Generalized Stochastic Petri Nets Research Articles

A reliability modeling method for the system subject to common cause failures and competing failures

AbstractCompeting failures are time domain contention situations between the propagated failures (PFs) that originate from dependent components and the failure isolation caused by the trigger component. The methods based on combinatorial analysis commonly used in the analysis of competing failures require a complicated formula derivation and model reduction process. This paper proposes an integrated model based on generalized stochastic Petri nets (GSPNs) for analyzing the competing failures in the system, and further considers the effect of common cause failures (CCFs). The proposed modeling method inherits the advantages of GSPNs and provides a simplified method to compute the reliability of systems, which affect by competing failures and CCFs. Finally, the proposed method is applied in the flight control system (FCS) and demonstrated by the efficient decomposition and aggregation (EDA) method and combinatorial analysis method.

Analyzing stochastic reward nets by model checking and parallel simulation

This paper deals with Stochastic Reward Nets (SRN), which are a powerful extension of Generalized Stochastic Petri Nets (GSPN). SRN have proved their usefulness in modelling and analysis of performance, availability and reliability of complex timed systems. SRN are supported by special-case tools like the Stochastic Petri Net Package (SPNP) which enables both analytic (based on Markov Reward Models) and simulative studies. The work described in this paper argues that there is still a gap in SRN analysis concerning functional correctness and non-deterministic property checking. Toward this a novel approach is proposed, which is based on two developed tools. First a formal reduction of SRN onto the Timed Automata (TA) of the popular Uppaal toolbox was defined and implemented. The Uppaal reduction enables a more complete investigation of SRN models, not allowed by existing SRN tools. However, the practical use of Uppaal forbids to study the performance of large models. Then, an SRN kernel, inspired by the carried formal Uppaal modelling and reasoning, was achieved in Java using the Theatre actor system. The realization supports the parallel simulation of scalable models. The paper applies the developed tools to a realistic grid-computing model and reports some experimental results, together with good execution performance (speedup) when using a scalable version of the grid model on a shared memory multi-core machine.

Towards analyzing the impact of intrusion prevention and response on cyber-physical system availability: A case study of NPP

The idea of industry 4.0 is quite pertinent for CPS. The integration of cyber components enhances a physical system’s capabilities by incorporating intelligence into objects and services. On the other hand, these systems are more vulnerable to cyber-attacks than traditional hard-wired electro-mechanical systems and infrastructure as they are accessible through the Internet. Most of such systems are safety–critical, where successful attacks may result in catastrophic situations by disturbing a critical system’s functionalities. To disrupt the physical process, the attacker should have a deep understanding of operational and control parameters and failure conditions of system components. The attacker first intrudes into the system and subsequently abuses the process parameters to disrupt the physical process. Consideration of these issues is important to evaluate the security of CPS. Hence, this work presents a Generalized Stochastic Petri Net (GSPN) based approach to analyze the effect of integrating the preventive and reactive measures against cyber attacks. By analyzing the model, system security is quantitatively estimated in terms of security metrics such as mean-time-to disrupt and system availability. We validate the combined effect of preventive and responsive measures on a case study of Nuclear power plant (NPP), which is one of the primary sources of electric power generation.

Modelling and availability analysis of container manufacturing industry with Petri Nets

The present work deals with the modeling and availability analysis of Container Manufacturing industry by applying Petri Net (PN) technique and attains the various availability levels by varying various operating parameters that affects the overall availability of the system. This system consist of four subsystems/components namely Gas Cutting machine, Hydraulic Press, Rolling machine and Submerged arc welding (SAW) welding machine. For the mathematical recreation of the system pertaining to the real environment, a Petri module of GRIF 2021 software was used. The model of the system has been made with Generalized Stochastic Petri Net (GSPN) considering exponential distribution for the failure of the components. In the existing research, an attempt has been made to identify the most critical component of system and suggest the repair priorities of different components on the basis of effect of repair rate on overall system availability. Also an attempt has been to find out the optimum number of repairmen. In the present work Hydraulic Press is the critical subsystem having more effect on availability of the system as compared to other subsystems. The optimum no of repairmen required are four thereafter, no increase in system availability seen in the present case. The results of present research work are might be helpful for plant management to design a suitable maintenance strategy to meet one of the objectives i.e. economically maintenance with maximum availability of the system.

