Performance analysis of stochastic timed Petri nets using linearprogramming approach

Stochastic timed Petri nets are a useful tool in the performance analysis of concurrent systems such as parallel computers, communication networks and flexible manufacturing systems. In general, performance measures of stochastic timed Petri nets are difficult to obtain for practical problems due to their sizes. In this paper, we provide a method to efficiently compute upper and lower bounds for the throughputs and mean token numbers for a large class of stochastic timed Petri nets. Our approach is based on uniformization technique and linear programming     

Performance analysis using Petri nets

The purpose of this paper is to focus on the implementation issues associated with using Petri nets for the performance analysis of discrete event dynamic systems while demonstrating several applications in manufacturing systems. Practical modeling issues will be discussed and several applications will be presented that illustrate the advantages and limitations of this methodology. These issues lead to the definition of several research problems in Petri nets for performance analysis.     

一种随机着色Petri网及模型的性能分析

针对随机Petri网（SPN）在系统性能分析时,其状态空间随着系统规模增大而指数性增长,造成求解稳定状态概率的复杂性的不足,提出了一种随机着色Petri网（SCPN）。分析了它的有界性和可达性,证明了它同构于一个一维连续时间的马尔可夫链;同时,也分析了随机着色Petri网用于建模和系统性能定量分析的方法。     

Regenerative stochastic Petri nets

The stochastic Petri net (SPN) model is well suited to formal representation of concurrency, synchronization, and communication. We define the marking process of an SPN in terms of a general state space Markov chain which describes the net at successive transition firing times. Using structural properties of the SPN and recurrence theory for generalized semi-Markov processes, we establish conditions which ensure that the marking process of an SPN is a regenerative process and that the expected time between regeneration points is finite. This leads to a theory of regenerative simulation in the SPN setting.     

生化网络的随机Petri网建模与分析

细胞的行为是随机性的,学习细胞中的随机性有助于理解细胞的组织,设计和进化。建立、确认和分析随机的生化网络模型是当前计算系统生物学领域的一个重要研究主题。当前,标准的Petri网模型已经成为生化网络模拟和定性分析的有力工具。尝试使用随机Petri网对生化网络进行建模与分析,简单描述了随机Petri网理论对标准Petri网的扩充,通过对二聚作用和肌动蛋白这两个典型例子的建模与演化模拟,介绍、论证了随机Petri网理论的新应用。     

Modeling and performance evaluation of supply chains using batch deterministic and stochastic Petri nets

Batch deterministic and stochastic Petri nets are introduced as a tool for modeling and performance evaluation of supply chains. The new model is developed by enhancing deterministic and stochastic Petri nets (DSPNs) with batch places and batch tokens. By incorporating stochastic Petri nets (SPNs) with the batch features, inhibitor arcs, and marking-dependent weights, operational policies of supply chains such as inventory policies can be easily described in the model. Methods for structural and performance analysis of the model are developed by extending existing ones for DSPNs. As applications, an inventory system and an industrial supply chain are modeled and their performances are evaluated analytically and by simulation, respectively, using this BSPN model. The applications demonstrate that our model and associated methods can solve some important supply chain modeling and analysis issues. Note to Practitioners-This paper was motivated by the problem of performance analysis and optimization of supply chains but it also applies to other discrete event systems where materials are processed in finite discrete quantities (batches) and operations are performed in a batch way because of batch inputs and/or in order to take advantages of the economies of scale. Existing Petri net modeling and analysis tools for such systems ignore their batch features, making their modeling complicated. This paper suggests a new model called batch deterministic and stochastic Petri nets (BDSPNs) by enhancing deterministic and stochastic Petri nets with batch places and batch tokens. Methods for structural and performance analysis of the model are developed. We then show how an inventory system and a real-life supply chain can be modeled and their performances can be evaluated analytically and by simulation respectively based on the model. The model and associated analysis methods therefore provide a promising tool for modeling and performance evaluation of supply chains.     

