Stochastic Petri Net Model Research Articles

Modeling and Performance Analysis of Satellite Network Moving Target Defense System with Petri Nets

With the development of satellite communication networks and the increase of satellite services, security problems have gradually become some of the most concerning issues. Researchers have made great efforts, including conventional safety methods such as secure transmission, anti-jamming, secure access, and especially the new generation of active defense technology represented by MTD. However, few scholars have theoretically studied the influence of active defense technique on the performance of satellite networks. Formal modeling and performance analysis have not been given sufficient attention. In this paper, we focus on the performance evaluation of satellite network moving target defense system. Firstly, two Stochastic Petri Nets (SPN) models are constructed to analyze the performance of satellite network in traditional and active defense states, respectively. Secondly, the steady-state probability of each marking in SPN models is obtained by using the isomorphism relation between SPN and Markov Chains (MC), and further key performance indicators such as average time delay, throughput, and the utilization of bandwidth are reasoned theoretically. Finally, the proposed two SPN models are simulated based on the PIPE platform. In addition, the effect of parameters on the selected performance indexes is analyzed by varying the values of different parameters. The simulation results prove the correctness of the theoretical reasoning and draw the key factors affecting the performance of satellite network, which can provide an important theoretical basis for the design and performance optimization of the satellite network moving target defense system.

Disassembly sequence planning of waste auto parts

ABSTRACT The disassembly of used products is a critical procedure in remanufacturing, and different disassembly strategies are often obtained from different perspectives. To describe the disassembly process more accurately, the uncertainty of the information in the disassembly process should be considered. Therefore, random variables are introduced for disassembly time, cost, and effort. Based on the extended stochastic Petri net modeling method and stochastic programming theory, a stochastic optimization algorithm combined with artificial intelligence technology and a multiobjective genetic algorithm are designed, and a multiobjective optimization model for the disassembly sequence of used car parts under uncertain conditions is successfully constructed. This model considers the viewpoint of the decision maker. Moreover, the Monte Carlo method is applied to solve the multiobjective optimization model, and the validity and practicability of the model are verified by an example of an automotive transmission. Implications: With the rapid development of the economy and the shortening of the product life cycle, the rate of product renewal is getting faster and faster, which also leads to the production of a large number of waste products. According to the forecast of the relevant departments, it is estimated that, in 2020, there will be about 35 million used televisions, 15 million used refrigerators, 13 million used washing machines, 12 million used air conditioners, 57 million used computers, and 8.3 million scrapped cars. Waste products contain a lot of renewable resources. If they cannot be effectively recycled, it will be a great waste of resources, and unreasonable disposal of waste products may have a negative impact on the environment. Therefore, due to environmental pressure and economic drive, product recycling and remanufacturing activities have caused widespread concern in society. Disassembly is defined as the operation or activity of disassembling an assembly such as a product, assembly, or component, and is the result of multiple removal operations of the product. It is a prerequisite for the efficient recycling of products and the first link in remanufacturing, that is, disassembly as a new production activity, which can provide raw materials for the smooth progress of the remanufacturing production plan, namely, old rough or used parts. Efficient dismantling not only saves natural resources and energy, but also effectively reduces environmental pollution. It is also an important guarantee for promoting the healthy development of the circular economy and achieving sustainable industrial development. The length of time required for the dismantling process, the level of costs, and the amount of profits obtained will directly affect the economic benefits of the recycling of end-of-life products. Therefore, the evaluation and optimization of the dismantling process of waste products have become one of the current hot issues. The research on the dismantling of waste products is conducive to speeding up the recycling process of waste, to a greater extent, the rapid and full recovery of resources, and to a certain extent, it will provide value basis and theoretical significance for subsequent research.

Stochastic Petri Net Based Modeling of Emergency Medical Rescue Processes during Earthquakes.

The post-disaster emergency medical rescue (EMR) is critical for people’s lives. This paper presents a stochastic Petri net (SPN) model based on the process of the rescue structure and a Markov chain model (MC), which is applied to the optimization of the EMR process, with the aim of identifying the key activities of EMR. An isomorphic MC model is developed for measuring and evaluating the time performance of the EMR process during earthquakes with the data of the 2008 Wenchuan earthquake. This paper provides a mathematical approach to simulate the process and to evaluate the efficiency of EMR. Simultaneously, the expressions of the steady state probabilities of this system under various states are obtained based on the MC, and the variations of the probabilities are analyzed by changing the firing rates for every transition. Based on the concrete data of the event, the authors find the most time consuming and critical activities for EMR decisions. The model results show that the key activities can improve the efficiency of medical rescue, providing decision-makers with rescue strategies during the large scale earthquake.

