Impact of Non-stationary Workload on Resource Reservation Based Slack Reclamation

Abstract—In open real-time systems with a non-stationary workload, tasks can be dynamically mapped to servers. If a server-based, slack reclamation scheduler is used, each task reserves a fraction of the bandwidth based on its resource esti-mation. However, the slack time scheduler makes no guarantee to a task beyond its processor capacity reserve, i.e., the scheduler cannot guarantee that a soft real-time task will receive a higher quality of service than is specified by its resource reservation. Nevertheless users often assume that a desired quality of service (QoS) can be achieved using an optimistic resource reservation. Even though existing slack time schedulers perform well in a closed real-time system (with well-behaved applications, station-ary workloads, or excessive processor speed), their performance can drop significantly when a task changes its workload. We identify resource underbooking and overbooking problems i