Abstract:
This paper presents the design and implementation of a custom scheduling
algorithm that integrates operating system (OS) principles with computer
organization and architecture (COA) fundamentals, supported by data-structure (DS)-
based signal handling mechanisms. The proposed scheduler emphasizes efficient
task management through asynchronous event-driven signal processing utilizing
queues and stacks. The research explores the interaction between OS-level software
scheduling and hardware-level architectural components, such as instruction cycles,
pipeline stalls, cache management, and interrupt control. Experimental evaluations
were conducted using simulated workloads to analyze latency, throughput, and
processor utilization under varying loads. The proposed scheduler demonstrates
notable improvements in responsiveness and CPU efficiency compared to traditional
scheduling algorithms. Furthermore, the signal-handling mechanism improves
concurrency and reliability in real-time and multitasking environments. This paper
also provides a detailed comparison with existing models, along with theoretical
analysis and performance outcomes that establish the proposed model as a
balanced and optimized scheduling framework.