摘要
We propose a novel approach called adaptive fuzzy ant-based routing (AFAR), where a group of intelligent agents (or ants) builds paths between a pair of nodes, exploring the network concurrently and exchanging obtained information to up-date the routing tables. Routing decisions can be made by the fuzzy logic technique based on local information about the current network state and the knowledge constructed by a previous set of behaviors of other agents. The fuzzy logic technique allows multiple constraints such as path delay and path utilization to be considered in a simple and intuitive way. Simulation tests show that AFAR outperforms OSPF, AntNet and ASR, three of the currently most important state-of-the-art algorithms, in terms of end-to-end delay, packet delivery, and packet drop ratio. AFAR is a promising alternative for routing of data in next generation networks.
We propose a novel approach called adaptive fuzzy ant-based routing （AFAR）, where a group of intelligent agents （or ants） builds paths between a pair of nodes, exploring the network concurrently and exchanging obtained information to update the routing tables. Routing decisions can be made by the fuzzy logic technique based on local information about the current network state and the knowledge constructed by a previous set of behaviors of other agents. The fuzzy logic technique allows multiple constraints such as path delay and path utilization to be considered in a simple and intuitive way. Simulation tests show that AFAR outperforms OSPF, AntNet and ASR, three of the currently most important state-of-the-art algorithms, in terms of end-to-end delay, packet delivery, and packet drop ratio. AFAR is a promising alternative for routing of data in next generation networks.
基金
Project supported by the Iranian Telecommunication Research Center
