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

Published: 13 June 2017 Publication History

Abstract

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:
no current optimization formulation scales well with the network size and
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 reduce the cost of the analysis dramatically. In extensive numerical experiments, we observe that our delay bounds deviate from the optimization-based ones by only 1.142% on average while computation times simultaneously decrease by several orders of magnitude.

References

[1]
Alessandro Biondi, Giorgio Buttazzo, and Stefano Simoncelli. 2015. Feasibility Analysis of Engine Control Tasks under EDF Scheduling. In Proceedings of the 27th Euromicro Conference on Real-Time Systems (ECRTS. 139--148.
[2]
Luca Bisti, Luciano Lenzini, Enzo Mingozzi, and Giovanni Stea. 2012. Numerical analysis of worst-case end-to-end delay bounds in FIFO tandem networks. Real-Time Systems 48, 5 (2012), 527--569.
[3]
Steffen Bondorf and Fabien Geyer. 2016. Generalizing Network Calculus Analysis to Derive Performance Guarantees for Multicast Flows. In Proceedings of the 10th International Conference on Performance Evaluation Methodologies and Tools (ValueTools).
[4]
Steffen Bondorf and Jens B. Schmitt. 2010. Statistical Response Time Bounds in Randomly Deployed Wireless Sensor Networks. In Proceedings of the 35th IEEE Local Computer Network Conference (LCN). 340--343.
[5]
Steffen Bondorf and Jens B. Schmitt. 2014. The DiscoDNC v2 -- A Comprehensive Tool for Deterministic Network Calculus. In Proceedings of the 8th International Conference on Performance Evaluation Methodologies and Tools (ValueTools).
[6]
Steffen Bondorf and Jens B. Schmitt. 2015. Boosting Sensor Network Calculus by Thoroughly Bounding Cross-Traffic. In Proceedings of the IEEE Conference on Computer Communications (INFOCOM). 235--243.
[7]
Steffen Bondorf and Jens B. Schmitt. 2015. Calculating Accurate End-to-End Delay Bounds -- You Better Know Your Cross-Traffic. In Proceedings of the 9th International Conference on Performance Evaluation Methodologies and Tools (ValueTools).
[8]
Steffen Bondorf and Jens B. Schmitt. 2016. Improving Cross-Traffic Bounds in Feed Forward Networks -- There is a Job for Everyone. In Proceedings of GI/ITG International Conference on Measurement, Modelling and Evaluation of Dependable Computer and Communication Systems (MMB & DFT).
[9]
Steffen Bondorf and Jens B. Schmitt. 2016. Should Network Calculus Relocate? An Assessment of Current Algebraic and Optimization- based Analyses. In Proceedings of the 13th International Conference on Quantitative Evaluation of Systems (QEST).
[10]
Anne Bouillard. 2014. Algorithms and efficiency of Network calculus. Habilitation thesis, École Normale Supérieure. (2014).
[11]
Anne Bouillard, Bruno Gaujal, Sébastien Lagrange, and Eric Thierry. 2008. Optimal routing for end-to-end guarantees using Network Calculus. Elsevier Performance Evaluation 65, 11--12 (2008), 883--906.
[12]
Anne Bouillard, Laurent Jouhet, and Eric Thierry. 2008. Computation of a (min,+) multi dimensional convolution for end-to-end performance analysis. In Proceedings of the 3rd International Conference on Performance Evaluation Methodologies and Tools (ValueTools). 68:1--68:7.
[13]
Anne Bouillard, Laurent Jouhet, and Eric Thierry. 2009. Service curves in Network Calculus: dos and don'ts. Research Report RR-7094. INRIA. 24 pages.
[14]
Anne Bouillard, Laurent Jouhet, and Eric Thierry. 2010. Tight performance bounds in the worst-case analysis of feed-forward networks. In Proceedings of the IEEE Conference on Computer Communications (INFOCOM). 1--9.
[15]
