This study focuses on the in-depth exploration of load balancing technology for distributed systems, and constructs a set of dynamic load balancing technology framework based on numerical analysis. The framework cleverly integrates the virtual network card technology, dynamic feedback strategy and ant colony optimization algorithm to achieve efficient scheduling and balanced allocation of computing resources in a distributed environment. The virtual NIC technology adopted in the study virtualizes the physically redundant and complex network structure into a logical single network, which greatly simplifies the development of upper-layer applications, and the optimized virtual NIC scheme also shows significant advantages in terms of the system failure switching speed and load distribution effect. In view of the dynamic characteristics of the system, we have constructed a comprehensive evaluation system that includes multi-dimensional indicators such as processor utilization, memory usage, I/O throughput and network traffic. The dynamic feedback load balancing strategy significantly improves the system resource distribution, significantly improves the storage and network throughput, and effectively reduces the service response latency. The virtual server load balancing algorithm based on ant colony optimization proposed in the study innovatively models the load balancing problem as a minimization generalized allocation problem. The group intelligence feature is utilized to find the near-optimal resource allocation scheme, and the experimental data verifies that the algorithm is effective in reducing the load shifting overhead and realizing the dynamic balance among nodes. The technical framework proposed in this paper successfully overcomes many technical bottlenecks faced by traditional load balancing methods in complex distributed environments, significantly improves the overall performance of the system and resource utilization efficiency, and provides a reliable guarantee for the stable and efficient operation of distributed systems.
