Coalition Game-assisted Joint Resource Optimization for Digital Twin-assisted Edge Intelligence

Abstract

In order to cope with the performance loss caused by temporal-spatial resource dispersion of edge service providers (ESPs) in edge intelligence-driven industrial Internet of Things system,this paper proposes a coalition game-based joint resource allocation scheme assisted by digital twin.Firstly,we design a transferable utility coalition game model consisting of a primary problem of utility maximization of edge devices and a sub-problem of utility maximization of ESPs under the constraints of ESPs' resource limitation including bandwidth,computation and cache capabilities.Then,the original multi-objective problem is transformed into one convex problem with linear constraints.Finally,an alternative optimization method is leveraged for solving the equivalent optimization problem.Simulation results show the effectiveness of the proposed coalition game-assisted scheme for improving system resource utilization,with greater promotion as the number of ESPs grows.This proves that the proposed scheme is more adaptable to large scale edge intelligence systems,compared with traditional Nash equilibrium and grand coalition method.

Keywords

• industrial internet of things|edge intelligence|digital twin|coalition game|joint resource allocation