The Effect of Updating Routing Tables of Neighboring Nodes in AntNet Algorithm by Assistant Agents

Appropriate routing in data transfer is a challenging problem that can lead to improved performance of networks in terms of lower delay in delivery of packets and higher throughput. Considering the highly distributed nature of networks, several multi-agent based algorithms, and in particular ant colony based algorithms, have been suggested in recent years. However, considering the need for quick optimization and adaptation to network changes, improving the relative slow convergence of these algorithms remains an elusive challenge. Our goal here is to reduce the time needed for convergence and to accelerate the routing algorithm’s response to network failures and/or changes by imitating pheromone propagation in natural ant colonies. More specifically, information exchange among neighboring nodes is facilitated by proposing a new type of ant (assistant ants) to the AntNet algorithm. This method is an extension of authors’ earlier work by allowing intermediate nodes, in addition to destination nodes, to produce assistant ants. The resulting algorithm, the “modified AntNet,” is then simulated via NS2 on NSF and NttNet network topologies. The network performance is evaluated under various conditions. Statistical analysis of results confirms that the new method can significantly reduce the average packet delivery time and rate of convergence to the optimal route when compared with standard AntNet.