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Reliability and performance optimization of pipelined real-time systems

Anne Benoit 1, 2 Fanny Dufossé 1 Alain Girault 3 Yves Robert 1, 2 
1 GRAAL - Algorithms and Scheduling for Distributed Heterogeneous Platforms
Inria Grenoble - Rhône-Alpes, LIP - Laboratoire de l'Informatique du Parallélisme
3 POP ART - Programming languages, Operating Systems, Parallelism, and Aspects for Real-Time
Inria Grenoble - Rhône-Alpes, LIG - Laboratoire d'Informatique de Grenoble
Abstract : We consider pipelined real-time systems, commonly found in assembly lines, consisting of a chain of tasks executing on a distributed platform. Their processing is pipelined: each processor executes only one interval of consecutive tasks. We are therefore interested in minimizing both the input-output latency and the period. For dependability reasons, we are also interested in maximizing the reliability of the system. We therefore assign several processors to each interval of tasks, so as to increase the reliability of the system. We assume that both processors and communication links are unreliable and subject to transient failures, the arrival of which follows a constant parameter Poisson law. We also assume that the failures are statistically independent events. We study several variants of this multiprocessor mapping problem with several hypotheses on the target platform (homogeneous/heterogeneous speeds and/or failure rates). We provide NP-hardness complexity results, and optimal mapping algorithms for polynomial problem instances. Efficient heuristics are presented to solve the general case, and experimental results are provided.
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Submitted on : Thursday, January 13, 2011 - 4:40:05 PM
Last modification on : Wednesday, October 26, 2022 - 8:16:13 AM
Long-term archiving on: : Thursday, June 30, 2011 - 1:47:56 PM


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  • HAL Id : inria-00555546, version 1


Anne Benoit, Fanny Dufossé, Alain Girault, Yves Robert. Reliability and performance optimization of pipelined real-time systems. [Research Report] RR-7509, INRIA. 2011, pp.32. ⟨inria-00555546⟩



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