Petri Nets Research Articles

Quantitative risk assessment of industrial hot work using Adaptive Bow Tie and Petri Nets

Hot work poses great hazards to industrial operation site. Although regulatory and guidance exist, accidents caused by hot work continue to occur. Risk assessment has proved to be an effective method for risk control. However, current studies paid less attention to the evolution process of industrial hot work accidents and the quantitative risk assessment seems to be insufficient. In this context, we aimed to perform comprehensive risk evolution analysis and quantitative risk assessment of hot work using adaptive bow tie (ABT) and Petri nets (PNs). The ABT model is improved to analyze deep causes, consequences, and their relationships. PNs are employed to conduct quantitative risk assessment. To address uncertainties, the triangular membership function and improved regional center method are proposed to calculate the confidences of all places and transitions in the PNs. The probabilities are finally obtained by data fitting method. The study found that the most likely consequence of hot work accident is near miss. The results also indicate that hot work accident prevention measures should emphasize on the isolation of workplace, combustible gases test, removal of combustible substances, job organization, and job training. Besides, emergency devices maintenance and emergency drilling are critical to prevent accidents from expanding.

Balanced Fuzzy Petri Nets

The paper presents a new Petri Net model: BFPN. Balanced Fuzzy Petri Nets make it possible to model processes that consider gain and loss calculations at the same time. Many business processes need to consider the ability to model a scarcity or loss situation. Balanced fuzzy sets and relations allow a complete visualization and interpretation of the processes.

Performability evaluation of NoSQL-based storage systems

NoSQL database management systems (DBMS) have been commonly adopted in cloud storage applications, as they usually provide better performance and availability than relational DBMSs. Eventual consistency is a remarkable feature of many NoSQL database systems, in which not all redundant nodes have the newest data, but, eventually, such data will be present in all nodes. Distinct consistency levels can be utilized, but they may affect user experience and service level agreements. The assessment of consistency concerning the probability of accessing the newest data is not common, and the jointly evaluation of performance and availability is usually neglected. This work proposes a method based on stochastic Petri nets (SPN) for evaluating the consistency levels of storage systems based on NoSQL DBMS adopting quorum technique. The models take into account distinct consistency levels and redundant nodes for estimating system availability, throughput and the probability of accessing the newest data. Experimental results demonstrate the practical feasibility of our approach.

Comparing perfomance abstractions for collective adaptive systems

Non-functional properties of collective adaptive systems (CAS) are of paramount relevance practically in any application. This paper compares two recently proposed approaches to quantitative modelling that exploit different system abstractions: the first is based on generalised stochastic Petri nets, and the second is based on queueing networks. Through a case study involving autonomous robots, we analyse and discuss the relative merits of the approaches. This is done by considering three scenarios which differ on the architecture used to coordinate the distributed components. Our experimental results assess a high accuracy when comparing model-based performance analysis results derived from two different quantitative abstractions for CAS.

Sprouting Tree for Physiological Stress Assessment Using Fuzzy Petri Net

Background: Stressors have a huge impact on one’s well-being. They affect individual’s mental and physical health, if untreated. The response to these stresses is termed as a stress response. Based on the type and severity of the stimulus, stress can affect the various actions and functioning of the body. This explains how important it becomes to detect the level of stress and treat it well. The best treatment for stress is to identify the factors causing stress and eliminate them in the initial stage. Various methods have been proposed to detect the level of stress. One of the common methods is by using wearable devices to capture EEG signals and use various proposed algorithms to detect the level of stress. However, there are cases where stress cannot be captured by non-invasive technologies. Besides, these technologies cannot determine the stress-causing factors. This paper proposes a methodology to cater to such cases and identify the factors causing stress in the patient. It can also act as a front line methodology to detect if the candidate is suffering from anxiety or stress. The use of fuzzy logic in various healthcare areas has become very evident. This is because it deals with a range of values. While, Petri nets is a network where the arc runs from place to transition and not between places and transitions. It is the best model to use in dynamic and concurrent activities of the system. Thus, a combination of these two logics can provide an extremely competent basis for the implementation of computing reasoning processes and the modeling of systems with uncertainty. Thus, Fuzzy Petri Nets (FPN) have been proposed. This paper proposes the use of FPN in designing a methodology for factors responsible for causing stress and advancing the level of stress in the patient. The methodology is developed by observing the process of food transfer in plants. The authors have also discussed afferent and efferent stress paths. Method: The methodology proposed in this paper uses Fuzzy Petri Net. The algorithm designed in this paper has been named as the Sprouting tree algorithm by the authors. Designing the fault tree is the first and very important step for the correct determination of the level of the stress. The score generated using the Hamilton scale is fed as input to the AND/OR gate system to receive the value of stressor, and thus, drawing a fault tree. The transformation rules are applied to convert the fault tree into the FPN. Then, we derive production rules and reachability matrix. These rules help in normalizing the value obtained via fault tree so that they lie in the range of fuzzy logic. FPN calculates the certainty factor (CF), which represents the state of stress in an individual. Therefore, the values obtained from FPN will finally build a tree, which is named as Sprouting tree. Conclusions: The methodology proposed in this paper is absolutely new to detecting the stress. The future of this work is to observe the accuracy of the proposed algorithm by implementing it with real data, which is under process.

