A Spectrum Handoff Scheme for Optimal Network Selection in NEMO based Cognitive Radio Vehicular Networks: A Cost Function MADM Method based on Grey Theory based Approach

Abstract

Multiple Attribute Decision Making (MADM) is one of the intelligent network selection methodologies for Intelligent Transportation System (ITS). The fundamental objective of MADM method is to select the optimal network among the finite set of alternative. In this paper, we have proposed a cost function MADM method based on the grey theory based approach which outperforms the existing MADM method for ITS. The method is validated to perform a spectrum handoff for optimal network selection in Network Mobility (NEMO) based Cognitive Radio (CR) vehicular networks. In NEMO based CR vehicular networks, the Mobile Reuter (MR) requires spectrum handoff when a mobile network changes its point of attachment in CR vehicular networks. It becomes difficult for MR to select the optimal network from the available access networks. The application of MADM methods provides wider and optimum choice among the available networks with quality of service. Numerical results revel that the proposed MADM method is effective for spectrum handoff decision for optimal network selection with reduced complexity in NEMO based CR vehicular networks.