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Service Caching Based Task Offloading and Resource Allocation in Multi-UAV Assisted MEC Networks

Service caching refers to caching the necessary programs or the related databases for executing computational tasks at edge servers, which has been considered to save both computation and communication resources in mobile edge computing (MEC) systems. In this paper, we investigate computation service caching in a multi-unmanned aerial vehicle (UAV) assisted MEC system, where each UAV equipped with an edge server can cache some programs in advance to execute the tasks offloaded from the ground devices. Aiming at minimizing the total latency of all devices, we formulate a joint service caching, task offloading, resource allocation and UAV placement optimization problem, while guaranteeing the task delay requirement and the energy budget of all devices and UAVs. The problem is a mixed integer non-linear programming problem, and we decouple it into two sub-problems, i.e., a joint service caching, offloading decision and resource allocation problem and a UAV placement problem, and then propose an iterative algorithm to obtain the joint solution. Simulation results reveal that our proposed algorithm can achieve higher performance compared with other baselines in terms of reducing system latency.