Online real-time job scheduling with rate of progress guarantees

Abstract

Investigates the job scheduling problem within the context of reservation-based real-time systems that provide quality of service (QoS) guarantees. In such a system, each incoming job specifies a rate of progress requirement on the job execution that must be met by the system in order for computation to be deemed usable. A new metric, called granularity, is introduced that quantifies both the maximum slowdown and the variance in execution rate that the job allows. This metric generalizes the stretch metric used in recent research on job scheduling. An online pre-emptive scheduling algorithm is presented that is shown achieve a competitive ratio of g(1-r) for every set of jobs with maximum rate r and granularity g. This result generalizes a previous result based on the stretch metric that showed that a competitive ratio of 1-r is achievable for the case when g=1.