Anne Bouillard and Thomas Nowak. 2015. Fast symbolic computation of the worst-case delay in tandem networks and applications. Performance Evaluation 91 (2015), 270 -- 285. Special Issue: Performance 2015.
[16]
Anne Bouillard and Giovanni Stea. 2015. Exact Worst-Case Delay in FIFO-Multiplexing Fee
[17]
Anne Bouillard and Éric Thierry. 2008. An Algorithmic Toolbox for Network Calculus. Discrete Event Dynamic Systems 18, 1 (2008), 3--49.
[18]
Marc Boyer and Christian Fraboul. 2008. Tightening end to end delay upper bound for AFDX network calculus with rate latency FIFO servers using network calculus. In Proceedings of the IEEE International Workshop on Factory Communication Systems (WFCS). 11--20.
[19]
Marc Boyer, Nicolas Navet, and Marc Fumey. 2012. Experimental assessment of timing verification techniques for AFDX. In Proceedings of the 6th European Congress on Embedded Real Time Software and Systems (ERTS) .
[20]
Tian Bu and Don Towsley. 2002. On Distinguishing between Internet Power Law Topology Generators. In Proceedings of the IEEE Conference on Computer Communications (INFOCOM).
[21]
Cheng-Shang Chang. 2000. Performance Guarantees in Communication Networks. Springer-Verlag, New York, NY.
[22]
Rene L. Cruz. 1991. A Calculus for Network Delay, Part I: Network Elements in Isolation. IEEE Transactions on Information Theory 37, 1 (1991), 114--131.
[23]
Rene L. Cruz. 1991. A Calculus for Network Delay, Part II: Network Analysis. IEEE Transactions on Information Theory 37, 1 (1991), 132--141.
[24]
Markus Fidler. 2003. Extending the Network Calculus Pay Bursts Only Once Principle to Aggregate Scheduling. In Proceedings of the 2nd International Workshop on Quality of Service in Multiservice IP Networks (QoS-IP). 19--34. http://dl.acm.org/citation.cfm?id=646464.691395
[25]
Fabrice Frances, Christian Fraboul, and Jérôme Grieu. 2006. Using Network Calculus to optimize the AFDX network. In Proceedings of the 6th European Congress on Embedded Real Time Software and Systems (ERTS).
[26]
Fabien Geyer and Georg Carle. 2016. Network engineering for real-time networks: comparison of automotive and aeronautic industries approaches. IEEE Communications Magazine 54, 2 (February 2016), 106--112.
[27]
Jérôme Grieu. 2004. Analyse et évaluation de techniques de commutation Ethernet pour l'interconnexion des systèmes avioniques. Ph.D. Dissertation. Institut National Polytechnique de Toulouse, France.
[28]
Nan Guan and Wang Yi. 2013. Finitary Real-Time Calculus: Efficient Performance Analysis of Distributed Embedded Systems. In Proceedings of the 34th IEEE Real-Time Systems Symposium (RTSS). 330--339.
[29]
Keon Jang, Justine Sherry, Hitesh Ballani, and Toby Moncaster. 2015. Silo: Predictable Message Latency in the Cloud. In Proceedings of the ACM Conference on Special Interest Group on Data Communication (SIGCOMM). 435--448.
[30]
Bengt Jonsson, Simon Perathoner, Lothar Thiele, and Wang Yi. 2008. Cyclic dependencies in modular performance analysis. In Proceedings of the 8th ACM international Conference on embedded software (EMSOFT). 179--188.
[31]
Mark Karol, Michael Hluchyj, and Samuel Morgan. 1987. Input Versus Output Queueing on a Space-Division Packet Switch. IEEE Transactions on Communications 35, 12 (1987), 1347--1356.
[32]
Andreas Kiefer, Nicos Gollan, and Jens Schmitt. 2010. Searching for Tight Performance Bounds in Feed-Forward Networks. In Proceedings of GI/ITG International Conference on Measurement, Modelling and Evaluation of Dependable Computer and Communication Systems (MMB & DFT).
[33]
Kai Lampka, Steffen Bondorf, and Jens B. Schmitt. 2016. Achieving Efficiency without Sacrificing Model Accuracy: Network Calculus on Compact Domains. In In Proceedings of the 24th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS). 313--318.
