Lyapunov optimization

Stability (learning theory)

Lyapunov equation

Mathematics

Algorithm

Distributed computing

Mathematical optimization

Geodesy

Machine learning

Enhanced Data Rates for GSM Evolution

Optimization problem

Benchmark (surveying)

Artificial intelligence

Geography

Lyapunov exponent

Chaotic

Mobile edge computing

Computer science

Real-time computing

IEEE Transactions on Wireless Communications

Unmanned aerial vehicle (UAV)-enabled mobile edge computing (MEC) has recently emerged as a cost-effective solution to provide computation service to distributed devices in the absence of terrestrial infrastructure. In this paper, we consider a UAV-enabled MEC system serving multiple energy harvesting (EH) devices, where the energy and task data arrive at the users stochastically. Without any future knowledge of task data and energy arrivals, our objective is to design an online algorithm to jointly optimize the UAV energy and task processing rate, meanwhile satisfying the long-term data queue stability. We formulate the problem as a multi-stage stochastic programming and propose an online algorithm, named PLOT, based on perturbed Lyapunov optimization technique. In particular, PLOT resolves the coupling effect of sequential control actions, and converts the stochastic problem into per-slot deterministic optimization problem. For each per-slot problem, we design a low-complexity algorithm to solve it. We show that the PLOT algorithm can derive a feasible solution to the original problem and achieve an <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$[O(1/V),O(V)]$ </tex-math></inline-formula> trade-off between the system cost and the data queue length. Simulation results justify our analysis and demonstrate that the PLOT algorithm achieves better performance in terms of system utility and maintains queue stability that is not achieved by other benchmark methods.

Dynamic Offloading and Trajectory Control for UAV-Enabled Mobile Edge Computing System With Energy Harvesting Devices