A wireless weak-connected network routing algorithm inspired by Physarum polycephalum

Abstract

Wireless weak-connected network (WWN) is a special self-organizing network, which can self-organize in an unstructured style and communicate with each other without infrastructure support. In this network, the link connection is weak and the topology is dynamic, which limits the performance of routing tasks. In order to address this issue, a novel Physarum-inspired routing algorithm (P-iRA) is proposed based on the intelligence and adaptability of Physarum polycephalum. Firstly, we construct a link capacity model for WWN via mapping the Physarum polycephalum network. Then, we design a next-hop selection strategy to obtain an optimal forwarding node in candidate set. Finally, we present a stochastic route strategy to achieve data transmission by virtue of finding the best routing path. Simulation results demonstrate that P-iRA improves approximately 47%, 34%, 56%, 20%, and 8% compared with Direct Delivery, Epidemic, First Contact, MaxProp, and Spray And Wait, respectively.