An Enhanced Hybrid Glowworm Swarm Optimization Algorithm for Traffic-Aware Vehicular Networks

A subclass of a Mobile Adhoc Network (MANET) is a Vehicular Adhoc Network (VANET). It consists of self-configuring moving vehicles which are called nodes. It is an inevitable ingredient of intelligent transportation systems. The vehicular network has some permanent devices called roadside units and moving devices called On Board Units (OBU). Every vehicle traveling on the network must possess the OBU. Safety and non-safety tidings are broadcasted in vehicular networks. Even vehicular network is derived from MANET and its characters are discriminated against the MANET. The various unique characteristics of VANETs are high mobility, changes in network topology, size of the network, long distance between the vehicles, frequently changing vehicle density, and limited time. Because of these special features, the traditional security and routing mechanisms are not suitable for VANETs. Also, the safety messages are modified or discarded by the attacker or any other node and it may lead to the loss of privacy, integrity, confidentiality, and authentication of the data.So to enhance the security of VANETs, it is very much essential to invent a secure communication protocol, to protect the infrastructure of the network and the confidentiality of the data. The simulation results reveal that the secure communication using certificate revocation approach, energy-efficient enhanced secure routing protocol, traffic-aware secure routing for VANETs using Hybrid Enhanced Glowworm Swarm Optimization (HEGSO), and trust model for secure communication in VANETs is ensuring the security in VANETs. When compared to peer existing routing protocols, the proposed scheme significantly reduces the packet failure ratio, response time, and throughput. When compared to ARIOR and I-AREOR, the proposed HEGSO technique diminished delays by 20% and 34%, respectively.