Bionic Optimization Based Stability and Congestion Aware Routing Algorithm for Airborne Highly Dynamic Network

Abstract

Airborne highly dynamic ad hoc UAV network has features of high node mobility, fast changing network topology, and complex application environment. The performance of traditional routing algorithms is so poor over aspects such as end to end delay, data packet delivery ratio, and routing overhead that they cannot provide efficient communication for multi-UAVs carrying out missions synergistically. A bionic optimization based stability and congestion aware routing algorithm—BSCAR algorithm—is proposed to solve these problems. This algorithm integrates biological behavior and dynamic source routing algorithm, which can sense the congestion level of routes and the stability of routes. Ant colony optimization algorithm and the mathematical model of Physarum's behavior exert effort in the process of route discovery and maintenance. The level of pheromone in routes is chosen as a standard to choose route and calculated by the mathematical model of Physarum's behavior. A new volatilization mechanism of pheromone is also introduced into the algorithm. Meanwhile, the algorithm can make adjustment to the variance of UAV formation to prevent the compromise of the network performance. The simulation results show that the BSCAR algorithm has superiority over traditional algorithms and it is dependable in battlefield environment.