Routing in vehicular ad hoc networks (VANETs) where the group of vehicles is moved randomly in any direction without any central coordination. The movements of the vehicle nodes are highly dynamic, therefore ensuring data delivery with small overhead and less delay is a challenging issue. In order to improve the routing, Geographical Zone clustered Multi-objective Glowworm swarm optimized Routing (GZMGR) technique is introduced. Initially, ‘n’ numbers of glowworms (i.e., vehicle nodes) are arbitrarily distributed in search space (i.e. network). In this proposed technique, the source vehicle node sends the data packet to the master node within the zone and it sends the data packet to a master node in another zone. Then the master node in another zone transmits to the destination (i.e. cluster member). Therefore, the routing of the data packet is performed via the master node since it collects the network status and location, direction, information of its cluster members. As a result, the master node reduces the overall traffic in the network and minimizes the delay. The master node is selected based on distance, high signal strength and direction of the node. After that, the source node initiates the data packets to transmit to the destination through the neighboring node. Initially, each glowworm has luminescence quantity called luciferin (i.e., objective function). The objective functions used for neighboring node selection are nodes speed, distance and link lifetime. Then the fitness is computed based on the objective functions to find the nodes for the optimization process. Due to the mobility, the luciferin value of the node is updated and finds the neighbor node through the probability. Finally, the source node takes a local decision for selecting the optimal neighboring node with minimum distance and high link lifetime. By this way, the optimal neighboring nodes are selected to forward the data packets. Followed by, a stable routing path from source to destination is established by considering the optimal one-hop vehicle. After that, the data packets are transmitted along the route path to the destination node. The simulation is conducted with different parameters such as collision rate, packet delivery ratio, normalized routing load and average end to end delay with respect to a number of vehicle nodes.

VANET, Geographical Zone, cluster-based routing, master node selection, Multi-objective Glowworm Swarm optimization

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