Adaptive swarm-based routing in communication networks.
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.
Lu
Yong
Y
College of Electrical Engineering, Zhejiang University, Hongzhou 310027, China. lvyongs@sohu.com
Zhao
Guang-Zhou
GZ
Su
Fan-Jun
FJ
Li
Xiao-Run
XR
D000222:Adaptation, Physiological / Q000502:physiology; D000465:Algorithms; D000818:Animals; D001000:Ants; D001185:Artificial Intelligence; D001522:Behavior, Animal / Q000502:physiology*; D032701:Biomimetics / Q000379:methods*; D003195:Computer Communication Networks; D003198:Computer Simulation; D005246:Feedback; D008962:Models, Theoretical; D012815:Signal Processing, Computer-Assisted; D012919:Social Behavior