Modeling and Analyzing Transmission of Infectious Diseases Using Generalized Stochastic Petri Nets

Some infectious diseases such as COVID-19 have the characteristics of long incubation period, high infectivity during the incubation period, and carriers with mild or no symptoms which are more likely to cause negligence. Global researchers are working to find out more about the transmission of infectious diseases. Modeling plays a crucial role in understanding the transmission of the new virus and helps show the evolution of the epidemic in stages. In this paper, we propose a new general transmission model of infectious diseases based on the generalized stochastic Petri net (GSPN). First, we qualitatively analyze the transmission mode of each stage of infectious diseases such as COVID-19 and explain the factors that affect the spread of the epidemic. Second, the GSPN model is built to simulate the evolution of the epidemic. Based on this model’s isomorphic Markov chain, the equilibrium state of the system and its changing laws under different influencing factors are analyzed. Our paper demonstrates that the proposed GSPN model is a compelling tool for representing and analyzing the transmission of infectious diseases from system-level understanding, and thus contributes to providing decision support for effective surveillance and response to epidemic development.

Risk assessment of FPSO topside based on generalized Stochastic Petri Net

This paper presents a Generalized Stochastic Petri Net (GSPN) approach to assess risk of FPSO topsides, considering the weather window and imperfect maintenance effect. The FPSO topside is considered as a multi-component system consisting of several assemblies. A GSPN model is developed according to system identification and the correlation between different components. The reliability, availability, and maintenance information of the system are derived using the model, based on failures collected from existing literature and database. An operation and maintenance cost model is established, and an optimized maintenance strategy is finally determined based on the GSPN outcomes. The results indicate that the proposed approach is an effective tool to evaluate the system risk and save the maintenance expenditure of FPSO topsides.

Task Allocation Approach for Minimizing Make-Span in Wireless Sensor Actor Networks

Wireless Sensor Actor Networks (WSANs) have contributed to the development of pervasive computing wherein time consideration to perform the tasks of pervasive applications is necessary. Hence, time constraint is one of the major challenges of WSANs. In this paper, we propose an analytical approach based on queuing theory to minimize the total time taken for completion of tasks, i.e., make-span, in WSANs with hybrid architecture. The best allocation rates of tasks to actor nodes are figured out through solving inequities and qualities resulting from a steady state analysis of the proposed model. Applying the calculated tasks arrival rates at each of the actors, the make-span could be minimized. To assess the accuracy of the tasks assignment rates to each of the actors attained from the suggested analytical approach and to provide a graphical representation of the WSAN a formal model in terms of the generalized stochastic Petri net (GSPN) is presented. The proposed GSPN model is analyzed, tasks distribution weights to the actors are determined, and then tasks allocation rates can be computed. Comparing the results achieved from the analytical approach and the GSPN model demonstrates that allocation rates and hence, the make-span figured out from proposed approach and the formal model are the same. Experimental results in typical scenarios show shorter make-span and longer network lifetime compared to when one of the two popular traditional task allocation algorithms, namely, opportunistic load balancing (OLB), and stochastic allocation (SA) algorithms, is used.

A reliability and performance GSPN-Based model for anti-collision RFID algorithms under noisy channels in industrial internet of things

The Industrial Internet of Things (IIoT) has the potential to deeply change the technological landscape in factories, transforming the way automation procedures are performed and relevant objects are identified. For that, however, reliability and performance issues have to be considered when providing the expected communication services. When employing Radio-Frequency Identification (RFID) in an IIoT context, previous works have struggled to improve the efficiency of RFID-complaint systems, usually defining mathematical models for planning and quality assessment. Nevertheless, such models are designed based on error-free communications, which are unreal when considering the error-prone nature of wireless communications in industrial plants. Therefore, this article defines a new formal model based on Generalized Stochastic Petri Nets (GSPN) for RFID communications, modelling different possibilities for errors between readers and RFID tags. Since this proposal employs the EPCglobal UHF Class 1 Gen2 parameters as reference, which are already adopted by the Dynamic Frame Slotted Aloha anti-collision protocol for passive RFID systems, this model can be exploited to assess the reliability and performance of different RFID medium access protocols when assuming noisy channels, supporting better comparisons among different algorithms and protocols. Simulation scenarios are defined to present reliability and performance results when assessing RFID tags reading, which are valuable when designing and maintaining IIoT applications.

