Analysis of Dynamic and Static Scheduling Algorithms in Soft Real-Time System with Its Implementation

Abstract

The earliest deadline first (EDF) and least slack time first (LST) are dynamic schedulers in real-time system. It chooses the priority of the processes grounded on deadline and slack time correspondingly. The process which has the shortest deadline and smallest slack time will have more priority in EDF and LST. EDF and LST are more appropriate for scheduling of process in soft real-time operating system (RTOS). The rate monotonic (RM) and shortest job first (SJF) are static schedulers in real-time system. It chooses the priority of the processes grounded on its occurrence and time required to execute for given process correspondingly. The process which has the smallest period and smallest time required to execute will be considered as more priority in RM and SJF. In this paper, we have implemented the two dynamic scheduling algorithms (EDF and LST) and two static algorithms (RM and SJF) for the soft RTOS. Algorithms are tested with a periodic task set, and results are collected. We have observed the success ratio (SR) and effective CPU utilization (ECU) for all algorithms in a similar environment. It has been observed that the EDF and LST (dynamic algorithms) perform well in underload condition, but in overload situation, they are not able to perform well, whereas the RM and SJF (static algorithms) are failed to schedule a specific process in the underload scenario as well. They perform well in an overload situation compared with static algorithm. Practical investigations have been led on a huge dataset. Dataset consists of the 7000+ process set, and each process set has one to nine processes, and load varies between 0.5 and 5. It has been tried on 500-time unit to approve the rightness everything being equal.