Enhancing Real-Time VR Scene Rendering with Optimized Task Path Scheduling Via Dynamic Programming Techniques (Informatica, 2025)
This article proposes a dynamic programming rendering path optimization algorithm for virtual reality scenes, which innovatively introduces real time feedback mechanism and sliding window resource scheduling, effectively improving rendering performance under multi scene concurrency conditions. Compared with traditional greedy, genetic, and local search methods, this method can achieve global optimal path selection and has been experimentally verified to achieve significant improvements in key indicators such as average frame rate and resource utilization. All experiments in this article were independently repeated 5 times, and the results were tested for variance and significance. This article proposes for the first time a dynamic programming path scheduling strategy that combines sliding window real time feedback, solving the problem of generating the global optimal path in multi task high concurrency environments. Compared with traditional heuristic and intelligent optimization algorithms, the proposed method significantly improves system stability and rendering performance, and has stronger practicality and promotional value. All variables and parameters are clearly defined in the Methods section, and the experimental process and evaluation criteria follow internationally recognized standards to ensure the reproducibility and rigor of the conclusions. The system conducted experiments on three types of virtual environments: typical city blocks, natural terrain, and indoor exhibition halls on the Unity platform. The results showed that after introducing dynamic programming, the average frame rate increased from 76.9 FPS to 86.3 FPS, GPU utilization increased from 85.1% to 91.6%, task completion rate increased from 92.8% to 98.2%, and rendering failure rate decreased from 3.1% to 0.9%. The solution significantly improves the real time performance, stability, and resource utilization efficiency of the system while ensuring image quality. Compared with traditional static scheduling methods, this method exhibits better response capability and scalability in multi task high concurrency environments, providing efficient technical support for complex virtual reality rendering tasks.