Compositional real-time scheduling framework with periodic model
ACM Transactions on Embedded Computing Systems (TECS)
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In this dissertation we introduce the notion of a Real-Time Virtual Resource (RTVR) which operates at a fraction of the rate of the shared physical resource and whose rate of operation varies with time but is bounded. Tasks within the same task group are scheduled by a task level scheduler that is specialized to the real-time requirements of the tasks in the group. The scheduling problems on both task level and resource level are analyzed. We specifically investigate RTVRs on the integer domain. For the case of regular resource partitioning, we show that the utilization bounds of both fixed-priority scheduling and dynamic-priority scheduling remain unchanged from those for dedicated resources. We determine the utilization bounds for the more general case of irregular partitioning. In particular, both types of partitions can be efficiently constructed by exploiting compositionality properties vis-à-vis the regularity measure. We further extend the applicability of the RTVR in several directions. First, we propose a hierarchical real-time virtual resource model that permits resource partitioning to be extended to multiple levels. Through this model, partitions on each level are scheduled as if they had access to a dedicated resource. Interference between neighboring partition levels is also minimized. Second, we apply RTVR to gang scheduling which is a popular scheduling technique used in parallel systems. We show that the clean isolation between resource-level and task-level scheduling makes RTVR an ideal candidate for implementing the gang scheduling solution in the real-time systems environment. Third, RTVRs in distributed environments are also discussed and end-to-end delay of a series of RTVRs is calculated. Finally, we investigate the resource locking issues in RTVR and present a resource server solution which has a highly efficient admission test. We also present an optimization scheme called Partition Coalition which is based on the server solution and which can substantially reduce the blocking time due to resource locking. These results provide a foundation for implementing RTVR on small-scale multiprocessor or processor cluster systems that are increasingly available. Based on the previous theoretical framework, we implement RTVRs on the Linux 2.4 kernel. The first RTVR implementation uses a static resource level scheduler which can be applied to systems with predefined application task sets. The second implementation has a novel dynamic resource level scheduler under which task groups can join and leave dynamically. (Abstract shortened by UMI.)