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Quality and Cost of Deterministic Network Calculus: Design and Evaluation of an Accurate and Fast Analysis

Quality and Cost of Deterministic Network Calculus: Design and Evaluation of an Accurate and Fast... Quality and Cost of Deterministic Network Calculus ­ Design and Evaluation of an Accurate and Fast Analysis STEFFEN BONDORF, PAUL NIKOLAUS, and JENS B. SCHMITT, Distributed Computer Systems (DISCO) Lab, University of Kaiserslautern Networks are integral parts of modern safety-critical systems and certification demands the provision of guarantees for data transmissions. Deterministic Network Calculus (DNC) can compute a worst-case bound on a data flow's end-to-end delay. Accuracy of DNC results has been improved steadily, resulting in two DNC branches: the classical algebraic analysis and the more recent optimization-based analysis. The optimization-based branch provides a theoretical solution for tight bounds. Its computational cost grows, however, (possibly super-)exponentially with the network size. Consequently, a heuristic optimization formulation trading accuracy against computational costs was proposed. In this article, we challenge optimization-based DNC with a new algebraic DNC algorithm. We show that: (1) no current optimization formulation scales well with the network size and (2) algebraic DNC can be considerably improved in both aspects, accuracy and computational cost. To that end, we contribute a novel DNC algorithm that transfers the optimization's search for best attainable delay bounds to algebraic DNC. It achieves a high degree of accuracy and our novel efficiency improvements http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Proceedings of the ACM on Measurement and Analysis of Computing Systems Association for Computing Machinery

Quality and Cost of Deterministic Network Calculus: Design and Evaluation of an Accurate and Fast Analysis

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References (26)

Publisher
Association for Computing Machinery
Copyright
Copyright © 2017 by ACM Inc.
ISSN
2476-1249
DOI
10.1145/3084453
Publisher site
See Article on Publisher Site

Abstract

Quality and Cost of Deterministic Network Calculus ­ Design and Evaluation of an Accurate and Fast Analysis STEFFEN BONDORF, PAUL NIKOLAUS, and JENS B. SCHMITT, Distributed Computer Systems (DISCO) Lab, University of Kaiserslautern Networks are integral parts of modern safety-critical systems and certification demands the provision of guarantees for data transmissions. Deterministic Network Calculus (DNC) can compute a worst-case bound on a data flow's end-to-end delay. Accuracy of DNC results has been improved steadily, resulting in two DNC branches: the classical algebraic analysis and the more recent optimization-based analysis. The optimization-based branch provides a theoretical solution for tight bounds. Its computational cost grows, however, (possibly super-)exponentially with the network size. Consequently, a heuristic optimization formulation trading accuracy against computational costs was proposed. In this article, we challenge optimization-based DNC with a new algebraic DNC algorithm. We show that: (1) no current optimization formulation scales well with the network size and (2) algebraic DNC can be considerably improved in both aspects, accuracy and computational cost. To that end, we contribute a novel DNC algorithm that transfers the optimization's search for best attainable delay bounds to algebraic DNC. It achieves a high degree of accuracy and our novel efficiency improvements

Journal

Proceedings of the ACM on Measurement and Analysis of Computing Systems – Association for Computing Machinery

Published: Jun 13, 2017

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