A feasible region for meeting aperiodic end-to-end deadlines in resource pipelines

Abdelzaher, Tarek; Thaker, G.H.; Lardieri, Patrick

doi:10.1109/icdcs.2004.1281610

Cited by 36 publications

(41 citation statements)

References 12 publications

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“…In contention-based Medium Access Control (MAC) communication protocols, packing data into larger units reduces the chances of packet collisions, hence reducing energy expenditure and improving delay. 1 Two different types of aggregation are possible; namely, lossless aggregation and lossy aggregation. Lossless aggregation refers to concatenating individual data items into larger packets, thus amortizing per-packet protocol overhead.…”

Section: Problem Statement and Architecturementioning

confidence: 99%

“…Any single path through the network can be thought of as a data pipeline of N stages, where N is the number of hops along the path. In a prior publication [1], we have shown that data traversing a pipeline will meet its end-to-end deadline as long as the following condition holds:…”

Section: Capacity Derivation and Sampling Ratementioning

confidence: 99%

“…This quantity is called the synthetic utilization of node j. The parameter α depends on the scheduling policy used to order outgoing packet transmissions on the link, as discussed in [1]. The bound was derived for nodes with dedicated links.…”

Section: Capacity Derivation and Sampling Ratementioning

confidence: 99%

“…Hence, the average packet transmission time is correspondingly increased m times to account for channel sharing. This is reflected in the values of Uj used in Equation (1). Next, we derive the real-time capacity bound in the presence of lossless aggregation.…”

Section: Capacity Derivation and Sampling Ratementioning

confidence: 99%

“…The instantaneous synthetic utilization of a node is Uinst = ¡ i Ci/Di, carried out over all outgoing packets. As explained in [1], this value is increased by Ci/Di when a new packet, Ti, arrives. It is decreased by Ci/Di only at the delivery deadline of the packet (and is set to zero when the link is idle).…”

Section: Control Of Lossy Aggregationmentioning

confidence: 99%

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Feedback control of data aggregation in sensor networks

Abdelzaher

Stankovic

2004

2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)

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Section: Problem Statement and Architecturementioning

confidence: 99%

Section: Capacity Derivation and Sampling Ratementioning

confidence: 99%

Section: Capacity Derivation and Sampling Ratementioning

confidence: 99%

Section: Capacity Derivation and Sampling Ratementioning

confidence: 99%

Section: Control Of Lossy Aggregationmentioning

confidence: 99%

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Feedback control of data aggregation in sensor networks

Abdelzaher

Stankovic

2004

2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601)

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Hybrid Metaheuristic Approach for Scheduling of Aperiodic OS Tasks

Gharsellaoui

Ahmed

2014

Complex System Modelling and Control Through Intelligent Soft Computations

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This book chapter deals with the purpose of one hybrid approach for solving the real-time embedded systems scheduling composed of aperiodic OS tasks which are used to control physical processes that range in complexity from automobile ignition systems to controllers for flight systems and nuclear power plants. In these systems, the correctness of system functions depends upon not only the results of computation but also on the times at which results are produced. This book chapter presents real-time scheduling techniques for reducing the response time of aperiodic tasks scheduled with real-time periodic tasks on uniprocessor systems where two problems are addressed: (i) the scheduling of aperiodic tasks when they arrive in order to obtain a feasible system, and (ii) the scheduling of periodic and aperiodic tasks to minimize their response time. Indeed, in order to improve the responsiveness to both types of problems, our approach proposed in this book chapter presents an efficient hybrid methaheuristic based on the combination of the Polling Server (PS) and the Background Server (BS). The effectiveness and the performance of the designed approach are evaluated through simulation studies. A tool named RT-Reconfiguration is developed in our research laboratory at INSAT Institute to support this new proposed approach.

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End-to-end deadline control for aperiodic tasks in distributed real-time systems

et al. 2007

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A category of Distributed Real-Time Systems (DRTS) that has multiprocessor pipeline architecture is increasingly used. The key challenge of such systems is to guarantee the end-to-end deadlines of aperiodic tasks. This paper proposes an end-to-end deadline control model, called Linear Quadratic Stochastic Optimal Control Model (LQ-SOCM), which features a distributed feedback control that dynamically enforces the desired performance. The control system considers the aperiodic task arrivals and execution times' variation as the two external factors of the system unpredictability. LQ-SOCM uses discrete time state space equation to describe the real-time computing system. Then, in the actuator design, a continuous manner is adopted to deal with discrete QoS (Quality of Service) adaptation. Finally, experiments demonstrate that the system is globally stable and can statistically provide the end-to-end deadline guarantee for aperiodic tasks. At the same time, LQ-SOCM is capable of effectively improving the system throughput.

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A feasible region for meeting aperiodic end-to-end deadlines in resource pipelines

Cited by 36 publications

References 12 publications

Feedback control of data aggregation in sensor networks

Feedback control of data aggregation in sensor networks

Hybrid Metaheuristic Approach for Scheduling of Aperiodic OS Tasks

End-to-end deadline control for aperiodic tasks in distributed real-time systems

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