Swarm Intelligence Inspired Multicast Routing: An Ant Colony Optimization Approach
EvoWorkshops '09 Proceedings of the EvoWorkshops 2009 on Applications of Evolutionary Computing: EvoCOMNET, EvoENVIRONMENT, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoINTERACTION, EvoMUSART, EvoNUM, EvoSTOC, EvoTRANSLOG
Distributed ant algorithm for inter-carrier service composition
NGI'09 Proceedings of the 5th Euro-NGI conference on Next Generation Internet networks
An initiative for a classified bibliography on G-networks
Performance Evaluation
Bibliography on G-networks, negative customers and applications
Mathematical and Computer Modelling: An International Journal
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This paper describes an experimental investigation of adaptive path discovery using genetic algorithms (GA). We start with the Quality of Service (QoS) driven routing protocol called "Cognitive Packet Network" (CPN) which uses Smart Packets (SPs) to dynamically select routes in a distributed autonomic manner based on the user's QoS requirements. We extend it by introducing GA at the source routers, which modifies and filters the paths discovered by CPN. The GA can combine paths that were previously discovered to create new untested but valid source-todestination paths, which are then selected on the basis of their "fitness". We implement this approach and the measurements which we have conducted on a network test-bed indicate that when the network's background traffic load is light to medium, the GA can result in improved QoS. When the background traffic load is high, it appears that the use of the GA may be detrimental to the QoS experienced by users as compared to CPN routing, because of the fact that the GA uses less timely state information in its decision making.