Load balancing is crucial in distributed systems, as it helps optimize the rational allocation of resources and improve overall system performance and reliability. But as the system scale continues to expand, load balancing technology also faces complexity issues. The load balancing algorithm increases computational overhead in large-scale systems, and the dynamic changes in load are highly unpredictable, making it difficult for the system to adjust load allocation in real time. In addition, system security also faces severe challenges such as malicious attacks and information leaks. To address these issues, optimization strategies include adaptive load balancing algorithms that can automatically adjust loads based on system status. Apply machine learning and deep learning models to predict load changes and improve scheduling accuracy. Combining blockchain technology to enhance the security of the load balancing process, avoiding malicious attacks and data leaks. Through these strategies, load balancing in distributed systems will be more efficient, secure, and scalable.

Buqin Wang. Research on Load Balancing Technology in Distributed System Architecture. International Journal of Multimedia Computing (2025), Vol. 6, Issue 1: 152-159. https://doi.org/10.38007/IJMC.2025.060115.

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