基于信息年龄的无人机缓存和轨迹优化算法

AoI⁃Based Algorithms for UAV Caching and Trajectory Optimization

针对无人机(Unmanned aerial vehicle,UAV)辅助的内容分发系统中信息新鲜度的问题,提出了一种基于信息年龄(Age of information,AoI)的无人机缓存和轨迹优化算法,缓解了热点区域内用户请求长时间无法应答的问题。在无人机有限的缓存容量和覆盖范围内,通过优化地面用户成簇,无人机缓存策略以及轨迹,建立了所有用户获取请求内容的平均代价最小化问题。以无人机的覆盖半径作为成簇半径,采用AP(Affinity propagation)聚类算法,对地面用户进行分簇;将本文中的无人机缓存问题转化为01背包问题,采用动态规划(Dynamic programming,DP)算法进行求解;通过遗传算法(Genetic algorithm,GA)求解无人机的飞行轨迹。仿真结果表明,本文算法能够有效降低用户获得请求内容的平均代价。

Aiming at the problem of information freshness in unmanned aerial vehicle(UAV)assisted content distribution system,a UAV caching and trajectory optimization algorithm based on age of information(AoI)is proposed to alleviate the problem of long time unanswered user requests in hotspot areas.The problem of minimizing the average cost of accessing the requested content for all users is established by optimizing the ground user clustering,the UAV caching policy and the trajectory within the limited cache capacity and coverage of the UAV.The radius of coverage of UAVs is used as the radius of clustering,and the affinity propagation(AP)clustering algorithm is used to cluster the ground users.The UAV caching problem in this paper is transformed into the 01 backpacking problem,which is solved using the dynamic programming(DP)algorithm.UAV flight trajectories are solved by the genetic algorithm(GA).Simulation results show that the algorithm proposed in this paper can effectively reduce the average cost for users to obtain the requested content.