Abstract: Aiming at the routing optimization problem of dynamic source routing（DSR） protocol, combining to the characteristics of UAV network, an optimization method of DSR protocol for UAV Ad Hoc network based on firefly algorithm is proposed. The method utilizes the energy consumption, buffer congestion, movement and transmission loss of the node to construct the fitness function of the firefly comprehensively, measure the fluorescence brightness of fireflies according to fitness function, and comprehensively optimizes the routing algorithm of the DSR protocol, through the routing search process in the stages of firefly initialization, firefly movement and fluorescent value update, to solve the problem of poor stability of the UAV ad hoc network transmission link. The OPNET simulation tool is used to evaluate various indicators of the DSR protocol before and after optimization. The simulation results show that compared with the traditional method, the optimization method increases the receiving rate of traffic by 33.8%, the average of end-to-end delay is reduced by 73.91%, the sending rate of routing load is reduced by 44.99%, the receiving rate of routing load is reduced by 37.55%, and the packet loss rate is reduced by 68.01% in the scenario of UAV. The proposed optimization method of DSR protocol can optimize network performance and routing overhead balanced, and can provide stable and efficient routing services for the UAV Ad Hoc network.

Key words: UAV Ad Hoc network, dynamic source routing（DSR） protocol, firefly algorithm, routing overhead

摘要： 针对DSR协议的路由优化问题，结合无人机网络的特点，提出一种基于萤火虫算法的无人机自组网DSR协议优化方法。该方法综合利用节点的能量消耗、缓冲拥塞、移动速率和传输损耗构建萤火虫的适应度函数，根据适应度函数来衡量萤火虫的荧光亮度，通过萤火虫初始化、萤火虫移动和更新荧光值等阶段的路由搜索过程，对DSR协议的路由算法进行综合优化，解决无人机自组网传输链路稳定性不佳的问题。使用OPNET仿真工具评估了优化前后DSR协议的各项指标，仿真结果表明，相比传统方法，优化方法在无人机场景下，业务接收速率提高了33.8%，平均端到端时延降低了73.91%，路由负荷发送速率减少了44.99%，路由负荷接收速率减少了37.55%，丢包率减少了68.01%。所提方法均衡优化了无人机自组网的网络性能和路由开销，可以为无人机自组网提供稳定高效的路由服务。

关键词: 无人机自组网, 动态源路由（DSR）协议, 萤火虫算法, 路由开销