Dynamic Priority-based Adaptive Scheduling (DPAS) for Modern Operating Systems

Manas Kumar Yogi; Dwarampudi Aiswarya; Yamuna  Mundru

Abstract

Dynamic Priority-based Adaptive Scheduling (DPAS) is an innovative CPU scheduling algorithm designed to optimize system performance and resource utilization in modern computing environments. As computing systems become increasingly complex and diverse, traditional static scheduling algorithms often struggle to adapt efficiently to the dynamic nature of workloads. DPAS addresses this challenge by introducing a dynamic and adaptive approach to process prioritization and resource allocation. DPAS leverages real-time feedback, machine learning, and resource awareness to assign and adjust priorities for running processes. Unlike conventional schedulers with fixed priority schemes, DPAS continuously evaluates process behavior and resource utilization, making real-time adjustments to process priorities. This adaptability ensures that critical processes receive the necessary attention while preventing resource monopolization by any single task. Furthermore, DPAS incorporates adaptive time quantum allocation, energy-efficient scheduling, and security measures to strike a balance between responsiveness, energy conservation, and system security. It utilizes process grouping and tagging to accommodate different workload characteristics and requirements, enhancing both fairness and system efficiency. The DPAS algorithm represents a significant advancement in CPU scheduling, offering improved system responsiveness, resource management, and adaptability to diverse workloads. This abstract provides an overview of DPAS's key principles, highlighting its potential to enhance the performance and reliability of modern computing systems

Abstract

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