Latency Minimization for Intelligent Reflecting Surface-Assisted Cloud-Edge Collaborative Computing

In this article, we consider an intelligent reflecting surface (IRS)-aided collaboration cloud-edge system. The impact of an IRS on computational performance is investigated in this system. The objective is to minimize the weighted sum latency via jointly optimizing the computation offloading strategy, computation resource, the multi-user detection (MUD) matrix, and the IRS reflection matrix while maintaining communication and computation resource constraint. To deal with the formulated problem, we propose an alternatively iterative optimization algorithm by the aid of successive convex approximation (SCA) and semi-definite relaxation (SDR) technology. Based on this, we propose a joint scheme for the originally formulated nonconvex optimization. The benefits of using IRSs in the collaboration cloud-edge system are evaluated under various simulation environments. Finally, simulation results are provided to demonstrate the performance of the proposed algorithms.