Abstract
High-speed transmission rates bring forward their specific issues influencing the network design. To cope with high-speed networks the routing algorithms should give a fast decision. The conventional routing algorithms of slow-speed networks are generally inapplicable for high-speed networks. The traffic control methods for high-speed networks must be adaptive, flexible, and intelligent for efficient network management. The intelligent routing algorithms based on Genetic Algorithms (GA), Neural Networks (NN), and Fuzzy Theory (FT) can prove to be efficient in high speed networks. In this paper, we propose a new adaptive routing method called ARGA (Adaptive Routing using GA). In the ARGA method, the network is modeled by a tree and the tree is reduced in the part where there are the same routes. In the reduced tree model, the tree junctions are represented by individual genes. By using a novel gene coding method, the chromosomes have the same length, which results in easy genetic operations and a fast routing can be achieved. Performance evaluation via simulations show that the ARGA method has a faster routing decision compared with the Genetic Load Balancing Routing (GLBR) method.
