A Hybrid SNMP–STP-Based Framework for Topology Discovery and Energy Optimization in Heterogeneous Power Information Networks

Abstract

The rapid development of new power systems and the pursuit of "dual-carbon" goals present power information systems with new challenges: diverse terminal access, dynamic network topologies, and complex load distributions. Traditional topology management and energy efficiency strategies fall short of the requirements for managing heterogeneous networks, VLAN isolation, and dynamic access efficiently. This study proposes an adaptive weight SNMP-STP hybrid topology discovery and energy-efficiency optimization framework that integrates an improved Simple Network Management Protocol (SNMP) with an enhanced Spanning Tree Protocol (STP). The algorithm first performs SNMP scanning to identify device vendor types, response delays, and MIB completeness, which are used to calculate initial weights. It then concurrently collects SNMP-layer routing and port status information along with STP link connectivity data, and constructs a topology matrix based on weight fusion. During operation, weights are dynamically updated, giving priority to high-weight vendor parsing results while incorporating MIB verification and STP status compensation to ensure topology integrity. In parallel, a correlation model between topology parameters and energy consumption is established, enabling coordinated topology recognition and energy-efficiency optimization. Experiments were conducted in a multi-vendor heterogeneous network environment, including 15 routers, 32 switches, and 50 servers. Results demonstrate that the framework achieves 96% topology identification accuracy, a link misjudgment rate below 4%, and a topology update latency of only 150 ms, significantly outperforming traditional methods. The energy-efficiency optimization strategy, based on redundant link sleep and dynamic load balancing, reduced overall system energy consumption by over 30%, with switch energy savings reaching 44.4%. These findings indicate that integrating topology information with energy-efficiency modeling not only enhances system performance and resource utilization but also provides a feasible approach for building low-carbon, efficient, and secure next-generation power information systems, highlighting both theoretical and engineering significance.