Performance evaluation of smart cooperative traffic lights in VANETs

Vehicular ad hoc network (VANET) is an emerging new type of network, consisting of vehicles as mobile nodes and temporary communication links among these nodes. One of the crucial topics in VANETs is related to how to use traffic lights to optimise vehicle mobility. The traffic lights can work cooperatively to reduce traffic jams by communicating with the vehicles. However, the architecture of smart traffic lights offers challenges related to network latency restrictions and resource constraints. This paper presents a performance evaluation of a cooperative smart traffic light using a stochastic Petri net (SPN) model. The proposed model can calculate the mean response time, resource utilisation, and the number of requests discards. Three case studies are presented to illustrate how useful the model can be. Besides, we conduct real experiments to validate the proposed model by using micro-controllers (Raspberry Pi) that emulate traffic lights. The model is highly flexible, allowing developers and system administrators to calibrate eighteen parameters.

Performance evaluation of smart cooperative traffic lights in VANETs

Vehicular ad hoc network (VANET) is an emerging new type of network, consisting of vehicles as mobile nodes and temporary communication links among these nodes. One of the crucial topics in VANETs is related to how to use traffic lights to optimise vehicle mobility. The traffic lights can work cooperatively to reduce traffic jams by communicating with the vehicles. However, the architecture of smart traffic lights offers challenges related to network latency restrictions and resource constraints. This paper presents a performance evaluation of a cooperative smart traffic light using a stochastic Petri net (SPN) model. The proposed model can calculate the mean response time, resource utilisation, and the number of requests discards. Three case studies are presented to illustrate how useful the model can be. Besides, we conduct real experiments to validate the proposed model by using micro-controllers (Raspberry Pi) that emulate traffic lights. The model is highly flexible, allowing developers and system administrators to calibrate eighteen parameters.

Model-based dependability evaluation of a Wireless Communication System in a Virtually Coupled Train Set

A new paradigm based on the concept of virtual coupling of train sets is being elaborated to provide innovative solutions so as to increase efficiency, operational flexibility, line capacity, competitiveness among market players and quality of consumer experience. Train-to-Train (T2T) and Train-to-Ground (T2G) wireless communications will be the backbone for the implementation of the virtual coupling functionalities. In the present paper, we perform a model-based dependability analysis of the wireless communication system under virtual coupling operation. Namely, Stochastic Colored Petri Net (SCPN) models are developed to depict the exchanges of the various information needed under virtual coupling operation. Dependability evaluation is then performed by means of simulation. In particular, the impact of various communication parameters is scrutinized while taking into account different operational scenarios. The obtained results allow the identification of the most impacting aspects on dependability analysis and provide valuable inputs to support the technological choices in terms of communication to implement virtual coupling.

Reliability Assessment Model of IMA Partition Software Using Stochastic Petri Nets

In order to reduce the failure rate of Integrated Modular Avionics (IMA) partition software, due to the reliability block diagram (RBD) method, fault tree analysis (FTA) method and GO method cannot describe the state transition process of partition software, according to the ARINC 653 standard and the actual running status of the partition software, this paper determines the state machine and conversion delay of the partition software, and establishes the stochastic Petri nets (SPN) reliability quantitative model of the partition software. By proving that each transition in the SPN model of the partition software approximately obeying exponential distribution, and according to the reachable state tree of the SPN isomorphic to a homogeneous Markov chain (MC), the steady-state probability of the partition software in the fault state is calculated to be 5.2778*10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-9</sup> by using MC stochastic process theory. The factors affecting the reliability of the partition software are obtained, and the sensitivity of each factor to the model is studied. Finally, the relevant conclusions are drawn to provide guidance for improving the reliability of partition software.

DevOps workflow verification and duration prediction using non‐Markovian stochastic Petri nets

AbstractIn this paper, we provide a non‐Markovian Stochastic Petri Net (SPN) model for DevOps workflow specification, and we determine how business processes are carried out. After describing our model semantics, we show how general properties related to liveness and safety can be checked. After that, we provide several extensions on SPNs (SPN) the notation and expressivity to check some specific properties related to actors' (Developers and Operators) availability, interactions between the actors, and execution failures detection linked to the DevOps steps. Next, we validate the proposed model relevance with MATLAB simulation through a specific DevOps case study. Finally, we propose a truncated density function to anticipate the delays related to the DevOps business process overall steps.

