UAV-assisted Wireless Power Charging for Efficient Hybrid Coded Edge Computing Network

Abstract

With the ubiquitous sensing enabled by the Internet-of-Things (IoT), massive amount of data is generated every second, transforming the way we interact with the world. To manage big data and enable analytics at the edge of the network, large amount of computation power is required to perform the computation intensive tasks. However, the energy-constrained IoT devices are not able to perform the computation tasks without compromising the quality-of-service of the applications. In this paper, we propose a hybrid network in which users can offload their computation tasks to edge servers through coded edge offloading or perform local computation with the wireless power transfer derived from coalitions of unmanned aerial vehicles (UAVs) serving as mobile charging stations. We consider a two-level optimization approach where an optimal UAV coalitional structure that minimizes the network cost is formed. In the performance evaluation, we provide extensive sensitivity analyses to study the performance of the cost minimization approach amid varying network parameters.