Resource management for computational offload in MEC networks with energy harvesting and relay assistance

In mobile edge computing (MEC) networks, the integrated application of energy harvesting (EH) and relay cooperation is a promising technology, which ensures the real-time performance of the system and computing power supply. Relay and EH cooperation also expand communication range and extend the battery life of energy-constrained devices. However, in wireless powered and relay-assisted MEC networks, it is challenging to jointly dispatch energy, and computing resources to coordinate heterogeneous performance requirements. To fill this gap, this paper examines the fundamental compromise between utility energy efficiency (UEE) and stable queue length in wireless powered and relay-assisted MEC network systems, and the amount of data transferred for each unit of energy is called UEE. The data queue and energy queue models are introduced and the constraints of stability of two queues in long term are included in the formulated problem. To tackle the fractional and nonconvex optimization problems, the Dinkelsbach method is utilized. Since optimization problems change from time to time and the long-term averaging queue stability is considered, the Lyapunov optimization theory is introduced to convert the non-convex problems into the solvable one. An online resource offloading allocation algorithm is proposed to determine the solution. In addition, the algorithm implements the control parameter V to achieve the compromise between UEE and stable queue length, while the impact of various parameters are also revealed on system performance.