Investigating Process Scheduling Techniques for Optimal Performance and Energy Efficiency in Operating Systems

Abstract

Process scheduling is a critical component of operating systems, determining the order in which processes are allocated CPU time. Traditionally, scheduling algorithms have aimed to optimize performance metrics such as throughput, latency, and CPU utilization. However, with increasing emphasis on energy efficiency in modern computing, particularly in mobile devices and data centers, energy consumption has become a key factor in evaluating scheduling strategies. This survey explores various process scheduling algorithms, focusing on their impact on energy efficiency. A comparative analysis is provided between traditional algorithms, like the Linux Completely Fair Scheduler (CFS), and energy-aware alternatives such as the Energy Fair Scheduler (EFS), which extends CFS by incorporating energy considerations in the scheduling process. Trade-offs in performance, including run-time and waiting time, are discussed, with case studies evaluating the effectiveness of energy-efficient schedulers. Performance metrics such as total energy consumption and CPU utilization are analyzed to highlight EFS's potential in reducing energy overheads while maintaining system throughput. Findings suggest that energy-aware scheduling algorithms, like EFS, can significantly improve energy efficiency without compromising performance, providing promising solutions for both battery-powered devices and energy-intensive server environments. Future directions in energy-efficient process scheduling research emphasize the need for dynamic energy management in modern operating systems.