A Fault-tolerant technique for future Social IoV using Evolutionary computation based Whale Optimization Model

This paper addresses the crucial fault control challenges for the regulation of system-level reliability in 5G enabled SDN-controlled Social Internet of Vehicles (SDSIoV) environment. To mitigate these challenges a new variant of optimal service scheduling has been proposed using Whale optimization algorithm for fault control (WOFC). Detection and prevention of fault is monitored in fog-computing vehicles (FCV) within SDSIoV Infrastructure is depicted in fog-computing RSUs (FCRSU) by load balancing the message passing-based interval in the chosen network traffic. Three SDSIoV scenarios (low, normal and high) of 10, 50 and 100 numbers of FCV nodes with 10, 25 and 40 services are considered with the routing lengths as 300m, 600m and 1500m. Each scenario is tested for no-fault data, with 15% and 30% faulty services and nodes data. The favourable hit ratio is computed in terms of execution times and response time of services with available fault-free and faulty resources. The obtained results of the proposed optimization model outperform over existing techniques.