Abstract Swarm intelligence inspired by the social behavior of ants boasts a number of attractive features, including adaptation, robustness and distributed, decentralized nature, which are well suited for routing in modern communication networks. This paper describes an adaptive swarm-based routing algorithm that increases convergence speed, reduces routing instabilities and oscillations by using a novel variation of reinforcement learning and a technique called momentum. Experiment on the dynamic network showed that adaptive swarm-based routing learns the optimum routing in terms of convergence speed and average packet latency.
LÜ Yong, ZHAO Guang-zhou, SU Fan-jun, LI Xiao-run. Adaptive swarm-based routing in communication networks. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2004, 5(7): 867-872.
Seyed Javad MIRABEDINI, Mohammad TESHNEHLAB, M. H. SHENASA, Ali MOVAGHAR, Amir Masoud RAHMANI. AFAR: adaptive fuzzy ant-based routing for communication networks[J]. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 2008, 9(12): 1666-1675.