Availability modeling and estimation of Fluid Catalytic Cracking Unit using generalized Stochastic Petri Nets

PurposeThe purpose of this paper to present a practical and systematic approach to estimate the availability of a process plant using generalized stochastic Petri nets (GSPNs). The actual live problem at a fluid catalytic cracking unit (FCCU) of a refinery is used to demonstrate this approach.Design/methodology/approachA majority of models used for estimation of availability of a complex system are based on the assumptions that the failure of the system is associated with only a few states, and the system does not face different operating conditions, repair actions and common-cause failures. In reality, this is often not the case. Therefore, it is necessary to construct more sophisticated models without such assumptions. In this paper, an attempt has been made to model interaction of component failures, partial failures of components and common-cause failures.FindingsThe superiority of this approach over other modeling approaches such as fault tree and Markov analysis is demonstrated. The proposed GSPN is a promising tool that can be conveniently used to model and analyze any complex systems.Practical implicationsGSPN was used to model the reactor-regenerator section of FCCU, which is quite a large system, which shows the strength of modeling capability. The use of Petri nets (PNs) for modeling complex systems for the purpose of availability assessment is demonstrated in this paper. Sensitivity analysis was also carried out for various subsystem/components.Originality/valueNo similar work has been conducted for FCCU using GSPN as per literature incorporating different operating conditions and common-cause failures. The understanding and usage of PNs require a steep learning curve for the practitioners, and this paper provides an approach to estimate availability measures for the complex system.

Safety Analysis of Integrated Modular Avionics System Based on FTGPN Method

Compared with federated avionic architecture, the integrated modular avionic (IMA) system architecture in the aircraft can provide more sophisticated and powerful avionic functionality, and meanwhile, it becomes structurally dynamic, variably interconnected, and highly complex. The traditional approach such as fault tree analysis (FTA) becomes neither convenient nor sufficient in making safety analysis of the IMA system. In order to overcome the limitations, the approach that FTA combines with generalized stochastic petri net (GSPN) is proposed. First, FTA is used to establish the static model for the top level of the IMA system, while GSPN is used to build a dynamic model for each cell system. Finally, the combination model is generated, which is called the FTGPN model. Moreover, the FTGPN model is made safety analysis with the PIPE2 tool. According to the simulation result, corresponding measures are taken to meet the safety requirements of the IMA system.

An Evaluation Framework for Comparative Analysis of Generalized Stochastic Petri Net Simulation Techniques

Availability of a common, shared benchmark to provide repeatable, quantifiable, and comparable results is an added value for any scientific community. International consortia provide benchmarks in a wide range of domains, being normally used by industry, vendors, and researchers for evaluating their software products. In this regard, a benchmark of untimed Petri net models was developed to be used in a yearly software competition driven by the Petri net community. However, to the best of our knowledge there is not a similar benchmark to evaluate solution techniques for Petri nets with timing extensions. In this paper, we propose an evaluation framework for the comparative analysis of generalized stochastic Petri nets (GSPNs) simulation techniques. Although we focus on simulation techniques, our framework provides a baseline for a comparative analysis of different GSPN solvers (e.g., simulators, numerical solvers, or other techniques). The evaluation framework encompasses a set of 50 GSPN models including test cases and case studies from the literature, and a set of evaluation guidelines for the comparative analysis. In order to show the applicability of the proposed framework, we carry out a comparative analysis of steady-state simulators implemented in three academic software tools, namely, GreatSPN , PeabraiN , and TimeNET . The results allow us to validate the trustfulness of these academic software tools, as well as to point out potential problems and algorithmic optimization opportunities.

Performance Modeling Based on GSPN for Cyberspace Mimic DNS

Cyberspace mimic domain name system (CMDNS) adopts dynamic heterogeneous redundant architecture with strategic decision mechanism to control the effectiveness of uncertain disturbance. There is lack of methods to evaluate the availability and awareness security of CMDNS. To further describe and analyze the characteristics of CMDNS accurately, the Generalized stochastic Petri net (GSPN) is used to model the attack disturbance and defense of mimic Domain name system (DNS), and the availability and awareness security of Dissimilar redundancy system (DRS) and mimic DNS under different disturbance intensities are compared. We compared the different effect of local service query and real network query on the average response delay. The results show that the introduction of mimic architecture will inevitably pay the corresponding delay cost which increase 9.3% compared with traditional local DNS, but it has little effect on the service which only increases by 1.9% compared with the DNS transmission delay at the network communication level.

