Abstract
Because of the huge growth in the number of Internet users, data packets flowing in communication networks have also growth, and as a result, some packets can become congested in communication networks. If packet congestion occurs in a communication network, the packets are trapped in congested nodes, and then the transmission of these packets to their destinations is delayed. Further, the packets could be removed from the communication network in the worst case. To overcome these undesirable problems, an efficient routing strategy based on mutually connected neural networks has been proposed. This neural-based routing strategy shows good performance for regular topological communication networks. However, the performance of the routing strategy declines in irregular topological communication networks. To improve its performance for irregular topological communication networks, we propose in this paper a new neural-based routing strategy with the transmission information. Numerical experiments show that the performance of the proposed strategy is enhanced by the newly added transmission information as compared to the conventional routing strategies. Further, the proposed routing strategy shows better performance for other topological complex communication networks.