Exploiting the structure of biochemical pathways to investigate dynamical properties with neural networks for graphs.

Dynamical properties of biochemical pathways (BPs) help in understanding the functioning of living cells. Their in silico assessment requires simulating a dynamical system with a large number of parameters such as kinetic constants and species concentrations. Such simulations are based on numerical methods that can be time-expensive for large BPs. Moreover, parameters are often unknown and need to be estimated. We developed a framework for the prediction of dynamical properties of BPs directly from the structure of their graph representation. We represent BPs as Petri nets, which can be automatically generated, for instance, from standard SBML representations. The core of the framework is a neural network for graphs that extracts relevant information directly from the Petri net structure and exploits them to learn the association with the desired dynamical property. We show experimentally that the proposed approach reliably predicts a range of diverse dynamical properties (robustness, monotonicity, and sensitivity) while being faster than numerical methods at prediction time. In synergy with the neural network models, we propose a methodology based on Petri nets arc knock-out that allows the role of each molecule in the occurrence of a certain dynamical property to be better elucidated. The methodology also provides insights useful for interpreting the predictions made by the model. The results support the conjecture often considered in the context of systems biology that the BP structure plays a primary role in the assessment of its dynamical properties. https://github.com/marcopodda/petri-bio (code), https://zenodo.org/record/7610382 (data).

Balancing Static Islands in Dynamically Scheduled Circuits Using Continuous Petri Nets

Balancing Static Islands in Dynamically Scheduled Circuits Using Continuous Petri Nets

Verification And Validation Of Business Process Modeling Using Petri Nets (Case Study of Telkom University FRI Laboratory Business Architecture Domain)

Enterprise Architecture is an approach that is present to form a sustainable organization. However, the average company that has implemented Enterprise Architecture does not see and does not know whether the existing business processes in the company are currently running well, and have been effective and efficient in achieving company goals or not. These conditions make validation and verification of business processes important. In this research, business process testing using the Scrum method with Petri Nets supported by WoPed tools is considered to verify and validate the business architecture design. Testing using the Scrum method is carried out through six stages, namely product backlog, sprint planning, sprint backlog, sprint review, and sprint retrospective. The test results show that several requirements are not met. This condition will have an impact on the efficiency and effectiveness of business processes. Furthermore, gap analysis is carried out with dependencies analysis, there are business processes that have not been verified and validated due to errors in the process that cause time constraints to work on more than one task simultaneously optimally, there is a process stage that is too long so that it hampers the efficiency and effectiveness of business processes.

A Software Testing Workflow Analysis Tool Based on the ADCV Method

Based on two progressive aspects of the modeling problems in business process management (BPM), (1) in order to address the increasing complexity of user requirements on workflows underlying various BPM application scenarios, a more verifiable fundamental modeling method must be invented; (2) to address the diversification of software testing processes, more formalized advanced modeling technology must also be applied based on the fundamental modeling method. Aiming to address these modeling problems, this paper first proposes an ADCV (acquisition, decomposition, combination, and verification) method that runs through the core management links of four types of business processes (mining, decomposition, recombination, and verification) and then describes the compositional structure of the ADCV method and the design of corresponding algorithms. Then, the software testing workflow is managed and monitored using the method, and the corresponding analysis tool is implemented based on Petri nets. At the same time, the tool is applied to the case processing of the software testing workflow. Specifically, the workflow models are established successively through ADCV during the process of business iteration. Then, the analysis tool developed with the ADCV method, the model–view–controller (MVC) design pattern, and Java Swing technology are applied to instances of the software testing workflow to realize the modeling and management of the testing processes. Thus, the analysis tool can guarantee the accuracy of the parameter estimations of related software reliability growth models (SRGMs) and ultimately improve the quality of software products.

