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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. 相似文献
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INTRODUCTION Communication network management ibecoming increasingly difficult due to thincreasing size, rapidly changing topology, ancomplexity of communication networks. Currenrouting algorithms cannot adequately tackle sucnetworks. Centralized algorithms have scalabilitproblems; static algorithms have trouble keepinup-to-date with network changes; and othedistributed and dynamic algorithms havoscillation and s… 相似文献
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