An UML Based Performance Evaluation of Real-Time Systems Using Timed Petri Net

Performance is a critical non-functional parameter for real-time systems and performance analysis is an important task making it more challenging for complex real-time systems. Mostly performance analysis is performed after the system development but an early stage analysis and validation of performance using system models can improve the system quality. In this paper, we present an early stage automated performance evaluation methodology to analyse system performance using the UML sequence diagram model annotated with modeling and analysis of real-time and embedded systems (MARTE) profile. MARTE offers a performance domain sub-profile that is used for representing real-time system properties essential for performance evaluation. In this paper, a transformation technique and transformation rules are proposed to map the UML sequence diagram model into a Generalized Stochastic Timed Petri net model. All the transformation rules are implemented using a metamodel based approach and Atlas Transformation Language (ATL). A case study from the manufacturing domain a Kanban system is used for validating the proposed technique.

Petri Net modelling approach for analysing the behaviour of Wnt/[inline-formula removed]-catenin and Wnt/Ca2+ signalling pathways in arrhythmogenic right ventricular cardiomyopathy.

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is an inherited heart muscle disease that may result in arrhythmia, heart failure and sudden death. The hallmark pathological findings are progressive myocyte loss and fibro fatty replacement, with a predilection for the right ventricle. This study focuses on the adipose tissue formation in cardiomyocyte by considering the signal transduction pathways including Wnt/[inline-formula removed]-catenin and Wnt/Ca2+ regulation system. These pathways are modelled and analysed using stochastic petri nets (SPN) in order to increase our comprehension of ARVC and in turn its treatment regimen. The Wnt/[inline-formula removed]-catenin model predicts that the dysregulation or absence of Wnt signalling, inhibition of dishevelled and elevation of glycogen synthase kinase 3 along with casein kinase I are key cytotoxic events resulting in apoptosis. Moreover, the Wnt/Ca2+ SPN model demonstrates that the Bcl2 gene inhibited by c-Jun N-terminal kinase protein in the event of endoplasmic reticulum stress due to action potential and increased amount of intracellular Ca2+ which recovers the Ca2+ homeostasis by phospholipase C, this event positively regulates the Bcl2 to suppress the mitochondrial apoptosis which causes ARVC.

A Stochastic Petri Net-Based Model of the Involvement of Interleukin 18 in Atherosclerosis.

Interleukin 18 (IL-18) is a proinflammatory and proatherogenic cytokine with pleiotropic properties, which is involved in T and NK cell maturation and the synthesis of other inflammatory cytokines and cell adhesion molecules. It plays a significant role in orchestrating the cytokine cascade, accelerates atherosclerosis and influences plaque vulnerability. To investigate the influence of IL-18 cytokine on atherosclerosis development, a stochastic Petri net model was built and then analyzed. First, MCT-sets and t-clusters were generated, then knockout and simulation-based analysis was conducted. The application of systems approach that was used in this research enabled an in-depth analysis of the studied phenomenon. Our results gave us better insight into the studied phenomenon and allow revealing that activation of macrophages by the classical pathway and IL-18-MyD88 signaling axis is crucial for the modeled process.

Architecture-level particular risk modeling and analysis for a cyber-physical system with AADL

Cyber-physical systems (CPSs) are becoming increasingly important in safety-critical systems. Particular risk analysis (PRA) is an essential step in the safety assessment process to guarantee the quality of a system in the early phase of system development. Human factors like the physical environment are the most important part of particular risk assessment. Therefore, it is necessary to analyze the safety of the system considering human factor and physical factor. In this paper, we propose a new particular risk model (PRM) to improve the modeling ability of the Architecture Analysis and Design Language (AADL). An architecture-based PRA method is presented to support safety assessment for the AADL model of a cyber-physical system. To simulate the PRM with the proposed PRA method, model transformation from PRM to a deterministic and stochastic Petri net model is implemented. Finally, a case study on the power grid system of CPS is modeled and analyzed using the proposed method.