Security Analysis and Enhancement of INTERBUS Protocol in ICS Based on Colored Petri Net

The integration of buses in industrial control systems, fueled by advancements such as the Internet of Things (IoT), has led to their widespread adoption, significantly enhancing operational efficiency. However, with the increasing interconnection of systems, ensuring the security of bus communications and protocols has become an urgent priority. This paper focuses on addressing the specific security concerns associated with the widely adopted INTERBUS protocol—a fieldbus protocol. Our approach leverages the theory of colored Petri nets (CPN) for modeling, enabling a comprehensive analysis of the protocol’s security. Rigorous formal verification and analysis of the security protocol are conducted by employing the Dolev–Yao adversary model. Our investigation reveals the presence of three critical vulnerabilities: replay attacks, tampering, and impersonation. To fortify the security of the protocol, we propose the introduction of a key distribution center and the utilization of hash values. Through meticulous analysis and verification, our proposed enhancements effectively reinforce the security performance of the INTERBUS protocol.

Modeling and efficiency analysis of blockchain agriculture products E-commerce cold chain traceability system based on Petri net

The cold chain supply chain of e-commerce has the characteristics of long chain, dispersed production, heterogeneous information sources, etc., which is easy to cause the upstream and downstream information of the supply chain to be broken and opaque. Traditional traceability data is stored in each node enterprise, and there are problems such as low cooperation trust and poor authenticity in the upstream and downstream data transmission process of the supply chain, resulting in consumers' trust crisis on the authenticity of traceability information. Blockchain traceability system through the establishment of multi-party participation, joint maintenance of distributed database, and the use of cryptography and consensus mechanism to establish trust relationships, with data can not be tampered with, sharing of high credibility. On the basis of stochastic Petri net theory, this study constructed a blockchain e-commerce cold chain traceability model centering on the actual application of blockchain technology in logistics traceability to improve the reliability and validity of e-commerce cold chain traceability. Correlation matrix and invariants were used to analyze the validity of the model, and an isomorphic Markov chain was constructed to analyze the effectiveness evolution of the model. This study aims to deepen the understanding of the cold chain traceability system of blockchain e-commerce from the three aspects of the best optimization link, the best synergism scale, and the adaptive ability of the system to provide reference for the improvement of cold chain traceability ability by blockchain technology.

