Effects of Hard Real-Time Constraints in Implementing the Myopic Scheduling Algorithm

TL;DR

This paper evaluates the performance of the Myopic hard real-time scheduling algorithm, focusing on how heuristic functions and window size affect its efficiency and constraints through experimental analysis.

Contribution

It provides a comparative analysis of how different heuristic functions and window sizes influence the Myopic scheduling algorithm's performance.

Findings

Performance varies with heuristic choice and window size.

Optimal window size balances scheduling efficiency and computational cost.

The algorithm shows specific constraints under certain parameter settings.

Abstract

Myopic is a hard real-time process scheduling algorithm that selects a suitable process based on a heuristic function from a subset (Window)of all ready processes instead of choosing from all available processes, like original heuristic scheduling algorithm. Performance of the algorithm significantly depends on the chosen heuristic function that assigns weight to different parameters like deadline, earliest starting time, processing time etc. and the sizeof the Window since it considers only k processes from n processes (where, k<= n). This research evaluates the performance of the Myopic algorithm for different parameters to demonstrate the merits and constraints of the algorithm. A comparative performance of the impact of window size in implementing the Myopic algorithm is presented and discussed through a set of experiments.