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 obtaine...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.展开更多
Particle swarm optimization algorithm is presented for the layout of ＂Integrate Circuit （IC）＂ design. Particle swarm optimization based on swarm intelligence is a new evolutionary computational tool and is success...Particle swarm optimization algorithm is presented for the layout of ＂Integrate Circuit （IC）＂ design. Particle swarm optimization based on swarm intelligence is a new evolutionary computational tool and is successfully applied in function optimization, neural network design, classification, pattern recognition, signal processing and robot technology and so on. A modified algorithm is presented and applied to the layout of IC design. For a given layout plane, first of all, this algorithm generates the corresponding grid group by barriers and nets＇ ports with the thought ofgridless net routing, establishes initialization fuzzy matrix, then utilizes the global optimization character to find out the best layout route only if it exits. The results of model simulation indicate that PSO algorithm is feasible and efficient in IC layout design.展开更多
基金Project supported by the Iranian Telecommunication Research Center
文摘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.
文摘Particle swarm optimization algorithm is presented for the layout of ＂Integrate Circuit （IC）＂ design. Particle swarm optimization based on swarm intelligence is a new evolutionary computational tool and is successfully applied in function optimization, neural network design, classification, pattern recognition, signal processing and robot technology and so on. A modified algorithm is presented and applied to the layout of IC design. For a given layout plane, first of all, this algorithm generates the corresponding grid group by barriers and nets＇ ports with the thought ofgridless net routing, establishes initialization fuzzy matrix, then utilizes the global optimization character to find out the best layout route only if it exits. The results of model simulation indicate that PSO algorithm is feasible and efficient in IC layout design.