[34]
Jean-Yves Le Boudec and Patrick Thiran. 2001. Network Calculus: A Theory of Deterministic Queuing Systems for the Internet. Springer- Verlag, Berlin, Germany.
[35]
Luciano Lenzini, Enzo Mingozzi, and Giovanni Stea. 2008. A Methodology for Computing End-to-End Delay Bounds in FIFO-Multiplexing Tandems. Elsevier Performance Evaluation 65, 11--12 (2008), 922--943.
[36]
Xiaoting Li, Jean-Luc Scharbarg, and Christian Fraboul. 2010. Improving end-to-end delay upper bounds on an AFDX network by integrating offsets in worst-case analysis. In Proceedings of the IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). 1--8.
[37]
Renato Mancuso, Andrew V. Louis, and Marco Caccamo. 2015. Using Traffic Phase Shifting to Improve AFDX Link Utilization. In Proceedings of the International Conference on Embedded Software (EMSOFT). 256- 265.
[38]
Frank Ruskey. 2003. Combinatorial Generation. Working version of book in progress.
[39]
Henrik Schiøler, Jan Jakob Jessen, Jens Dalsgaard Nielsen, and Kim Guldstrand Larsen. 2005. Network Calculus for Real Time Analysis of Embedded Systems with Cyclic Task Dependencies. In Proceedings of the 20th Conference on Computers and Their Applications (CATA). 326--332.
[40]
Jens B. Schmitt, Frank A. Zdarsky, and Markus Fidler. 2008. Delay Bounds under Arbitrary Multiplexing: When Network Calculus Leaves You in the Lurch .... In Proceedings of the IEEE Conference on Computer Communications (INFOCOM). 1669--1677.
[41]
Jens B. Schmitt, Frank A. Zdarsky, and Ivan Martinovic. 2008. Improving Performance Bounds in Feed-Forward Networks by Paying Multiplexing Only Once. In Proceedings of GI/ITG International Conference on Measurement, Modelling and Evaluation of Computer and Communication Systems (MMB).
[42]
David Starobinski, Mark Karpovsky, and Lev A. Zakrevski. 2003. Application of Network Calculus to General Topologies Using Turn-Prohibition. IEEE/ACM Transactions on Networking 11, 3 (2003), 411--421.
[43]
Joanna Tomasik and Marc-Antoine Weisser. 2010. Internet topology on AS-level: Model, generation methods and tool. In Proceedings of the IEEE International Performance Computing and Communications Conference (IPCCC). 263--270.
[44]
Yaakov L. Varol and Doron Rotem. 1981. An algorithm to generate all topological sorting arrangements. Comput. J. 24, 1 (1981), 83--84.
[45]
Timothy Zhu, Alexey Tumanov, Michael A. Kozuch, Mor Harchol-Balter, and Gregory R. Ganger. 2014. PriorityMeister: Tail Latency QoS for Shared Networked Storage. In Proceedings of the ACM Symposium on Cloud Computing (SOCC). ACM, Article 29, 14 pages.

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cover image Proceedings of the ACM on Measurement and Analysis of Computing Systems
Proceedings of the ACM on Measurement and Analysis of Computing Systems  Volume 1, Issue 1
June 2017
712 pages
EISSN:2476-1249
DOI:10.1145/3107080
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 13 June 2017
Published in POMACS Volume 1, Issue 1

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Author Tags

  1. delay bounds
  2. deterministic network calculus
  3. worst-case analysis

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  • Carl-Zeiss-Stiftung

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  • (2024)Extending Network Calculus to Deal with Min-Plus Service Curves in Multiple Flow Scenarios2024 IEEE 30th Real-Time and Embedded Technology and Applications Symposium (RTAS)10.1109/RTAS61025.2024.00016(95-107)Online publication date: 13-May-2024
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