A two-dimension security assessing model for CMDs combined with Generalized Stochastic Petri net

Cyber mimic defenses have recently emerged as a dynamic heterogeneity redundancy architecture, which adjust the asymmetry between defenders and attackers by reconfiguring the system according to the network scenario. Some studies have investigated the effectiveness of security models, however, there is still a lack of convincing and practical methods to assess CMD networks quantitatively. Thus, in this paper, we propose a two-dimension model that calculates those details as a digital result to compare different CMD networks. In addition, the proposed method demonstrates good scalability in different networks. Specifically, in the first dimension, i.e., attacking a single node, we elaborate on system configurations and employ the Generalized Stochastic Petri net model to capture the effectiveness of different behaviors from gamers. To quantify the impacts of those behaviors, we parameterized them using a Poisson process, common vulnerabilities and exposures, and the common vulnerability scoring system. In the second dimension, we adopt Markov chains and the Martingale theory to analyze the attack process along the attack chain. Finally, security metrics and countermeasures under different scenarios are presented to verify the effectiveness of CMD, which provides some guidance for designing future systems with acceptable cost.

Linkage Control Policy on Area Pacesetter and Active Compensation for Chip Angle Correction

In order to improve the optical and electrical consistency in lighting and display, light emitting diode (LED) dies should be sorted and aligned precisely one by one. As per given current production process practices, the sorting efficiency is required to be more than 36 thousand units per hour (KUPH), while the alignment deviation should not exceed 1 mil (25.4 $\mu \text{m}$ ) and all dies’ angle deviations should fall within 5°. Among all the requirements, the chip angle correction is particularly difficult to achieve because a small die correction on wafer would cause a change in all dies’ positions, leading to significant performance degradation. This results in an ambiguity, due to the difficulty in balancing efficiency and accuracy. In this article, the influence factors of the accuracy deviation caused by the angle correction are analyzed in detail, and the negative effect caused by tiny deformation of the elastic substrate is studied with comprehensive experiments. The parallel scheduling mechanism of the angle correction is analyzed, and the influences on sorting performance are evaluated with stochastic petri net (SPN) model, so that the suitable working area is disclosed. A local compensation strategy using the local deformation trend of the membrane is utilized to optimize the accuracy of precorrection. Further, the alignment area is actively compensated according to the alignment precision requirements, so that the performance and accuracy requirements are balanced. In the chip packaging field, microchip angle correction is often needed. This method is applicable to similar situation and chips are adhesive on membrane.

HEALTHCARE CRITICAL INFRASTRUCTURE STOCHASTIC INTERDEPENDENCIES SIMULATION MODEL FOR SMART CITIES: FLOOD DISASTER SCENARIO

Abstract. Healthcare Critical Infrastructure (HCI) is not an independent network; the operation of a healthcare facility depends on many other Critical Infrastructure (CI) networks such as electric supply CI, water supply CI, etc., forming an interdependent CI network. During a flooding disaster event, as the flood levels rise, the interdependent HCI network becomes vulnerable. A failure in one of the CI results in failure of the dependent CI. During a disaster event such as flooding, the failures propagate and cause cascading failures like a domino effect. The paper proposes an IoT based flood sensor network integrated with a stochastic Petri net interdependent healthcare critical infrastructure network simulation model. An IoT (Internet of Things) based flood water level sensor network can deliver real-time information on the flood conditions at the various interdependent CI facilities in the interdependent network, using the Sensor Observation Services (SOS). The Stochastic Petri Net (SCPN) based interdependent Healthcare Critical Infrastructure (HCI) simulation model, is used to model and simulate the stochastic interdependencies between the interdependent HCI networks. The real-time flood sensor network is integrated with the SCPN based interdependent HCI simulation model. The end to end system is developed in a spatiotemporal environment. This kind of an integrated simulation model will help the end-user to understand system dynamics in real-time, visualize and predict the propagation of cascading failure scenarios in an Interdependent HCI network in a spatiotemporal environment, during a flooding scenario. Real-time information simulation would help disaster response personnel to respond to the question, ‘what if something else happens?

Reliability of Autonomous Internet of Things Systems With Intrusion Detection Attack-Defense Game Design

In this article we develop an intrusion detection attack–defense game for Internet of Things (IoT) systems for which autonomous IoT devices collaboratively solve a problem. We develop an analytical model to determine the conditions under which malicious nodes have no incentives to perform attack in the intrusion detection attack–defense game. We also develop a stochastic Petri net model to analyze the effect of attack–defense behaviors on system reliability, given a definition of system failure conditions as input. The performance evaluation results demonstrate that our intrusion detection system (IDS) attack-defense game design greatly improves system reliability over existing autonomous IoT systems without gaming design consideration when attacks are reckless and intensive.