Correctness verification and performance analysis of real-time systems using stochastic preemptive time Petri nets

Time Petri nets describe the state of a timed system through a marking and a set of clocks. If clocks take values in a dense domain, state space analysis must rely on equivalence classes. These support verification of logical sequencing and quantitative timing of events, but they are hard to be enriched with a stochastic characterization of nondeterminism necessary for performance and dependability evaluation. Casting clocks into a discrete domain overcomes the limitation, but raises a number of problems deriving from the intertwined effects of concurrency and timing. We present a discrete-time variant of time Petri nets, called stochastic preemptive time Petri nets, which provides a unified solution for the above problems through the adoption of a maximal step semantics in which the logical location evolves through the concurrent firing of transition sets. We propose an analysis technique, which integrates the enumeration of a succession relation among sets of timed states with the calculus of their probability distribution. This enables a joint approach to the evaluation of performance and dependability indexes as well as to the verification of sequencing and timeliness correctness. Expressive and analysis capabilities of the model are demonstrated with reference to a real-time digital control system.     

Symbolic execution of concurrent systems using Petri nets

Techniques for analyzing sequential programs in order to improve their reliability have been widely studied in the past. Among the most interesting analysis techniques, we consider symbolic execution. However, analysis techniques for concurrent programs, and in particular symbolic execution, are still an open research area. In this paper, we define a method for symbolic execution of concurrent systems, based on an extension of the Petri net formalism, called EF nets. EF nets are a powerful, highly expressive and general formalism. Depending on the level of abstraction of actions and predicates that one associates to the transitions of the net, EF nets can be used as a high-level specification formalism for concurrent systems, or as a lower level internal representation of concurrent programs. Thus, the model is not dependent on a particular concurrent programming language, but it is flexible enough to be the kernel model for the representation of a wide set of systems and programming languages. In the paper, in order to support the analysis of a concurrent system or program, at first a general algorithm for symbolically executing an EF net is defined. Then, a more efficient algorithm is given for the particular, though important, subclass of EF nets, defined as safe EF nets. Such algorithm is proved to significantly help in reducing the amount of information needed to characterize a symbolic execution. Both the modelling power of the EF nets and the usefulness of the concurrent symbolic execution algorithms defined are illustrated by means of a case study.     

基于Gillespie算法的生化随机Petri网演化分析

Petri网既有严格的数学表达方式,又有直观的图形描述形式,是当前生物化学系统模拟和定性分析的一个有力工具。作为标准Petri网的一个重要扩展,随机Petri网使得可以定量地分析生物化学系统。建立了两个典型的生物化学系统的随机Petri网模型：Schlogl系统和转录调控系统,并使用Gillespie随机仿真算法模拟了这些生化随机Petri网模型的状态演化。     

Prediction of business process durations using non-Markovian stochastic Petri nets

Companies need to efficiently manage their business processes to deliver products and services in time. Therefore, they monitor the progress of individual cases to be able to timely detect undesired deviations and to react accordingly. For example, companies can decide to speed up process execution by raising alerts or by using additional resources, which increases the chance that a certain deadline or service level agreement can be met. Central to such process control is accurate prediction of the remaining time of a case and the estimation of the risk of missing a deadline.To achieve this goal, we use a specific kind of stochastic Petri nets that can capture arbitrary duration distributions. Thereby, we are able to achieve higher prediction accuracy than related approaches. Further, we evaluate the approach in comparison to state of the art approaches and show the potential of exploiting a so far untapped source of information: the elapsed time since the last observed event. Real-world case studies in the financial and logistics domain serve to illustrate and evaluate the approach presented.     

