Swarm-Inspired Routing Algorithms for Unstructured P2P Networks

Abstract

Due to extreme complexity in nowadays networks, routing becomes a challenging task. This problem is especially delicate in unstructured P2P networks, as there is neither a global view on the network nor a global address mapping. Although different conventional solutions are commercially available, swarm-intelligent approaches are promising in case of frequently changing conditions in P2P networks. In this article, an approach inspired by Dictyostelium discoideum slime molds and bees with distributive and autonomous properties is proposed. Both bio-mechanisms are “tailored” for routing in unstructured P2P systems, resulting in swarm-inspired routing algorithms, SMNet and BeeNet. They are compared with three swarm-based routing algorithms and two conventional approaches. The benchmarks include parameter sensitivity-, comparative-, statistical- and scalability-analysis. SMNet outperforms the other algorithms in the comparative analysis regarding the average data packet delay, especially for bigger network sizes and data packet traffic levels. Both algorithms show good scalability.