Improving Performance by Monitoring While Maintaining Worst-Case Guarantees
Jakaria Abdullah, Kai Lampka, Wang Yi · 2016
With real-time systems, feasibility analysis is based on worst-case scenarios. At run-time, worst-case situations are often very unlikely to occur. With the system being dimensioned for the worst-case, one faces low resource utilization and implicit loss in performance at run-time. We propose to use run-time monitoring for evaluating the deviation of job releases from their worst-case release bound. This allows us to compute a conservative bound on the future workload. Based on this, we design a scheme for reclaiming computation time, which has been originally allocated for jobs which are now known to be absent. By organizing the consumption of extra computing time in a dynamic and time-safe manner, we improve the run-time performance of applications and provably maintain the worst-case guarantees for their response times. We evaluate the usefulness of the presented approach by using randomly generated traces of job releases.