A systematic approach to designing distributed real-time systems

Sha, Lui; Sathaye, Shirish S.

doi:10.1109/2.231276

Cited by 54 publications

(14 citation statements)

References 10 publications

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“…In particular, GRM is claimed to be applicable to distributed systems. As (unvoluntarily) demonstrated in [22], such claims are unfounded. The unsolvable problem faced with GRM is that there cannot exist a method that could be used off-line to transform the deadlines into fixed priorities, while demonstrating that the transformed problem is equivalent to [HRTDM] or without violating [cc2].…”

Section: ]mentioning

confidence: 99%

“…The unsolvable problem faced with GRM is that there cannot exist a method that could be used off-line to transform the deadlines into fixed priorities, while demonstrating that the transformed problem is equivalent to [HRTDM] or without violating [cc2]. It is in fact easy to demonstrate that GRM cannot solve general distributed scheduling problems, contrary to the claims made in [22]. GRM is a typicM example of an approach based on an artificially restrictive view of reality (see section 4.1).…”

Section: ]mentioning

confidence: 99%

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On real-time and non real-time distributed computing

Lann¹

1995

Distributed Algorithms

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Abstract. In this paper, taking an algorithmic viewpoint, we explore the differences existing between the class of non real-time computing problems (R~) versus the class of real-time computing problems (~). We show how a problem in class RN can be transformed into its counterpart in class ~. Claims of real-time behavior made for solutions to problems in class ~ are examined. Ah example of a distributed computingproblem arising m class Is studmd, along with its solutmn. It is shown why off-line strategies or scheduling algorithms that are not driven by real-time/timeliness requirements ~ are incorrect for class ~. Finally, a unified approach to conceiving and measuring the efficiency of solutions to problems in classes R~ and ~ is proposed and illustrated with a few examples. INTRODUCTIONOver the last 20 years, the distributed algorithms community has spent considerable effort solving problems in the areas of serializable or linearizable concurrent computing. These problems belong to a class denoted R~, the class of non reMtime computing problems. Separately, over the last 30 years, the real-time algorithms community has spent considerable effort solving scheduling problems in the area of centralized computing, considering preemptable and non-preemptable resources. Only recently has distributed computing received some attention. These problems belong to a class denoted ~, the class of real-time computing problems.In this paper, taking an algorithmic viewpoint, we embark on exploring the differences between both classes. The scope of this paper is restricted to that of deterministic algorithms. Besides intellectual interest, investigation of these issues is expected to bring the two communities closer, via the clarification of a few essential concepts. In particular, we have observed that the qualifiers "realtime" and "distributed" may not carry the same meaning in both communities. Broadly speaking, with few exceptions, the distributed algorithms community does not consider problem specifications that include real-time requirements. Conversely, the real-time algorithms community often fails to understand what is implied with considering a distributed computing problem.The remainder of this paper is organized as follows. In section 2, we introduce the distinctive attributes of class ~. In section 3, we examine claims of real-time

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Section: ]mentioning

confidence: 99%

Section: ]mentioning

confidence: 99%

On real-time and non real-time distributed computing

Lann¹

1995

Distributed Algorithms

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“…The execution times of all the jobs are known except for J 3 . Its execution time can be any value in the range [2,8]. Parts (b), (c) and (d) of this figure show the maximal, minimal and actual schedules, respectively.…”

Section: Arbitrary Release Time Casementioning

confidence: 99%

“…Consequently, it is impractical and unreliable to validate that all jobs meet their deadlines using exhaustive testing and simulation when their execution times and release times may vary. Recently, several efficient and analytical methods for validating timing constraints of static multiprocessor and distributed systems have been developed, e.g., [2,3,4] (In a static system, jobs are assigned and bound to processors.). These methods are based on worst-case bounds and schedulability conditions for uniprocessor systems [5,6,7,8].…”

Section: Introductionmentioning

confidence: 99%

Validating Timing Constraints of Dependent Jobs with Variable Execution Times in Distributed Real-Time Systems

Cha

2002

Tools and Algorithms for the Construction and Analysis of Systems

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Abstract. In multiprocessor and distributed real-time systems, scheduling jobs dynamically on processors can be used to achieve better performance. However, analytical and efficient validation methods for determining whether all the timing constraints are met do not yet exist for systems using modern dynamic scheduling strategies, and exhaustive methods are often infeasible or unreliable since the execution time and release time of each job may vary. In this paper, we present several upper bounds and efficient algorithms for computing the worst-case completion times of dependent jobs in dynamic systems where jobs are dispatched and scheduled on available processors in a priority-driven manner. The bounds and algorithms consider arbitrary release times and variable execution times. We present conditions under which dependent jobs execute in a predictable manner.

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“…A number of methods for modeling the real-time behavior of dataflow applications have been developed for multiprocessor and distributed systems [4,12,15,23]. Typically, such applications are modeled as directed acyclic graphs (DAGs), with nodes denoting tasks and edges denoting producer/consumer relationships.…”

Section: Introductionmentioning

confidence: 99%

Minimizing response times of automotive dataflows on multicore

Elliott

AKim

Erickson

et al. 2014

2014 IEEE 20th International Conference on Embedded and Real-Time Computing Systems and Applications

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Dataflow software architectures are prevalent in prototypes of advanced automotive systems, for both driver-assisted and autonomous driving. Safety constraints of these systems necessitate real-time performance guarantees. Automotive prototypes often ensure such constraints through overprovisioning and dedicated hardware; however, a commercially viable system must utilize as few low-cost multicore processors as possible to meet size, weight, and power constraints. In short, these platforms must do more with less. To this end, we develop cache-aware and overhead-cognizant scheduling techniques that lessen guaranteed response times without unnecessarily constraining platform utilization. We implement these techniques in PGM RT , a portable middleware framework for managing real-time dataflow applications on multicore platforms. The efficacy of our techniques is demonstrated through overhead-aware schedulability experiments and runtime observations. Results for our test platform show that cache-aware clustered scheduling outperforms naïve partitioned and global approaches in terms of schedulability and end-to-end response times of dataflows.

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A systematic approach to designing distributed real-time systems

Cited by 54 publications

References 10 publications

On real-time and non real-time distributed computing

On real-time and non real-time distributed computing

Validating Timing Constraints of Dependent Jobs with Variable Execution Times in Distributed Real-Time Systems

Minimizing response times of automotive dataflows on multicore

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