Optimal Configuration for Multiversion Real-Time Systems Using Slack Based Schedulability
In an embedded control system control performances of each job depend on its latency and a control algorithm implemented in it In order to adapt a job set to optimize control performances subject to schedulability we design several types of control software for each job which will be called versions and select one version from them when the job is released A real time system where each job has several versions is called a multiversion real time system A benefit and a CPU utilization of a job depend on the versions So it is an important problem to select a version of each job so as to maximize the total benefit of the system subject to a schedulability condition Such a problem will be called an optimal configuration problem In this paper we assume that each version is specified by the relative deadline the execution time and the benefit We show that the optimal configuration problem is transformed to a maximum path length problem We propose an optimal algorithm based on the forward dynamic programming Moreover we propose sub optimal algorithms to reduce computation times The efficiencies of the proposed algorithms are illustrated by simulations
real time systems edf scheduling multiversion task model optimization