Abstract:

Efficient routing algorithm is the key to guaranteeing the performance of delay-tolerant network ( DTN) . In order to improve the efficiency of DTN routing algorithms,a routing algorithm based on gradient and fuzzy neural network decision is proposed. This algorithm improves the vector for network description by adopting the own information of a node and the link state information between two nodes,which enables a comprehensive description of the network. Moreover,it provides accurate measurement for routing decisions by combining the dynamic average of limited historical information with an accurate prediction and by adaptively maintaining the components of the vector. In addition,fuzzy RBF ( Radical Basis function) neural network is employed in the algorithm for routing decision so as to result in an intelligent routing decision-making process,and,the successful multi-hop packet transmission probability is used to guide the forwarding along the gradient,thus improving the packet forwarding efficiency. Simulated results indicate that the proposed algorithm achieves better performance than epidemic and context-aware routing algorithms under the same network conditions.

Key words: delay-tolerant network, routing algorithm, gradient, fuzzy neural network