Optimization of Satellite Distance Education Network Resource Scheduling for Remote Areas

Education plays a crucial role in driving personal development and societal progress. In the digital age, satellite-based remote open education for remote areas has encountered significant opportunities for development. However, with limited satellite network bandwidth, resource allocation efficiency is insufficient to handle high-concurrency task requests, especially with repeated requests for the same tasks, preventing satellite remote education from fully realizing its potential. To address this issue, this paper proposes a resource scheduling method for satellite-based remote education networks, including a task merging mechanism and a multivariate-initialized particle swarm-genetic hybrid algorithm for optimized scheduling. Experimental results show that, compared to baseline algorithms, the proposed method improves task completion rate by at least 10% per unit time and achieves lower resource consumption, with maximum bandwidth utilization efficiency. Therefore, this algorithm enhances the performance of satellite network educational resource scheduling, optimizes task scheduling and resource allocation strategies, and provides effective support for remote education in underserved areas.