Trinity Equilibrium Algorithm for Computing Network Digital Twin

The integration of Network Digital Twin (NDT) with 6 G and future networks is a burgeoning field, where the optimization of computing resources is paramount. This paper introduces the Trinity Equilibrium Algorithm (TEA), a novel approach to balance the fulfillment of Computing Service Requests (CSRs), the scheduling of Computing Resources (CRs), and the minimization of Energy Consumption (EC) within a Computing Network Digital Twin (CNDT). TEA is designed to maximize overall revenue by considering the operational costs of CNDT and the revenue nature of computing services. The algorithm addresses the inefficiencies of traditional computing resource optimization by integrating NDT capabilities to dynamically adjust to service quality expectations and energy costs. A numerical evaluation demonstrates TEA's superiority over contrast algorithms in generating higher revenue and lower energy consumption across various test scenarios. The findings underscore TEA's potential in enhancing the performance of future networks by optimizing resource allocation and energy efficiency.