Various forms of swarm intelligence are inspired by social behavior of insects that live collectively. AntNet is a form of such social algorithms, but it has a scalability problem with growing network size. If every node sends only one ant to each destination node and there are N nodes in the network, the total number of ants that are sent is N(N-1). In addition with increasing overhead for large networks, most of the ants are often lost for distant destinations. Furthermore, due to long travel times, ants that do arrive may carry outdated information. In this paper, a novel hierarchical algorithm is proposed to resolve this scalability problem of AntNet. The proposed Super-AntNet divides a large scale network into several small networks that are chosen based their internal traffic patterns. A separate ant colony is then assigned to each of these networks. A Super-Ant Colony is then responsible to coordinate data routing among the colonies. Performance of Super-AntNet is compared with those of standard AntNet as well as two other conventional routing algorithms such as Distance Vector (DV) and Link State (LS) in terms of end-toend delay, throughput, packet loss ratio, increased overhead, as well as jitter. Application to a 16-node network indicates the superiority of the proposed algorithm.

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