Distributed Energy Management for Multiuser Mobile-Edge Computing Systems With Energy Harvesting Devices and QoS Constraints

Mobile-edge computing (MEC) has evolved as a promising technology to alleviate the computing pressure of mobile devices by offloading computation tasks to MEC server. Energy management is challenging since the unpredictability of the energy harvesting (EH) and the quality of service (QoS). In this paper, we investigate the problem of power consumption in a multiuser MEC system with EH devices. The system power consumption, which includes the local execution power and the offloading transmission power, is designated as the main system performance index. First, we formulate the power consumption minimization problem with the battery queue stability and QoS constraints as a stochastic optimization programming, which is difficult to solve due to the time-coupling constraints. Then, we adopt the Lyapunov optimization approach to tackle the problem by reformulating it into a problem with relaxed queue stability constraints. We design an online algorithm based on the Lyapunov optimization method, which only uses current states of the mobile users and does not depend on the system statistic information. Furthermore, we propose a distributed algorithm based on the alternating direction method of multipliers to reduce the system computational complexity. We prove the optimality of the online algorithm and the distributed algorithm using rigorous theoretical analysis. Finally, we perform extensive trace-simulations to verify the theoretical results and evaluate the effectiveness of the proposed algorithms.