CoSMoS: Cooperative Sky-Ground Mobile Edge Computing System

In this correspondence, we study a tethered unmanned aerial vehicle (TUAV)-assisted mobile edge computing (MEC) system, in which tasks of several ground mobile users (MUs) are served by ground edge cloud (GEC) with superior computing capability and poor communication links and TUAV-mounted cloudlet with lower computing capability and better communication links. We aim to minimize weighted-sum system delay of MUs by jointly optimizing TUAV position, time slot allocation, and task splitting ratio. We first decompose the optimization problem into three subproblems, and then to solve non-convex subproblem related to TUAV position, we reformulate it by the first-order Taylor series approximation and apply the successive convex approximation (SCA) method. Then, we tackle the overall problem by applying the alternative optimization algorithm. Numerical results verify that our proposed cooperative sky-ground mobile edge computing system (CoSMoS) algorithm can achieve a better performance than other benchmark schemes.

Automated summary

This study focuses on a tethered unmanned aerial vehicle (TUAV)-assisted mobile edge computing (MEC) system to minimize the system delay of multiple ground mobile users (MUs). By optimizing TUAV position, time slot allocation, and task splitting ratio, the proposed CoSMoS algorithm outperforms benchmark schemes through decomposition, approximation, and alternative optimization techniques.