Modeling and Analysis of Cyber–Physical System Based on Object-Oriente Generalized Stochastic Petri Net

Cyber–physical system (CPS) is a complex system that contains multiple components working cooperatively. According to its characteristics, we propose an object-oriented generalized stochastic Petri net (OGSPN), in which the CPS is abstracted into several types of objects and its logical structure and working process is visually described. Moreover, we model and measure the time consumed by each activity in CPS for quantitative analysis. To simplify the process of performance analysis on this model, in this article we propose a compression algorithm to convert OGSPN into a generalized stochastic Petri net (GSPN). Considering the uncertainty in CPS, we use a fuzzy mathematics based method to process the compressed model of GSPN for improving the accuracy of the performance analysis. We apply our method to a real-world thick metal plate production line in a manufacturing company, and the availability of our method is verified by extensive experiments.

From software architecture to analysis models and back: Model-driven refactoring aimed at availability improvement

With the ever-increasing evolution of software systems, their architecture is subject to frequent changes due to multiple reasons, such as new requirements. Appropriate architectural changes driven by non-functional requirements are particularly challenging to identify because they concern quantitative analyses that are usually carried out with specific languages and tools. A considerable number of approaches have been proposed in the last decades to derive non-functional analysis models from architectural ones. However, there is an evident lack of automation in the backward path that brings the analysis results back to the software architecture. In this paper, we propose a model-driven approach to support designers in improving the availability of their software systems through refactoring actions. The proposed framework makes use of bidirectional model transformations to map UML models onto Generalized Stochastic Petri Nets (GSPN) analysis models and vice versa. In particular, after availability analysis, our approach enables the application of model refactoring, possibly based on well-known fault tolerance patterns, aimed at improving the availability of the architectural model. We validated the effectiveness of our approach on an Environmental Control System. Our results show that the approach can generate: (i) an analyzable availability model from a software architecture description, and (ii) valid software architecture models back from availability models. Finally, our results highlight that the application of fault tolerance patterns significantly improves the availability in each considered scenario. The approach integrates bidirectional model transformation and fault tolerance techniques to support the availability-driven refactoring of architectural models. The results of our experiment showed the effectiveness of the approach in improving the software availability of the system.

Modeling and Performance Evaluation of Energy Consumption in S-MAC Protocol Using Generalized Stochastic Petri Nets

One of the specifications of wireless sensor networks is the limited power sources for their nodes. Therefore, assessment of energy consumption in these networks is very important, andusing traditional simulators to evaluate the energy consumption of network nodes has become common practice. Simulators often have problems such as fluctuating output values in different implementations of the same scenario, lack of a visual structure to understand the system, and lack of theoretical background for the gained results. In contrast, analytical modeling methods such as Petri nets do not have the aforementioned problems. Also, they have the necessary tools to model and evaluate the performance of investigated system.The Sensor-MAC (S-MAC) protocol in these networks, which operates in MAC layer, is a competition-based protocol designed to reduce power consumption. This paper presents an analytical model based on a Generalized Stochastic Petri Net (GSPN) to evaluate the power consumption of nodes in an S-MAC-based wireless sensor network. The presented Petri model was implemented in PIPE software, and by applying mathematical calculations from the model, we were able to derive the equations for calculating its energy consumption. The validity of the proposed model is measured by implementing similar scenarios in the Castalia simulator. The experiments were conducted in terms of the number of nodes, duty cycle rate, upper layer data flow, and packet size. The results of the presented model are extracted in a much shorter time than the simulator with the same gained values.

Measuring Systemic Risk of Switching Attacks Based on Cybersecurity Technologies in Substations

This paper describes the derivation of steady-state probabilities of the power communication infrastructure based on today's cybersecurity technologies. The elaboration of steady-state probabilities is established on (i) modified models developed such as password models, (ii) new models on digital relays representing the authentication mechanism, and (iii) models for honeypots/honeynet within a substation network. A generalized stochastic Petri net (GSPN) is utilized to formulate the detailed statuses and transitions of components embedded in a cyber-net. Comprehensive steady-state probabilities are quantitatively and qualitatively performed. The methodologies on how transition probabilities and rates are extracted from the network components and a conclusion of actuarial applications is discussed.

