An Evolutionary Approach to Distance Vector Routing

Distance vector routing algorithms operate by having each router maintain a table giving the best known distance to each destination and which line to use to get there. Genetic algorithms are search algorithms based on mechanics of natural selection and natural genetics. To overcome some of the problems of traditional adaptive routing techniques genetic algorithms can be used. GA’s have the capacity of solving complicated solutions in practical systems. Hardware implementation of GA is very fast and it is not sensitive to network size. GA’s are very flexible as quality of solution can be adjusted as a function of population size. GA hardware scale well to network that may not even fit in memory. Due to the above reasons GA offers very promising solutions to many problems. In the proposed work parameters used for calculating the routes are hop count and queue length. For better performance of any network, path which is selected for transmission should be such that path with lowest hop count and shortest queue length is selected. Various parameters i.e. throughput, packet delivery ratio, delay, hop count etc. are analyzed to see the performance of the network with and without using GA in distance vector routing.