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With the explosive increment of computation requirements, the multi-accessedge computing (MEC) paradigm appears as an effective mechanism. Besides, asfor the Internet of Things (IoT) in disasters or remote areas requiring MECservices, unmanned aerial vehicles (UAVs) and high altitude platforms (HAPs)are available to provide aerial computing services for these IoT devices. Inthis paper, we develop the hierarchical aerial computing framework composed ofHAPs and UAVs, to provide MEC services for various IoT applications. Inparticular, the problem is formulated to maximize the total IoT data computedby the aerial MEC platforms, restricted by the delay requirement of IoT andmultiple resource constraints of UAVs and HAPs, which is an integer programmingproblem and intractable to solve. Due to the prohibitive complexity ofexhaustive search, we handle the problem by presenting the matching game theorybased algorithm to deal with the offloading decisions from IoT devices to UAVs,as well as a heuristic algorithm for the offloading decisions between UAVs andHAPs. The external effect affected by interplay of different IoT devices in thematching is tackled by the externality elimination mechanism. Besides, anadjustment algorithm is also proposed to make the best of aerial resources. Thecomplexity of proposed algorithms is analyzed and extensive simulation resultsverify the efficiency of the proposed algorithms, and the system performancesare also analyzed by the numerical results.

Hierarchical Aerial Computing for Internet of Things via Cooperation of HAPs and UAVs