Adaptive swarm-based routing in communication networks
| Autor: | Xiao-run Li, Fan-jun Su, Yong Lü, Guang-zhou Zhao |
|---|---|
| Rok vydání: | 2004 |
| Předmět: |
Routing protocol
Static routing Behavior Animal Adaptive quality of service multi-hop routing Ants Computer science Distributed computing General Engineering Signal Processing Computer-Assisted Models Theoretical Adaptation Physiological Feedback Computer Communication Networks Routing domain Link-state routing protocol Artificial Intelligence Biomimetics Multipath routing Computer Science::Networking and Internet Architecture Animals Computer Simulation Destination-Sequenced Distance Vector routing Social Behavior Algorithms Hierarchical routing |
| Zdroj: | Journal of Zhejiang University SCIENCE. 5:867-872 |
| ISSN: | 1009-3095 |
| DOI: | 10.1631/jzus.2004.0867 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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