Multiconstraint-based quality of service-aware joint optimistic framework for non-orthogonal multiple access-based fog computing vehicular network

Abstract

The internet of vehicles (IoV) supports urban transit by connecting automobiles to the internet of things (IoT). The IoV improves vehicle safety and efficiency by assisting passengers. In vehicular networks, fog computing is used to store and utilise energy. Because data transmission is massive, vehicular fog computing networks are vulnerable. In this study, a joint optimistic framework in a non-orthogonal multiple access (NOMA)-based fog computing vehicular network is utilised to solve IoV resource management issues. NOMA improves the spectral efficiency and throughput of a system. The optimised hybrid leader war strategy (HLWS) algorithm is designed by combining hybrid leader-based optimisation and war strategy optimisation to allocate the subchannel and resources. The developed HLWS algorithm achieves an adequate energy efficiency of 40.32 %, the best possible subchannel utility, a lower penalty function, and the highest throughput of 793.28 Mbps, compared with other algorithms investigated.