Educational process modelling with workflow and time Petri nets : a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Computer Science at Massey University, Palmerston North, New Zealand

The research presented in this thesis describes how to use workflow management technology to model educational processes with a time axis. As workflow management technology has been widely used in modelling business processes, it has the potential to model educational processes. Based upon the components of workflow, educational processes and business processes have many common features such that educational processes can be modelled with workflow management technology. In addition, owing to the importance of the time component in processes, time Petri nets have been chosen as the design language for the modelling of the educational processes. The notation of time Petri nets has been illustrated in this thesis for the educational process. In this thesis, three different educational processes have been presented and modelled with workflow management technology as well as with time Petri nets individually. Furthermore, the architecture of the educational process management system has been constructed by adopting the reference model from the Workflow Management Coalition. To show the validity of using workflow management technology in the education domain, a sub-process of an educational process has been modelled and developed with certain developing techniques. It provides the potential research direction for further research on the modelling of educational process with workflow technology associated with a time component

TIME EXTENSIONS OF PETRI NETS FOR MODELLING AND YERIFICATION OF HARD REAL-TIME SYSTEMS

The main aim ofthepaper is apresentation oftime extensions ofPetri nets appropriate for modelling and analysis o f hard real-time systems. It is assumed, that the extensions must provide a model o f time flow, an ability to force a transition to fire within a stated timing constraint (the so-called the strongfiring rule), and timing constraints represented by inte- rvals. The presented survey includes extensions o f classical Place/Transition Petri nets, as well as the ones applied to high-level Petri nets. An expressiveness o f each time extension is illustrated using simple hard real-time system. The paper includes also a brief description o f analysis and verification methods related to the extensions, and a survey o f software tools supporting modelling and analysis o f the considered Petri nets

Cluster Grid based Response-time analysis module for the PIPE Tool.

Generalized Stochastic Petri Nets (GSPNs) are a widely used high-level formalism used for modelling discrete-event systems. The Platform Independent Petri net Editor (PIPE) is an open source software project that allows creation, analysis and simulation of Petri Nets. This tool paper presents a PIPE module for response-time analysis of a Petri net’s underlying Continuous Time Markov Chain (CTMC). Jobs are submitted via a web interface, from within PIPE or from a browser. The parallel computations are run using Grid Engine on a cluster hosted at Imperial College London. 1

Modelling, reduction and analysis of Markov automata (extended version)

Markov automata (MA) constitute an expressive continuous-time compositional modelling formalism. They appear as semantic backbones for engineering frameworks including dynamic fault trees, Generalised Stochastic Petri Nets, and AADL. Their expressive power has thus far precluded them from effective analysis by probabilistic (and statistical) model checkers, stochastic game solvers, or analysis tools for Petri net-like formalisms. This paper presents the foundations and underlying algorithms for efficient MA modelling, reduction using static analysis, and most importantly, quantitative analysis. We also discuss implementation pragmatics of supporting tools and present several case studies demonstrating feasibility and usability of MA in practice

Compositional modelling using Petri nets with the analysis power of stochastic hybrid processes

A general stochastic hybrid process (GSHP) is a mathematical formalism that covers most of the requirements posed by the modelling of complex operations, such as time dependencies, multi-dimensional continuous as well as discrete processes, discontinuities, randomness and model uncertainties. In addition, it is possible to study GSHP by using stochastic analysis methodologies, thereby empowering it with powerful mathematical properties. This guarantees unambiguous simulation possibility of the model and allows speeding up this simulation while keeping the model properties intact. However, using GSHP to construct a model of a complex operation is not easy. To support the modelling and the subsequent verification both by mathematical and by multiple operational domain experts, a supporting graphical modelling formalism is desired. Petri nets have shown to be useful for developing models of various complex applications. Typical Petri net features are concurrency and synchronisation mechanism, hierarchical and modular construction, and natural expression of causal dependencies, in combination with graphical and analytical representations.\ud \ud The aim of this thesis is to combine the strengths of Petri net modelling formalisms and those of GSHP. First, dynamically coloured Petri nets (DCPN) are developed, and proof of equivalence is provided with piecewise deterministic Markov processes, which is a particular class of GSHP. Next, DCPN are extended to stochastically and dynamically coloured Petri nets (SDCPN), and proof of equivalence is provided with GSHP. Subsequently, SDCPN are extended to SDCPN with interconnection mapping types (SDCPNimt) and proof of equivalence is provided with both SDCPN and GSHP. It is shown with illustrative air transport examples that these three classes of Petri net are very effective when it comes to the compositional modelling of operations consisting of many distributed components that behave and interact in a dynamic way with many uncertainties. With the equivalence relations between these formalisms, the properties and strengths of the various approaches are combined. The many applications of the approach developed in this thesis, executed at NLR and beyond, show that both the approach and its combined strengths are acknowledged and supported by practice

