COMPARATIVE ANALYSIS OF SCHEDULING ALGORITHMS IN HARD AND SOFT REAL-TIME SYSTEMS
Abstract
Real-time systems are vital in fields like aerospace, automotive, and healthcare, where timely and predictable task execution is crucial. These systems are classified as hard or soft real-time based on the severity of deadline misses. This paper compares three key scheduling algorithms—Rate Monotonic Scheduling (RMS), Earliest Deadline First (EDF), and Least Laxity First (LLF)—to evaluate their performance under both types of real-time constraints. Through simulation and metrics like deadline miss ratio, CPU utilization, and response time, the study finds that EDF excels in soft real-time settings with dynamic workloads, RMS ensures predictability in hard real-time systems, and LLF, despite its theoretical optimality, is less practical due to high complexity. These findings guide developers in choosing suitable scheduling strategies based on application needs
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