Probabilistic Worst-Case Timing Analysis

Author:

Cazorla Francisco J.1,Kosmidis Leonidas2,Mezzetti Enrico2,Hernandez Carles3,Abella Jaume2ORCID,Vardanega Tullio4ORCID

Affiliation:

1. IIIA-CSIC and Barcelona Supercomputing Center, Barcelona, (Spain)

2. Barcelona Supercomputing Center, Barcelona, (Spain)

3. Universitat Politecnica de Valencia and Barcelona Supercomputing Center, Valencia, (Spain)

4. University of Padova, Padova, (Italy)

Abstract

The unabated increase in the complexity of the hardware and software components of modern embedded real-time systems has given momentum to a host of research in the use of probabilistic and statistical techniques for timing analysis. In the last few years, that front of investigation has yielded a body of scientific literature vast enough to warrant some comprehensive taxonomy of motivations, strategies of application, and directions of research. This survey addresses this very need, singling out the principal techniques in the state of the art of timing analysis that employ probabilistic reasoning at some level, building a taxonomy of them, discussing their relative merit and limitations, and the relations among them. In addition to offering a comprehensive foundation to savvy probabilistic timing analysis, this article also identifies the key challenges to be addressed to consolidate the scientific soundness and industrial viability of this emerging field.

Funder

Spanish Ministry of Science and Innovation

HiPEAC Network of Excellence

Spanish Ministry of Economy and Competitiveness under Juan de la Cierva-Incorporación postdoctoral fellowship

research and innovation programme

European Research Council (ERC) under the European Union’s Horizon 2020

Ministry of Economy and Competitiveness under a Ramon y Cajal postdoctoral fellowship

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

Reference112 articles.

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2. H. Abarbanel S. Koonin H. Levine G. MacDonald and O. Rothaus. 1992. Statistics of Extreme Events with Application to Climate. MITRE CORP MCLEAN VA JASON PROGRAM OFFICE. http://www.dtic.mil/cgi-bin/GetTRDoc?Location=U28doc=GetTRDoc.pdf8AD=ADA247342. H. Abarbanel S. Koonin H. Levine G. MacDonald and O. Rothaus. 1992. Statistics of Extreme Events with Application to Climate. MITRE CORP MCLEAN VA JASON PROGRAM OFFICE. http://www.dtic.mil/cgi-bin/GetTRDoc?Location=U28doc=GetTRDoc.pdf8AD=ADA247342.

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