The optimization of thread management in operating systems is essential to improve the performance of multithreading-based applications. This study analyzes various techniques to enhance thread management efficiency, including thread pooling, dynamic scheduling, load balancing, and synchronization contention reduction. Experimental results indicate that thread pooling reduces overhead by reusing threads, while dynamic scheduling improves multitasking responsiveness by prioritizing urgent tasks. Load balancing ensures equitable workload distribution across processor cores, minimizing execution time. Furthermore, reducing synchronization contention using mechanisms like semaphores decreases thread waiting time, thereby boosting application performance. These optimizations enable modern operating systems to efficiently utilize multi-core architectures, improving speed, responsiveness, and user experience. This research highlights the importance of thread management optimization as a foundational step towards developing adaptive and scalable operating systems for future complex and data-intensive applications.
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