Resource-Optimized Multiarmed Bandit-Based Offload Path Selection in Edge UAV Swarms

This paper looks into the problem of a decentralized data offloading within an edge unmanned aerial vehicle (UAV) swarm to mitigate the complexities of a single UAV continually generating and processing large application-specific data. The mobile edge UAVs considered here are multirotor types having constrained energy and processing power, which makes long-term handling of large data volumes impossible for standalone UAVs. The load mitigation is carried out by offloading data from a source UAV to other swarm members with sufficient energy and processing requirements. In this paper, we focus on selecting the most optimal multihop path through the UAVs concerning available energies and processing resources, which can survive the duration of the data offload between the source and a target UAV. We formulate a multiarmed bandit-based offload path selection scheme, which selects the most energy and processing optimized multihop path between a source and a target UAV. Upon comparison of our scheme against the naive shortest path approach, we observe that our approach results in significant savings of collective network energies, even for long operational durations.