Perturbation analysis of stochastic Petri nets

This paper addresses the sensitivity analysis of stochastic Petri nets (SPNs) using simulations. The goal is to evaluate the derivatives of performance measures with respect to timing parameters. To characterize the underlying stochastic processes of SPNs, we use a generalized semi-Markov process (GSMP) representation and propose a new representation, called GSMP*, which differs from GSMP in the routing mechanism. By using existing results on perturbation analysis of GSMPs and by extending them to GSMP*, unbiased sensitivity estimators are obtained for SPNs simulated under a GSMP or GSMP* framework. Most importantly, we prove that only one simulation run is needed for evaluating both the performance measures and their derivatives for a class of free-choice nets simulated under a GSMP framework and for any free-choice net simulated under a GSMP* framework     

Performance modeling of IEEE 802.11 wireless LANs with stochastic Petri nets

In 1997, IEEE standardized the physical layers and the medium access for wireless local area networks. This paper presents a performance study of the distributed coordination function, the fundamental contention-based access mechanism. Most performance studies adopt unchecked simplifying assumptions or do not reveal all details of the simulation model. We develop a stochastic Petri net model, which captures all relevant system aspects in a concise way. Simulation allows to quantify the influence of many mandatory features of the standard on performance, especially the backoff procedure, extended interframe spaces, and the timing synchronization function. We identify conditions when simplifying assumptions commonly used in analytical modeling are justified. Applying these conditions, we derive a more compact and analytically tractable model from the detailed model.     

Embedded processes in stochastic Petri nets

Embedded discrete time processes are used to study a class of SPNs (stochastic Petri nets) which have a closed-form equilibrium distribution. These SPNs have probabilistic output bags, colored tokens, and alternating periods of arbitrarily distributing enabling and firing times (periods of time between transitions becoming enabled and absorption of tokens and between transitions absorbing tokens and depositing them in output places, respectively). In addition, an aggregation procedure is proposed which, in certain nets, not only reduces a complex SPN to a much simpler skeleton SPN but also obtains results for the skeleton SPN with are exact marginal distributions for the original SPN     

Implementing compositionality for stochastic Petri nets

An implementation of compositionality for stochastic well-formed nets (SWN) and, consequently, for generalized stochastic Petri nets (GSPN) has been recently included in the GreatSPN tool. Given two SWNs and a labelling function for places and transitions, it is possible to produce a third one as a superposition of places and transitions of equal label. Colour domains and arc functions of SWNs have to be treated appropriately. The main motivation for this extension was the need to evaluate a library of fault-tolerant “mechanisms” that have been recently defined, and are now under implementation, in a European project called TIRAN. The goal of the TIRAN project is to devise a portable software solution to the problem of fault tolerance in embedded systems, while the goal of the evaluation is to provide evidence of the efficacy of the proposed solution. Modularity being a natural “must” for the project, we have tried to reflect it in our modelling effort. In this paper, we discuss the implementation of compositionality in the GreatSPN tool, and we show its use for the modelling of one of the TIRAN mechanisms, the so-called local voter. Published online: 24 August 2001     

Reachability analysis of real-time systems using time Petri nets

Time Petri nets (TPNs) are a popular Petri net model for specification and verification of real-time systems. A fundamental and most widely applied method for analyzing Petri nets is reachability analysis. The existing technique for reachability analysis of TPNs, however, is not suitable for timing property verification because one cannot derive end-to-end delay in task execution, an important issue for time-critical systems, from the reachability tree constructed using the technique. In this paper, we present a new reachability based analysis technique for TPNs for timing property analysis and verification that effectively addresses the problem. Our technique is based on a concept called clock-stamped state class (CS-class). With the reachability tree generated based on CS-classes, we can directly compute the end-to-end time delay in task execution. Moreover, a CS-class can be uniquely mapped to a traditional state class based on which the conventional reachability tree is constructed. Therefore, our CS-class-based analysis technique is more general than the existing technique. We show how to apply this technique to timing property verification of the TPN model of a command and control (C2) system.     

Discrete-event simulation of fluid stochastic Petri nets

The purpose of this paper is to describe a method for the simulation of the recently introduced fluid stochastic Petri nets. Since such nets result in rather complex system of partial differential equations, numerical solution becomes a formidable task. Because of a mixed (discrete and continuous) state space, simulative solution also poses some interesting challenges, which are addressed in the paper