In distributed real-time embedded systems (DRE), it is common to model an application as a set of task chains. Each chain is activated cyclically and must complete before an end-to-end deadline. Each task of the chain is bound to execute on a particular processing element. The complexity of designing and analyzing a DRE can be reduced by applying a component-based methodology: each pipeline can be seen as a component with its temporal characteristic summarized in its interface. Analysis can be carried out in two different steps: 1) derivation of the temporal interface of a component pipeline, 2) analysis of the whole system by integrating the temporal interfaces of the components. In this paper, we propose to describe the temporal interface of a task pipeline by a set of demand bound functions, one per each node on which the pipeline executes, and we describe an algorithm for computing the dbfs. First, we show that the scenario of strictly periodic activations is not the worst when the pipelines are sporadically activated. Then, we propose an exact algorithm for computing the dbfs. We show by experimental analysis that the computation time of the algorithm on pipelines with reasonable size is below one second on common PCs. Finally, we estimate the pessimism introduced by our analysis with respect to holistic analysis by an extensive set of simulations.

The Demand Bound Function Interface of Distributed Sporadic Pipelines of Tasks Scheduled by EDF

LIPARI, Giuseppe;BINI, Enrico
2010-01-01

Abstract

In distributed real-time embedded systems (DRE), it is common to model an application as a set of task chains. Each chain is activated cyclically and must complete before an end-to-end deadline. Each task of the chain is bound to execute on a particular processing element. The complexity of designing and analyzing a DRE can be reduced by applying a component-based methodology: each pipeline can be seen as a component with its temporal characteristic summarized in its interface. Analysis can be carried out in two different steps: 1) derivation of the temporal interface of a component pipeline, 2) analysis of the whole system by integrating the temporal interfaces of the components. In this paper, we propose to describe the temporal interface of a task pipeline by a set of demand bound functions, one per each node on which the pipeline executes, and we describe an algorithm for computing the dbfs. First, we show that the scenario of strictly periodic activations is not the worst when the pipelines are sporadically activated. Then, we propose an exact algorithm for computing the dbfs. We show by experimental analysis that the computation time of the algorithm on pipelines with reasonable size is below one second on common PCs. Finally, we estimate the pessimism introduced by our analysis with respect to holistic analysis by an extensive set of simulations.
2010
9781424475469
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11382/374700
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