On Modelling and Analyzing Composite Resources’ Consumption Cycles using Time Petri-Nets

ICT community cornerstones (IoT in particular) gain competitive advantage from using physical resources. This paper adopts Time Petri-Nets (TPNs) to model and analyze the consumption cycles of composite resources. These resources consist of primitive, and even other composite, resources that are associated with consumption properties and could be subject to disruptions. These properties are specialized into unlimited, shareable, limited, limited-but-renewable, and non-shareable, and could impact the availability of resources. This impact becomes a concern when disruptions suspend ongoing consumption cycles to make room for the unplanned consumptions. Resuming the suspended consumption cycles depends on the resources’ consumption properties. To ensure correct modeling and analysis of consumption cycles, whether disrupted or not, TPNs are adopted to verify that composite resources are reachable, bound, fair, and live

Identification of Stochastic Timed Discrete Event Systems with st-IPN

[EN] This paper presents amethod for the identification of stochastic timed discrete event systems, based on the analysis of the behavior of the input and output signals, arranged in a timeline. To achieve this goal stochastic timed interpreted Petri nets are defined.These nets link timed discrete event systems modelling with stochastic time modelling. The procedure starts with the observation of the input/output signals; these signals are converted into events, so that the sequence of events is the observed language. This language arrives to an identifier that builds a stochastic timed interpreted Petri net which generates the same language. The identified model is a deterministic generator of the observed language.The identification method also includes an algorithm that determines when the identification process is over.This work was supported by a Grant from the Universidad del Cauca, reference 2.3-31.2/05 2011.Muñoz-Añasco, DM.; Correcher Salvador, A.; García Moreno, E.; Morant Anglada, FJ. (2014). Identification of Stochastic Timed Discrete Event Systems with st-IPN. Mathematical Problems in Engineering. 2014:1-21. https://doi.org/10.1155/2014/835312S1212014Cassandras, C. G., & Lafortune, S. (Eds.). (2008). Introduction to Discrete Event Systems. doi:10.1007/978-0-387-68612-7Yingwei Zhang, Jiayu An, & Chi Ma. (2013). Fault Detection of Non-Gaussian Processes Based on Model Migration. IEEE Transactions on Control Systems Technology, 21(5), 1517-1526. doi:10.1109/tcst.2012.2217966Ichikawa, A., & Hiraishi, K. (s. f.). Analysis and control of discrete event systems represented by petri nets. Lecture Notes in Control and Information Sciences, 115-134. doi:10.1007/bfb0042308Fanti, M. P., Mangini, A. M., & Ukovich, W. (2013). Fault Detection by Labeled Petri Nets in Centralized and Distributed Approaches. IEEE Transactions on Automation Science and Engineering, 10(2), 392-404. doi:10.1109/tase.2012.2203596Cabasino, M. P., Giua, A., & Seatzu, C. (2010). Fault detection for discrete event systems using Petri nets with unobservable transitions. Automatica, 46(9), 1531-1539. doi:10.1016/j.automatica.2010.06.013Hu, H., Zhou, M., Li, Z., & Tang, Y. (2013). An Optimization Approach to Improved Petri Net Controller Design for Automated Manufacturing Systems. IEEE Transactions on Automation Science and Engineering, 10(3), 772-782. doi:10.1109/tase.2012.2201714Hu, H., Zhou, M., & Li, Z. (2011). Supervisor Optimization for Deadlock Resolution in Automated Manufacturing Systems With Petri Nets. IEEE Transactions on Automation Science and Engineering, 8(4), 794-804. doi:10.1109/tase.2011.2156783Hiraishi, K. (1992). Construction of a class of safe Petri nets by presenting firing sequences. Lecture Notes in Computer Science, 244-262. doi:10.1007/3-540-55676-1_14Estrada-Vargas, A. P., López-Mellado, E., & Lesage, J.