Collaborative task offloading and resource allocation optimization for intelligent edge devices

Abstract

In order to deal with the increasingly scarce computing resources, a cooperative edge computing scheme was proposed, which makes full use of the idle resources among users to improve the overall data processing performance.To maximize the user utility, the target problem was formulated as an MINLP (mixed integer non-linear programming), and a learning-optimization-integrated method was proposed to jointly optimize the resource allocation and user offloading decisions.Simulation results show that the proposed scheme can produce a near-optimal solution in sub-second and effectively improve the system utility at least 85.4% compared to the considered benchmark methods.

Keywords

• mobile edge computing
• utility maximization
• convex optimization
• reinforcement learning