Favorable Trail Detection using ACO-Bellman Algorithm in VANETs

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Abstract
Vehicular ad hoc networks (VANETs) are the networks, which configured themselves, where the nodes are moving vehicles. These provide the communications required to deploy Intelligent Transportation Systems (ITS). A major dispute in VANETs is distribution of efficient and computable information because during communication nodes may leave or join the network dynamically. There is no guarantee about node availability at any given time, which leads to traffic problem, congestion problem. Therefore trailing the favorable path is a challengeable issue. Multiple routing algorithms have been developed for routing solution. In this paper the swarm-based algorithm has been presented, which helps to find out the optimal route using Bellman Ford algorithm. Ant colonization searches out the path using pheromones level. Higher the pheromone count of a route gives the optimal choice of path that can be used for packet delivery. Bellman Ford Algorithm optimizes the paths found by Ant Colony Optimization (ACO) by comparing the distance of source to all the nodes of network or cost given to the networks.

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