility. Existing decision algorithms and newlineschemes are deficient either in proper representation of network parameters or newlinedo not provide sufficient detail in reporting these studies for real world newlineimplementations. newlineThis research focuses on decision making for network selection during vertical newlinehandover between heterogeneous wireless networks. In the existing literature, newlineclassical Multi-Attribute Decision Making (MADM) methods have been used newlinewhich are inefficient due to the imprecise nature of data used by the decision newlinealgorithm. We use Fuzzy MADM techniques to deal with imprecise information newlineand to obtain a robust mathematical framework for evaluation of multiple newlinecriteria. newlineWe have developed the Mash-up Analytical Index Multiplicative Sensing newline(MAIMS) algorithm based on Analytical Hierarchical Process (AHP) for newlineparameter selection. Weights are then assigned to the selected parameters newlinedepending on the type of application and Quality of Service (QoS) using Fuzzy newlineAnalytical Network Process (F-ANP). An optimized ranking of the eligible newlinenetworks for handover is then done using Multiplicative Exponential Weighing newline(MEW) technique. Once the optimum network is selected, proper resource newlineallocation needs to be done. A comparison of handover decision delay and the newlineprobability of handover failures by using the proposed scheme, with the existing newlineMADM techniques is done. The parameters required for the decision phase are