Client-Server Networked Automation Systems Reactivity: Deterministic and Probabilistic Analysis

In this paper, we present an analytic approach to evaluate the reactivity of client-server networked automation systems (NASs). Both deterministic and probabilistic analyses are provided while modeling the NAS using Timed Event Graphs (TEG). Since many results with regard to the deterministic approach have already been published, we recall only its main steps that prove useful, while exposing the probabilistic method. Thereby, we provide the density of probability distribution of the response time (or reactivity) using the probability densities of the local delays, experienced at the different stages of the NAS. Furthermore, a case study is presented to compare the results of the study to measures taken from a real platform.

[1]  Tadao Murata,et al.  Petri nets: Properties, analysis and applications , 1989, Proc. IEEE.

[2]  François Baccelli,et al.  Recursive equations and basic properties of timed Petri nets , 1991 .

[3]  Rene L. Cruz,et al.  A calculus for network delay, Part I: Network elements in isolation , 1991, IEEE Trans. Inf. Theory.

[4]  Geert Jan Olsder,et al.  Synchronization and Linearity: An Algebra for Discrete Event Systems , 1994 .

[5]  D. Zaitsev,et al.  State equations and equivalent transformations for timed petri nets , 1997 .

[6]  Jürgen Jasperneite,et al.  Switched Ethernet for factory communication , 2001, ETFA 2001. 8th International Conference on Emerging Technologies and Factory Automation. Proceedings (Cat. No.01TH8597).

[7]  Suk Lee,et al.  Performance evaluation of switched Ethernet for real-time industrial communications , 2002, Comput. Stand. Interfaces.

[8]  D. A. Zaitsev.  Switched LAN simulation by colored Petri nets , 2004, Math. Comput. Simul..

[9]  Peter Neumann,et al.  Communication in industrial automation—What is going on? , 2004 .

[10]  Eric Rondeau,et al.  Confronting the performances of a switched Ethernet network with industrial constraints by using the network calculus , 2005, Int. J. Commun. Syst..

[11]  Birgit Vogel-Heuser,et al.  PERFORMANCE ANALYSIS OF INDUSTRIAL ETHERNET NETWORKS BY MEANS OF TIMED MODEL-CHECKING , 2006 .

[12]  Georg Frey,et al.  Optimizing Quality of Control in Networked Automation Systems using Probabilistic Models , 2006, 2006 IEEE Conference on Emerging Technologies and Factory Automation.

[13]  Georg Frey,et al.  Evaluation of Response Time in Ethernet-based Automation Systems , 2006, 2006 IEEE Conference on Emerging Technologies and Factory Automation.

[14]  Georg Frey,et al.  Measuring the impact of vertical integration on response times in ethernet fieldbuses , 2007, 2007 IEEE Conference on Emerging Technologies and Factory Automation (EFTA 2007).

[15]  Georg Frey,et al.  PROBABILISTIC TIMED AUTOMATA FOR MODELING NETWORKED AUTOMATION SYSTEMS , 2007 .

[16]  Georg Frey,et al.  Reactivity analysis of different Networked Automation System architectures , 2008, 2008 IEEE International Conference on Emerging Technologies and Factory Automation.

[17]  Jan Jonsson,et al.  Guaranteed real-time communication in packet-switched networks with FCFS queuing , 2009, Comput. Networks.

[18]  Jean-Jacques Lesage,et al.  Analytic Calculus of Response Time in Networked Automation Systems , 2010, IEEE Transactions on Automation Science and Engineering.

[19]  Jean-Jacques Lesage,et al.  Linear time-varying (max, +) representation of conflicting timed event graphs , 2010, WODES.