Route Discovery in Flying Ad-Hoc Network Based on Bee Colony Algorithm

Flying Ad-Hoc Networks(FANETs) has the characteristics of multi-hop, self-organization and no center of the traditional ad-hoc network, and also has the characteristics of high-speed node movement, high-speed changes of topology and three-dimensional motion space. Bee colony algorithm is a kind of bionic intelligent optimization algorithm. The communication principle and honey collecting behavior of the bee colony can simulate the route discovery process in the ad hoc network, so it can be applied to the route discovery of the ad hoc network. However, the link stability of route discovery cannot be guaranteed due to the high-speed topology change caused by unmanned aerial vehicle (UAV) nodes moving at high speed. Because Bee colony algorithm cannot be directly applied to FANETs, this paper introduces the variable of link expiration time predicted by the extended Gaussian Markov mobility model into the fitness function of the bee colony algorithm, and then uses bee colony algorithm for the route discovery of FANETs in the three-dimensional environment. Through experimental simulation, the method improves the packet delivery rate and reduces the end-to-end delay.