Editorial

Dear Readers,  It gives me great pleasure to announce the tenth regular issue of 2023. In this issue, various topical aspects of computer science are covered by 18 authors from 8 countries in 6 articles. As always, I would like to thank all the authors for their sound research and the editorial board for their highly valuable review effort and suggestions for improvement. These contributions, together with the generous support of the consortium members, sustain the quality of our journal.  In an ongoing effort to further strengthen our journal, I would like to expand the editorial board: If you are a tenured associate professor or above with a strong publication record, you are welcome to apply to join our editorial board. We are also interested in receiving high-quality proposals for special issues on new topics and trends. Please consider yourself and encourage your colleagues to submit high-quality articles or special issue proposals for our journal.  As we want to secure the financial support also for the years to come, we are looking for institutions and libraries to financially support our diamond open access journal as consortium members, who will then benefit from the research community, international visibility, and the opportunity to manage special issues and focused topics within the journal. Please think about the possibility of such financial participation by your institution, we would be very grateful for any kind of support.  In this regular issue, I am very pleased to introduce the following 6 accepted articles: In a collaboration between researchers from Palestine and Jordan, Rasha R. Atallah, Ahmad Sami Al-Shamayleh, and Mohammed A. Awadallah look into the impact of plastic surgery on face recognition models and propose a model based on an artificial neural network with model-agnostic meta-learning (ANN-MAML) for plastic surgery face recognition which results in an accuracy of 90% in all evaluation experiments. In another research collaboration between colleagues from Tunisia and the Kingdom of Saudi Arabia, Samar Bouazizi, Emna Benmohamed, and Hela Ltifi propose in their article an advanced approach to recognize human emotions by using electroencephalogram (EEG) signals and focus their analysis on two specific classes of emotion recognition: H/L Arousal and H/L Valence. Anderson Melo de Morais, Fernando Antonio Aires Lins, and Nelson Souto Rosa from Brazil report on their survey on integration of consensus mechanisms into IoT-based blockchains, analyzing eight dimensions that help understand existing proposals: ease of integration, scalability, latency, throughput, power consumption, configuration issues, integrated algorithms, and adversary tolerance. In the next article Aymane Ezzaim, Aziz Dahbi, Abdelfatteh Haidine, and Abdelhak Aqqal from Morocco carry out a systematic mapping of the literature on AI-based adaptive learning environments and approaches. They examine 93 articles published between 2000 and 2022 and discuss the findings, including the types of AI algorithms used, the objectives targeted by these systems as well as the factors related to adaptation. Sergio-Daniel Sanchez-Solar, Gustavo Rodriguez-Gomez, and Jose Martinez-Carranza from México present their research on the control of a spherical robot rolling over irregular surfaces, which is achieved by controlling two motors for longitudinal and lateral motion in this non-holonomic system, and showed improvements by tuning the controller’s gains using stochastic signals for the longitudinal controller. Last but not least, Layse Santos Souza and Michel S. Soares from Brazil propose in their article the joint use of the SmartCitySysML with TCPN (Timed Coloured Petri Nets) to refine and formally model SysML diagrams that specify internal behavior, and then verify the developed model to prove behavioral properties of an urban traffic signal control system.  Enjoy Reading!  Cordially,  Christian Gütl, Managing Editor  Graz University of Technology, Graz, Austria

Combining SysML and Timed Coloured Petri Nets for Designing Smart City Applications

A smart city is an urban centre that integrates a variety of solutions to improve infrastructure performance and achieve sustainable urban development. Urban roads are a crucial infrastructure highly demanded by citizens and organisations interested in their deployment, performance, and safety. Urban traffic signal control is an important and challenging real-world problem that aims to monitor and improve traffic congestion. The deployment of traffic signals for vehicles or pedestrians at an intersection is a complex activity that changes constantly, so it is necessary to establish rules to control the flow of vehicles and pedestrians. Thus, this article describes the joint use of the SmartCitySysML, a profile proposed by the authors, with TCPN (Timed Coloured Petri Nets) to refine and formally model SysML diagrams specifying the internal behaviour, and then verify the developed model to prove behavioural properties of an urban traffic signal control system.

Model Petri Net Produksi Tahu Pada Industri Skala Rumah Tangga

The process of making tofu includes several steps, namely the process of soaking soybeans, washing soybeans, milling soybeans, boiling or cooking, filtering, settling and adding vinegar. The purpose of this study it was to obtain a Petri Net model of the tofu making process and perform simulations with signed Petri Nets. Simulations are carried out to determine the dynamics that occur during the process of making tofu. The data used is by observation in a household-scale tofu and tempeh processing industry in Tarakan City. The Petri Net model obtained consists of six transitions and ten places. Assuming that every enable transition will always be fired in every state, there are sixteen possible states that can be achieved in the Petri Net simulation.

On the Complexity of Techniques That Make Transition Systems Implementable by Boolean Nets

Let us consider some class of (Petri) nets. The corresponding Synthesis problem consists in deciding whether a given labeled transition system (TS) A can be implemented by a net N of that class. In case of a negative decision, it may be possible to convert A into an implementable TS B by applying various modification techniques, like relabeling edges that previously had the same label, suppressing edges/states/events, etc. It may however be useful to limit the number of such modifications to stay close to the original problem, or optimize the technique. In this paper, we show that most of the corresponding problems are NP-complete if the considered class corresponds to so-called flip-flop nets or some flip-flop net derivatives.