Availability analysis of design configurations to compose virtual performance‐optimized data center systems in next‐generation cloud data centers

SummaryNext‐generation cloud data centers are based on software‐defined data center infrastructures that promote flexibility, automation, optimization, and scalability. The Redfish standard and the Intel Rack Scale Design technology enable software‐defined infrastructure and disaggregate bare‐metal compute, storage, and networking resources into virtual pools to dynamically compose resources and create virtual performance‐optimized data centers (vPODs) tailored to workload‐specific demands. This article proposes four chassis design configurations based on Distributed Management Task Force's Redfish industry standard applied to compose vPOD systems, namely, a fully shared design, partially shared homogeneous design, partially shared heterogeneous design, and not shared design; their main difference is based on the used hardware disaggregation level. Furthermore, we propose models that combine reliability block diagram and stochastic Petri net modeling approaches to represent the complexity of the relationship between the pool of disaggregated hardware resources and their power and cooling sources in a vPOD. These four proposed design configurations were analyzed and compared in terms of availability and component's sensitivity indexes by scaling their configurations considering different data center infrastructure. From the obtained results, we can state that, in general, when one increases the hardware disaggregation, availability is improved. However, after a given point, the availability level of the fully shared, partially shared homogeneous, and partially shared heterogeneous configurations remain almost equal, while the not shared configuration is still able to improve its availability.

Deciphering the expression dynamics of ANGPTL8 associated regulatory network in insulin resistance using formal modelling approaches.

ANGPTL8 is a recently identified novel hormone which regulates both glucose and lipid metabolism. The increase in ANGPTL8 during compensatory insulin resistance has been recently reported to improve glucose tolerance and a part of cytoprotective metabolic circuit. However, the exact signalling entities and dynamics involved in this process have remained elusive. Therefore, the current study was conducted with a specific aim to model the regulation of ANGPTL8 with emphasis on its role in improving glucose tolerance during insulin resistance. The main contribution of this study is the construction of a discrete model (based on kinetic logic of René Thomas) and its equivalent Stochastic Petri Net model of ANGPTL8 associated Biological Regulatory Network (BRN) which can predict its dynamic behaviours. The predicted results of these models are in‐line with the previous experimental observations and provide comprehensive insights into the signalling dynamics of ANGPTL8 associated BRN. The authors’ results support the hypothesis that ANGPTL8 plays an important role in supplementing the insulin signalling pathway during insulin resistance and its loss can aggravate the pathogenic process by quickly leading towards Diabetes Mellitus. The results of this study have potential therapeutic implications for treatment of Diabetes Mellitus and are suggestive of its potential as a glucose‐lowering agent.

Privacy and safety analysis of timed stochastic discrete event systems using Markovian trajectory-observers

Various aspects of privacy and safety in many application domains can be assessed based on proper analysis of successive measurements that are collected about a given system. This work is devoted to such issues in the context of timed stochastic discrete event systems (DES) that are modeled with partially observed timed stochastic Petri net models. The first contribution is to introduce a k-step trajectory-observer, which is a construction that captures all possible k-suffixes of the trajectories that are consistent with a given sequence of measurements that has been recorded. When the system behaves according to Markovian dynamics (i.e., all event occurrences are distributed in time with exponential probability density functions), a parallel-like composition of the timed system with the resulting observer is proposed that leads to a Markovian process. The second contribution is to take advantage of the Markovian analysis to compute certain important characteristic times during which the underlying system should satisfy a given property (based on the suffixes of length k of a given trajectory). To illustrate the approach, we consider two particular properties, namely k-suffix language opacity and k-diagnosability, which can be studied in a stochastic timed context using the Markovian trajectory observer.

Edge servers placement in mobile edge computing using stochastic Petri nets

Mobile edge computing (MEC) is a network architecture that takes advantage of cloud computing features (such as high availability and elasticity) and makes use of computational resources available at the edge of the network in order to enhance the mobile user experience by decreasing the service latency. MEC solutions need to dynamically allocate the requests as close as possible to their users. However, the request placement depends not only on the geographical location of the servers, but also on their requirements. Based on this fact, this paper proposes a stochastic Petri net (SPN) model to represent an MEC scenario and analyse its performance, focusing on the parameters that can directly impact the service mean response time (MRT) and resource utilisation level. In order to present the applicability of our work, we propose three case studies with numerical analysis using real-world values. The main objective is to provide a practical guide to help infrastructure administrators to adapt their architectures, finding a trade-off between MRT and level of resource usage.