Optimal Service Placement for 6G Edge Computing With Quantum-Centric Optimization in Real Quantum Hardware

Abstract

Mobile edge computing (MEC) is emerging as a transformative enabler for the sixth-generation (6G) wireless networks. This letter investigates the potential of a quantum-centric optimisation approach for service placement in 6G MEC. Specifically, we formulate a mixed-integer binary programming problem that aims to minimise both service costs and delay by optimising service placement decisions, subject to constraints on service availability and the computing budget of edge servers. The formulated problem is NP-hard, making it computationally challenging for classical methods to solve. To address this, we develop a quantum-centric optimisation solution that efficiently finds optimal binary solutions for the problem, demonstrating potential for tackling medium-to-large-scale instances. Simulation results validate the effectiveness of the quantum-centric approach by showcasing the convergence pattern of the optimisation process on real quantum hardware and the associated increase in running time compared to a classical method.