Optimizing Object Storage Performance for Large File Uploading under Small-start Environments

Abstract

The rapid growth of educational video content has increased demands on storage systems in universities. Although MinIO offers a cost-effective object storage solution, its default configurations might not provide optimal upload performance. This study investigates optimization strategies for MinIO file upload performance under small-start educational environments, while examining the impact of chunk sizes and parallel upload numbers across different network conditions (including high latency variations and packet loss). Through systematic experiments, we found that optimal configurations vary by file size: 100MB files perform best with 8MB chunks and 16-32 parallel uploads, 1GB files achieve optimal performance with 64MB chunks and 16-32 parallel uploads, while 10GB files perform best with 128MB chunks and 16-32 parallel uploads. These settings showed an average 55% improvement in upload throughput under normal conditions, but a 400% improvement was demonstrated in high-latency environments, providing practical guidelines for educational institutions deploying object storage systems.