A Highly Efficient Resource Slicing and Scheduling Optimization Algorithm for Power Heterogeneous Communication Networks Based on Hypergraph and Congruence Entropy

Abstract

New services, such as distributed photovoltaic regulation and control, pose new service requirements for networks in the new power system. These requirements include low latency, high reliability, and large bandwidth. Consequently, power heterogeneous communication networks face the challenge of maintaining QoS while enhancing network resource utilization. Therefore, this paper puts forward a highly efficient optimization algorithm for resource slicing and scheduling in power heterogeneous communication networks. Our first step involves establishing an architectural description model of heterogeneous wireless networks for electric power based on hypergraph. This model characterizes complex dynamic relationships among service requirements, virtual networks, and physical networks. The system congruence entropy characterizes the degree of matching between the service demand and resource supply. An optimization problem is formed to maximize the system congruence entropy through dynamic resource allocation. To solve this problem, a joint resource allocation and routing method based on Lagrangian dual decomposition is proposed. These methods provide optimal solutions to the nodes and link mappings of service function chains. The results of our simulation demonstrate that the method proposed in this research enhances resource utilization and meets the QoS requirements of various services.