-J. (2010). A Comparative Analysis of Recent Identification Approaches for Discrete-Event Systems. Mathematical Problems in Engineering, 2010, 1-21. doi:10.1155/2010/453254Shaolong Shu, & Feng Lin. (2013). I-Detectability of Discrete-Event Systems. IEEE Transactions on Automation Science and Engineering, 10(1), 187-196. doi:10.1109/tase.2012.2215959Li, L., & Hadjicostis, C. N. (2011). Least-Cost Transition Firing Sequence Estimation in Labeled Petri Nets With Unobservable Transitions. IEEE Transactions on Automation Science and Engineering, 8(2), 394-403. doi:10.1109/tase.2010.2070065Supavatanakul, P., Lunze, J., Puig, V., & Quevedo, J. (2006). Diagnosis of timed automata: Theory and application to the DAMADICS actuator benchmark problem. Control Engineering Practice, 14(6), 609-619. doi:10.1016/j.conengprac.2005.03.028Dotoli, M., Fanti, M. P., & Mangini, A. M. (2008). Real time identification of discrete event systems using Petri nets. Automatica, 44(5), 1209-1219. doi:10.1016/j.automatica.2007.10.014Chen, Y., Li, Z., Khalgui, M., & Mosbahi, O. (2011). Design of a Maximally Permissive Liveness- Enforcing Petri Net Supervisor for Flexible Manufacturing Systems. IEEE Transactions on Automation Science and Engineering, 8(2), 374-393. doi:10.1109/tase.2010.2060332Murata, T. (1989). Petri nets: Properties, analysis and applications. Proceedings of the IEEE, 77(4), 541-580. doi:10.1109/5.24143Ramirez-Trevino, A., Ruiz-Beltran, E., Aramburo-Lizarraga, J., & Lopez-Mellado, E. (2012). Structural Diagnosability of DES and Design of Reduced Petri Net Diagnosers. IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, 42(2), 416-429. doi:10.1109/tsmca.2011.2169950Ramirez-Trevino, A., Ruiz-Beltran, E., Rivera-Rangel, I., & Lopez-Mellado, E. (2007). Online Fault Diagnosis of Discrete Event Systems. A Petri Net-Based Approach. IEEE Transactions on Automation Science and Engineering, 4(1), 31-39. doi:10.1109/tase.2006.872120Toutenburg, H. (1974). Fleiss, J. L.: Statistical Methods for Rates and Proportions. John Wiley & Sons, New York-London-Sydney-Toronto 1973. XIII, 233 S. Biometrische Zeitschrift, 16(8), 539-539. doi:10.1002/bimj.19740160814Livingston, E. H., & Cassidy, L. (2005). Statistical Power and Estimation of the Number of Required Subjects for a Study Based on the t-Test: A Surgeon’s Primer. Journal of Surgical Research, 126(2), 149-159. doi:10.1016/j.jss.2004.12.013Ruppert, D. (2011). Statistics and Data Analysis for Financial Engineering. Springer Texts in Statistics. doi:10.1007/978-1-4419-7787-

Internet enabled modelling of extended manufacturing enterprises using the process based techniques

The paper presents the preliminary results of an ongoing research project on Internet enabled process-based modelling of extended manufacturing enterprises. It is proposed to apply the Open System Architecture for CIM (CIMOSA) modelling framework alongside with object-oriented Petri Net models of enterprise processes and object-oriented techniques for extended enterprises modelling. The main features of the proposed approach are described and some components discussed. Elementary examples of object-oriented Petri Net implementation and real-time visualisation are presented

Petri nets for systems and synthetic biology

We give a description of a Petri net-based framework for modelling and analysing biochemical pathways, which uni¯es the qualita- tive, stochastic and continuous paradigms. Each perspective adds its con- tribution to the understanding of the system, thus the three approaches do not compete, but complement each other. We illustrate our approach by applying it to an extended model of the three stage cascade, which forms the core of the ERK signal transduction pathway. Consequently our focus is on transient behaviour analysis. We demonstrate how quali- tative descriptions are abstractions over stochastic or continuous descrip- tions, and show that the stochastic and continuous models approximate each other. Although our framework is based on Petri nets, it can be applied more widely to other formalisms which are used to model and analyse biochemical networks