Methods for Efficient Unfolding of Colored Petri Nets

Colored Petri nets offer a compact and user friendly representation of the traditional Place/Transition (P/T) nets and colored nets with finite color ranges can be unfolded into the underlying P/T nets, however, at the expense of an exponential explosion in size. We present two novel techniques based on static analysis in order to reduce the size of unfolded colored nets. The first method identifies colors that behave equivalently and groups them into equivalence classes, potentially reducing the number of used colors. The second method overapproximates the sets of colors that can appear in places and excludes colors that can never be present in a given place. Both methods are complementary and the combined approach allows us to significantly reduce the size of multiple colored Petri nets from the Model Checking Contest benchmark. We compare the performance of our unfolder with state-of-the-art techniques implemented in the tools MCC, Spike and ITS-Tools, and while our approach is competitive w.r.t. unfolding time, it also outperforms the existing approaches both in the size of unfolded nets as well as in the number of answered model checking queries from the 2021 Model Checking Contest.

Compositional Safe Approximation of Response Time Probability Density Function of Complex Workflows

We evaluate a stochastic upper bound on the response time Probability Density Function (PDF) of complex workflows through an efficient and accurate compositional approach. Workflows consist of activities having generally distributed stochastic durations with bounded supports, composed through sequence, choice/merge, and balanced/unbalanced split/join operators, possibly breaking the structure of well-formed nesting. Workflows are specified using a formalism defined in terms of Stochastic Time Petri Nets that permits decomposition into a hierarchy of subworkflows with positively correlated response times, guaranteeing that a stochastically larger end-to-end response time PDF is obtained when intermediate results are approximated by stochastically larger PDFs and when dependencies are simplified by replicating activities appearing in multiple subworkflows. In particular, an accurate stochastically larger PDF is obtained by combining shifted truncated Exponential terms with positive or negative rates. Experiments are performed on sets of manually and randomly generated models with increasing complexity, illustrating under which conditions different decomposition heuristics work well in terms of accuracy and complexity and showing that the proposed approach outperforms simulation having the same execution time.

Mental workload evaluation model of receiver aircraft pilots based on multiple resource theory

AbstractAerial refueling is an extender of air combat capability that has received widespread attention with the development of the military field, particularly the mental workload of the pilot performing the aerial refueling task, as it is the key to the aerial refueling success rate. Therefore, this study analyzes the behavior of receiver aircraft pilots from rendezvous to the separation phase and constructs a mental workload model to improve the aerial refueling success rate. First, the time‐channel‐action unit network was constructed based on Petri net and multiple resource theory (MRT). Second, the mental workload evaluation model was constructed from three dimensions: conventional resource occupation, additional resource occupation, and time occupation. Finally, a simulated experiment was conducted, and the results showed that the mental workload obtained by the model constructed in this study exhibits a high positive correlation with subjective mental workload, pupil diameter, and blink rate, surpassing the accuracy of the traditional MRT model.

Automated modelling of discrete-event processes. Discovering Petri nets including silent transitions by classifying event traces

ABSTRACT This paper addresses the problem of automated modelling of discrete-event processes from event traces that capture the process behaviour. A novel method for building Petri nets (PN) that include silent transitions is presented. The method discovers workflow nets (WFN), a class of PN, from logs of event traces λ. The proposed approach is based on a classification of traces such that λ is partitioned into four classes: normal traces (λN), which do not involve the firing of silent transitions; skip traces (λS), redo traces (λR), and switch traces (λSW), which involve the firing of skip, redo, and switch type silent transitions, respectively. Afterwards, traces in λN are used to build a base WFN N, which may include silent transitions of type initialise and finalise. Then, N is refined by adding the silent transitions corresponding to the classes oftraces λS, λR, and λSW. The algorithms of the method have polynomial-time complexity; implementation and tests using artificial event logs are presented.

Enhancement of Computational Efficiency for Deadlock Recovery of Flexible Manufacturing Systems Using Improved Generating and Comparing Aiding Matrix Algorithms

After the fourth industrial evolution, precision and automatic manufacturing have become increasingly widely accepted in production. With highly variable productivity and flexibility, flexible manufacturing systems (FMS) lower production costs and increase efficiency. Due to its resource shareability, unexpected system deadlock may occur in some specific situations. Many existing works use deadlock prevention as the primary control methodology in research on system deadlock control, while this type of control policy would constrain the transportation resources and reduce the system’s liveness. This paper adopts a new transition-based deadlock recovery policy as the direct control strategy, which uses generating and comparing aiding matrix (GCAM) to determine the optimal control transition. We also improve the existing GCAM-based method by reducing the computational redundancy. This kind of control strategy and its benefit could be demonstrated through two typical systems of simple sequential processes with resource (S3PR) nets and their Petri nets model.