Joint Multi-UAV Path Planning and LoS Communication for Mobile-Edge Computing in IoT Networks With RISs

This article addresses a joint path planning and communication scheduling problem for a team of unmanned aerial vehicles (UAVs) equipped with central processing units and performing computing tasks for Internet of Things (IoT) devices located on uneven terrain. On such terrains, the Line of Sight (LoS) between a UAV and a ground IoT device may be blocked by buildings or mountains. In this article, reconfigurable intelligent surfaces (RISs) are deployed on the ground to improve wireless communication between UAVs and IoT devices. Computing tasks and their results can be sent to and from UAVs either directly or via RIS-reflected paths. The objective is to develop a joint multi-UAV path planning/transmission scheduling algorithm that maximizes the number of computing tasks successfully and timely performed by the UAVs and transmitted back to the IoT ground devices and minimizes the total energy consumption of the UAVs. An effective path planning algorithm for this optimization problem is proposed. A mathematically rigorous proof of its asymptotic optimality is given. The developed algorithm is computationally effective and easily implementable in real time. Computer simulations and comparisons with other effective methods prove the effectiveness of the developed approach.

Automated summary

This article proposes a joint path planning and communication scheduling problem for a team of unmanned aerial vehicles (UAVs) performing computing tasks for IoT devices on uneven terrain. Reconfigurable intelligent surfaces (RISs) are deployed to improve wireless communication between UAVs and IoT devices. The objective is to develop an algorithm that maximizes computing tasks performed by the UAVs and minimizes their energy consumption. An effective path planning algorithm is proposed and its asymptotic optimality is mathematically proven.