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We consider the problem of resource provisioning for real-time cyber-physical applications in an open system environment where there does not exist a global resource scheduler that has complete knowledge of the real-time performance requirements of each individual application that shares the resources with the other applications. Regularity-based Resource Partition (RRP) model is an effective strategy to hierarchically partition and assign various resource slices among such applications. However, previous work on RRP model only discusses uniform resource environment, where resources are implicitly assumed to be synchronized and clocked at the same frequency. The challenge is that a task utilizing multiple resources may experience unexpected delays in non-uniform environments, where resources are clocked at different frequencies. This paper extends the RRP model to non-uniform multi-resource open system environments to tackle this problem. It first introduces a novel composite resource partition abstraction and then proposes algorithms to construct and reconfigure the composite resource partitions. Specifically, the Acyclic Regular Composite Resource Partition Scheduling (ARCRP-S) algorithm constructs regular composite resource partitions and the Acyclic Regular Composite Resource Partition Dynamic Reconfiguration (ARCRP-DR) algorithm reconfigures the composite resource partitions in the run time upon requests of partition configuration changes. Our experimental results show that compared with state-of-the-art methods, ARCRP-S can prevent unexpected resource supply shortfall and improve the schedulability up to 50%. On the other hand, ARCRP-DR can guarantee the resource supply during the reconfiguration with moderate computational overhead. [ABSTRACT FROM AUTHOR]

Maintaining the freshness of real-time data is one of the crucial design issues in cyber-physical systems (CPS). Past studies have focused on designing update algorithms to minimize the workload imposed by a fixed set of update tasks while ensuring the temporal validity of data. In this paper, we revisit this problem in dynamic cyber-physical systems (DCPS) which may exhibit multi-modal behavior. Any solution to this problem must recognize that: (1) different update algorithms may be needed in different modes according to the workload in each mode, and (2) temporal validity of data must be maintained not only in each mode but also during the mode switch. To strike a balance between data freshness and system schedulability, we propose a utilization-based scheduling selection (UBSS) strategy. We first introduce two synchronous mode switch algorithms, named search-based switch (SBS) and adjustment-based switch (ABS) to search for the proper switch point online and execute all update tasks in the new mode synchronously. SBS checks for temporal validity at the beginning time slot of each idle period in the schedule, while ABS relaxes this restriction through schedule adjustment. To support immediate mode switch, we propose an asynchronous switch algorithm named instant switch (IS) to reduce the switch delay. IS schedules outstanding jobs from the old mode together with the jobs in the new mode using the least-available-laxity-first scheduling policy. Our experimental results demonstrate the effectiveness of these three algorithms. They also show that UBSS strategy can significantly outperform a single fixed update algorithm in terms of maintaining better data freshness while incurring only limited online switch overhead. [ABSTRACT FROM PUBLISHER]

In many emerging time-critical applications, the exact time of event occurrences may not be known. In such cases, events can be represented as a probabilistic occurrence within a time interval. Thus, monitoring of timing constraints, generally used in time-critical systems, needs to incorporate the uncertainty of event occurrences. In this paper, we propose mechanisms to monitor the satisfaction/violation of timing constraints that can be assessed probabilistically. We assume a uniform distribution of event occurrence within a time interval. Our proposed algorithm determines whether the probability that a timing constraint has been satisfied exceeds a specified threshold value. A confidence threshold is a minimum satisfaction probability of the timing constraint. A timing constraint is violated if the confidence threshold is not reached. We design an efficient monitoring algorithm for detecting timing violations of a set of timing constraints by finding the earliest expiration time (EET) for each timing constraint. Since it is critical to derive implicit constraints for early detection of violation of timing constraints, we present the derivation of the implicit constraints under uncertainty using an all-pairs shortest path algorithm. Further, we propose pruning techniques to discard unnecessary implicit constraints. We present the properties and proofs of our approach. [ABSTRACT FROM AUTHOR]

Discusses the concepts of extremely and critically utilizing task set and an approach to find the utilization bound as a function of the information about the task set. Preemptive fixed-priority scheduling; Rate-monotonic priority assignment; Linear programming; Bound algorithms.