Optimization of cloud data transfer using TOST processes and priority scheduling
Rekha R Nair, Tina Babu, Gayathri Ramasamy, Viraj Kisan Daule, Samrudhi S. Kamble, Xiaohui Yuan · 2025
Cloud computing has revolutionized data storage and processing, but efficient data transfer remains a challenge as volumes grow exponentially. This study addresses this issue by proposing an optimized approach for cloud data transfer using Time-Ordered Scheduling Technique (TOST) processes and priority scheduling. Traditional methods struggle with increasing data loads and user demands, necessitating more efficient solutions. Our strategy integrates cloud storage, TOST, and priority scheduling to improve transfer processes and meet modern computing needs. Implemented in Python, the model simulates cloud features with upload and download operations, employing priority-based execution and First-Come-First-Serve (FCFS) for equal-priority processes. The system provides detailed insights into execution time and energy consumption. Results demonstrate significant improvements in average execution time and energy efficiency. This approach offers a foundation for enhancing resource management and performance evaluation in cloud environments, with potential for further optimization through dynamic allocation and real-time monitoring.