Planning Computation Offloading on Shared Edge Infrastructure for Multiple Drones

Drones are used in a wide range of applications, which may involve computationally-demanding data processing tasks during the missions. While such heavy tasks can be offloaded to nearby edge-servers, this may not always be feasible due to capacity limitations and contention. In this case, it is important to have a fair allocation of server resources to drones. We propose a heuristic for this problem, and evaluate it though simulation experiments using realistic performance parameters. We show that the mission time can be greatly reduced, by up to 33% (16 min) compared to the default where drones perform all computations onboard, while evenly balancing the benefits of offloading among drones with different missions.