Model niezawodności oparty na wydajności przesyłu energii i jego zastosowanie do oceny lotniczego układu hydrauliki siłowej

The power transfer systems (PTS) has special reliability properties, including multiple states and fault dependence. Consequently, traditional binary-state reliability modeling methods cannot accurately evaluate the reliability of PTS. In order to resolve the contradiction between terminal energy demand and power transfer capability of PTS, this paper proposes a novel multi-state reliability model based on power transfer efficiency (PTE) for reliability evaluation of PTS. The multi-state model caused by performance degradation based on PTE is considered in this paper. In addition, the failure correlation in virtue of the system structure and energy allocation mechanism is analyzed in the proposed model, and the corresponding reliability evaluation result is obtained under different terminal energy requirements. The approach is verified on the example of a dual hydraulic actuation system (DHAS), in which the stochastic model based on the generalized stochastic Petri nets (GSPNs) is established and combined with the power transfer capability via universal generating function (UGF). Though changing flow rate to face the degradation rate of hydraulic pump, the reliability assessment of DHAS based on the proposed reliability model is effective and accurate.

Performance modeling and analysis of a Hyperledger-based system using GSPN

As a highly scalable permissioned blockchain platform, Hyperledger Fabric supports a wide range of industry use cases ranging from governance to finance. In this paper, we propose a model to analyze the performance of a Hyperledger-based system by using Generalized Stochastic Petri Nets (GSPN). This model decomposes a transaction flow into multiple phases and provides a simulation-based approach to obtain the system latency and throughput with a specific arrival rate. Based on this model, we analyze the impact of different configurations of ordering service on system performance to find out the bottleneck. Moreover, a mathematical configuration selection approach is proposed to determine the best configuration which can maximize the system throughput. Finally, extensive experiments are performed on a real-time system to validate the proposed model and approaches.

Reliability analysis for complex systems based on generalized stochastic petri nets and EDA approach considering common cause failure

PurposeThis paper aims to deal with the problems of failure dependence and common cause failure (CCF) that arise in reliability analysis of complex systems.Design/methodology/approachFirstly, a dynamic fault tree (DFT) is used to capture the dynamic failure behaviours and converted into an equivalent generalized stochastic petri net (GSPN) for quantitative analysis. Secondly, an efficient decomposition and aggregation (EDA) theory is combined with GSPN to deal with the CCF problem, which exists in redundant systems. Finally, Birnbaum importance measure (BIM) is calculated based on the EDA approach and GSPN model, and it is used to take decisions for system improvement and fault diagnosis.FindingsIn this paper, a new reliability evaluation method for dynamic systems subject to CCF is presented based on the DFT analysis and the GSPN model. The GSPN model is easy to capture dynamic failure behaviours of complex systems, and the movement of tokens in the GSPN model represent the changes in the state of the systems. The proposed method takes advantage of the GSPN model and incorporates the EDA method into the GSPN, which simplifies the reliability analysis process. Meanwhile, simulation results under different conditions show that CCF has made a considerable impact on reliability analysis for complex systems, which indicates that the CCF should not be ignored in reliability analysis.Originality/valueThe proposed method combines the EDA theory with the GSPN model to improve the efficiency of the reliability analysis.

Reliability analysis of the PMU microwave communication networks using generalised stochastic Petri nets

The phasor measurement units (PMUs) have evolved as powerful extrapolations of the supervisory control and data acquisition (SCADA) systems due to their profound application in the real time monitoring of the smart grid (SG). In the SG several such PMUs continuously generate the time tagged phasor measurements which are communicated to a central monitoring station known as the phasor data concentrator (PDC). The communication system plays a pivotal role in the transfer of the phasor measurements to the PDC and thus should be highly reliable. This article presents a detailed approach for the construction of the generalised stochastic Petri nets (GSPNs) for the reliability analysis of the synchrophasor microwave communication networks. These communication networks are optimally planned to achieve maximum reliability without compromising the system observability. Results from the case studies for the North Eastern power grid of India are presented to demonstrate the efficacy of the proposed approach.