Fuzzy-Based Secure Clustering with Routing Technique for VANETs

Abstract

Due to the advanced developments in communication technologies, Internet of vehicles and vehicular adhoc networks (VANET) offers numerous opportunities for effectively managing transportation problems. On the other, the cloud environment needs to disseminate the emergency message to the vehicles which are consistently distributed on the roadway so that every vehicle gets the messages from closer vehicles in a straightforward way. To resolve this issue, clustering and routing techniques can be designed using computational intelligence approaches. With this motivation, this paper presents a new type-2 fuzzy sets based clustering with metaheuristic optimization based routing (T2FSC-MOR) technique for secure communication in VANET. The T2FSC-MOR technique aims to elect CHs and optimal routes for secure intercluster data transmission in VANET. The proposed model involves T2FSC technique for the selection of CHs and construction of clusters. The T2FSC technique uses different parameters namely traveling speed (TS), link quality (LQ), trust factor (TF), inter-vehicle distance (IVD), and neighboring node count (NCC). The inclusion of trust factor helps to select the proper cluster heads (CHs) for secure data dissemination process. Moreover, trust aware seagull optimization based routing (TASGOR) approach was derived for the optimal selection of routes in VANET. In order to validate the enhanced performance of proposed technique, the set of simulations take place and the outcomes are examined interms of different measures. The experimental outcomes highlighted the improved performance of the proposed model over the other state of art techniques with a higher throughput of 98%.