An evolutionary computation based tunicate swarm optimization approach for fault control in SDN-driven and 5G enabled social IoV
Satyabrat Sahoo, Satyabrat Sahoo, Satya Prakash Sahoo, Satya Prakash Sahoo, Manas Ranjan Kabat, Ram Chandra Barik · International Journal of Computers and Applications · 2025
Though over time, many services of Social Internet of Vehicles (SIoV) have emerged along with software defined network (SDN) and 5th generation (5G) connectivity, the regulation of system-level dependability is a concern in reference to the critical fault control challenges. There are a number of obstacles to this fault control strategy, such as resource constraints, reaction time latency, service placement and extended execution periods of network services. In this study, we have introduced an evolutionary computation form of optimal service scheduling by utilizing the Tunicate swarm optimization technique, for improved supervision with low cost and high system performance rate to counter the faults. With a route distance ranging from 300 to 1500 meters, the three scenarios have 10 to 100 vehicles and 10 to 40 services, each with 15% and 30% of services that are defective and/or error-free. The burst and reaction times of the services, the cost-price ratio, and the system performance rate are used to determine the favorable hit ratio while using both defective and fault-free resources. Results from the proposed optimization model outperform those from earlier methods. The average response time is 11.24 milli seconds and the average performance rate is nearly 76% in our proposed model.