Software-defined network based resource allocation in distributed servers for unmanned aerial vehicles

Unmanned Aerial Vehicles (UAVs) are gaining a lot of popularity among research communities as well as various service providers. The UAVs deployed in mission-critical applications need to perform tasks with very less delay. They also need to conserve their on-board battery power so that their flight time can be increased. To accomplish both of these purposes UAVs may offload their computation and energy intensive jobs to some remote place like cloud servers, edge servers or another UAV node having abundant computing and energy resources. This paper proposes a Software Defined Networking (SDN) architecture to provision hybrid computing resources in an efficient manner. The proposed SDN architecture uses a greedy algorithm to satisfy Quality of Service (QoS) requirements of UAV's applications. The proposed method further leverages a simulated annealing based approach to minimize average latency of the applications and average energy consumption of UAV nodes. Simulation results illustrate a substantial improvement in average latency and energy consumption using proposed mechanism in contrast to processing applications on UAV node itself or offloading it only to the cloud.