Fuzzy system for adaptive network routing
Ajay Pasupuleti, Athimootil V. Mathew, Nirmala Shenoy, Soheil A. Dianat · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2002
In this paper we propose an adaptive routing using a fuzzy system. The traffic in the network is re-routed to nodes, which are less congested, or have spare capacity. Based on a set of fuzzy rules, link cost is dynamically assigned depending upon the present condition of the network. Distance vector algorithm, which is one of the shortest path routing algorithms is used to build the routing tables at each node in the network. The proposed fuzzy system determines the link cost given the present congestion situation measured via the delays experienced in the network and the offered load on the network. Delay in the links, was estimated by the time taken for the test packets to travel from the node to its neighbors. The delay information collected by the test packets and the number of packets waiting in the queue, are the two inputs to the fuzzy system. The output of the fuzzy system is the link cost. This algorithm was applied on a simulated NSFNET, the USA backbone, as well as to another test network with a different topology. Robustness and optimality of the proposed fuzzy system was tested by simulating various types of load patterns on these networks. Simulation studies showed that the performance of the fuzzy system was very close to or better than the best performance of the composite metric under different load conditions and topologies.