Scheduling Design and Verification for Open Soft Real-Time Systems

Glaubius, Robert; Tidwell, Terry; Smart, William D.; Gill, Christopher

doi:10.1109/rtss.2008.48

Cited by 14 publications

(12 citation statements)

References 23 publications

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“…Our previous work [5]- [7] formulated MDPs to design scheduling policies in soft real-time environments with always-available jobs, but did so only for simple utilizationshare-based semantics. In this work we extend such use of MDPs to design new classes of utility-aware scheduling policies for periodic tasks with stochastic duration.…”

Section: Related Workmentioning

confidence: 99%

“…In previous work [5]- [7] we presented methods for formulating scheduling problems with non-preemptable jobs with stochastic duration as MDPs. Using existing techniques from the operations research literature [24] we were able to derive policies for a particular class of scheduling problems.…”

Section: Solution Approachmentioning

confidence: 99%

“…In this paper we extend our previous work on Markov Decision Process (MDP) based scheduling policy design [5]- [7] to generate utility-aware scheduling policies appropriate for real-time cyber-physical systems with non-preemptable jobs that run with stochastic duration. This extension enables us to derive scheduling policies that optimize expected utility accrual for this important class of systems.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Optimizing Expected Time Utility in Cyber-Physical Systems Schedulers

Tidwell¹,

Glaubius²,

Gill³

et al. 2010

2010 31st IEEE Real-Time Systems Symposium

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Abstract-Classical scheduling abstractions such as deadlines and priorities do not readily capture the complex timing semantics found in many real-time cyber-physical systems. Time utility functions provide a necessarily richer description of timing semantics, but designing utility-aware scheduling policies using them is an open research problem. In particular, scheduling design that optimizes expected utility accrual is needed for realtime cyber-physical domains.In this paper we design scheduling policies that optimize expected utility accrual for cyber-physical systems with periodic, non-preemptable tasks that run with stochastic duration. These policies are derived by solving a Markov Decision Process formulation of the scheduling problem. We use this formulation to demonstrate that our technique improves on existing heuristic utility accrual scheduling policies.

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Section: Related Workmentioning

confidence: 99%

Section: Solution Approachmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimizing Expected Time Utility in Cyber-Physical Systems Schedulers

Tidwell¹,

Glaubius²,

Gill³

et al. 2010

2010 31st IEEE Real-Time Systems Symposium

Self Cite

View full text Add to dashboard Cite

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“…In Glaubius et al (2008), we extended our previous work to eliminate the dependence on a time horizon by taking advantage of recurrence in the system model. As we discuss in this section, that allows us instead to use a discounting scheme that can be thought of as a prior probability that a system will continue to execute from time step to time step and to derive scheduling policies that are optimal to arbitrary planning horizons.…”

Section: Wrapped State Modelmentioning

confidence: 99%

Scheduling policy design for autonomic systems

Glaubius

Tidwell

Gill

et al. 2009

IJAACS

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Scheduling the execution of multiple concurrent tasks on shared resources such as CPUs and network links is essential to ensuring the reliable operation of many autonomic systems. Well-known techniques such as rate-monotonic scheduling can offer rigorous timing and preemption guarantees, but only under assumptions (i.e. a fixed set of tasks with well-known execution times and invocation rates) that do not hold in many autonomic systems. New hierarchical scheduling techniques are better suited to enforce the more flexible execution constraints and enforcement mechanisms that are required for autonomic systems, but a rigorous and efficient foundation for verifying and enforcing concurrency and timing guarantees is still needed for these approaches. This paper summarises our previous work on addressing these challenges, on Markov decision process-based scheduling policy design and on wrapping repeated structure of the scheduling state spaces involved into a more efficient model, and presents a new algorithm called expanding state policy iteration (ESPI), that allows us to compute the optimal policy for a wrapped state model.

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“…In previous work [1] we presented methods for generating task scheduling policies for open soft real-time systems with these properties. However, the inherent complexity of generating these policies limits the usefulness of that approach to problem instances with a small number of tasks.…”

Section: Introductionmentioning

confidence: 99%

Scalable Scheduling Policy Design for Open Soft Real-Time Systems

Glaubius

Tidwell

Sidoti

et al. 2010

2010 16th IEEE Real-Time and Embedded Technology and Applications Symposium

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Open soft real-time systems, such as mobile robots, must respond adaptively to varying operating conditions, while balancing the need to perform multiple mission specific tasks against the requirement that those tasks complete in a timely manner. Setting and enforcing a utilization target for shared resources is a key mechanism for achieving this behavior. However, because of the uncertainty and non-preemptability of some tasks, key assumptions of classical scheduling approaches do not hold. In previous work we presented foundational methods for generating task scheduling policies to enforce proportional resource utilization for open soft real-time systems with these properties. However, these methods scale exponentially in the number of tasks, limiting their practical applicability.In this paper, we present a novel parameterized scheduling policy that scales our technique to a much wider range of systems. These policies can represent geometric features of the scheduling policies produced by our earlier methods, but only require a number of parameters that is quadratic in the number of tasks. We provide empirical evidence that the best of these policies are competitive with exact solution methods in small problems, and significantly outperform heuristic methods in larger ones.

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Scheduling Design and Verification for Open Soft Real-Time Systems

Abstract: Abstract

Cited by 14 publications

References 23 publications

Optimizing Expected Time Utility in Cyber-Physical Systems Schedulers

Optimizing Expected Time Utility in Cyber-Physical Systems Schedulers

Scheduling policy design for autonomic systems

Scalable Scheduling Policy Design for Open Soft Real-Time Systems

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