1,933 research outputs found

    The GreatSPN tool: recent enhancements

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    GreatSPN is a tool that supports the design and the qualitative and quantitative analysis of Generalized Stochastic Petri Nets (GSPN) and of Stochastic Well-Formed Nets (SWN). The very first version of GreatSPN saw the light in the late eighties of last century: since then two main releases where developed and widely distributed to the research community: GreatSPN1.7 [13], and GreatSPN2.0 [8]. This paper reviews the main functionalities of GreatSPN2.0 and presents some recently added features that significantly enhance the efficacy of the tool

    Translation Of AADL To PNML To Ensure The Utilization Of Petri Nets

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    Architecture Analysis and Design Language (AADL), which is used to design and analyze software and hardware architectures of embedded and real-time systems, has proven to be a very efficient way of expressing the non-functional properties of safety-critical systems and architectural modeling. Petri nets are the graphical and mathematical modeling tools used to describe and study information processing systems characterized as concurrent and distributed. As AADL lacks the formal semantics needed to show the functional properties of such systems, the objective of this research was to extend AADL to enable other Petri nets to be incorporated into Petri Net Markup Language (PNML), an interchange language for Petri nets. PNML makes it possible to incorporate different types of analysis using different types of Petri net. To this end, the interchange format Extensible Markup Language (XML) was selected and AADL converted to AADL-XML (the XML format of AADL) and Petri nets to PNML, the XML-format of Petri nets, via XSLT script. PNML was chosen as the transfer format for Petri nets due to its universality, which enables designers to easily map PNML to many different types of Petri nets. Manual conversion of AADL to PNML is error-prone and tedious and thus requires automation, so XSLT script was utilized for the conversion of the two languages in their XML format. Mapping rules were defined for the conversion from AADL to PNML and the translation to XSLT automated. Finally, a PNML plug-in was designed and incorporated into the Open Source AADL Tool Environment (OSATE)

    Mapping AADL to Petri Net Tool-Sets Using PNML Framework

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    Architecture Analysis and Design Language (AADL) has been utilized to specify and verify non- functional properties of Real-Time Embedded Systems (RTES) used in critical application systems. Examples of such critical application systems include medical devices, nuclear power plants, aer- ospace, financial, etc. Using AADL, an engineer is enable to analyze the quality of a system. For example, a developer can perform performance analysis such as end-to-end flow analysis to guarantee that system components have the required resources to meet the timing requirements relevant to their communications. The critical issue related to developing and deploying safety critical systems is how to validate the expected level of quality (e.g., safety, performance, security) and functionalities (capabilities) at design level. Currently, the core AADL is extensively applied to analyze and verify quality of RTES embed in the safety critical applications. The notation lacks the formal semantics needed to reason about the logical properties (e.g., deadlock, livelock, etc.) and capabilities of safety critical systems. The objective of this research is to augment AADL with exit- ing formal semantics and supporting tools in a manner that these properties can be automatically verified. Toward this goal, we exploit Petri Net Markup Language (PNML), which is a standard act- ing as the intermediate language between different classes of Petri Nets. Using PNML, we interface AADL with different classes of Petri nets, which support different types of tools and reasoning. The justification for using PNML is that the framework provides a context in which interoperability and exchangeability among different models of a system specified by different types of Petri nets is possible. The contributions of our work include a set of mappings and mapping rules between AADL and PNML. To show the feasibility of our approach, a fragment of RT-Embedded system, namely, Cruise Control System has been used

    Analyzing the viability of UAV missions facing cyber attacks

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    With advanced video and sensing capabilities, un-occupied aerial vehicles (UAVs) are increasingly being usedfor numerous applications that involve the collaboration andautonomous operation of teams of UAVs. Yet such vehicle scan be affected by cyber attacks, impacting the viability of their missions. We propose a method to conduct mission via-bility analysis under cyber attacks for missions that employa team of several UAVs that share a communication network. We apply our method to a case study of a survey mission in a wildfire firefighting scenario. Within this context, we show how our method can help quantify the expected mission performance impact from an attack and determine if the mission can remain viable under various attack situations. Our method can be used both in the planning of the mission and for decision making during mission operation.Our approach to modeling attack progression and impact analysis with Petri nets is also more broadly applicable toother settings involving multiple resources that can be used interchangeably towards the same objectiv

    Analysis of Petri Net Models through Stochastic Differential Equations

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    It is well known, mainly because of the work of Kurtz, that density dependent Markov chains can be approximated by sets of ordinary differential equations (ODEs) when their indexing parameter grows very large. This approximation cannot capture the stochastic nature of the process and, consequently, it can provide an erroneous view of the behavior of the Markov chain if the indexing parameter is not sufficiently high. Important phenomena that cannot be revealed include non-negligible variance and bi-modal population distributions. A less-known approximation proposed by Kurtz applies stochastic differential equations (SDEs) and provides information about the stochastic nature of the process. In this paper we apply and extend this diffusion approximation to study stochastic Petri nets. We identify a class of nets whose underlying stochastic process is a density dependent Markov chain whose indexing parameter is a multiplicative constant which identifies the population level expressed by the initial marking and we provide means to automatically construct the associated set of SDEs. Since the diffusion approximation of Kurtz considers the process only up to the time when it first exits an open interval, we extend the approximation by a machinery that mimics the behavior of the Markov chain at the boundary and allows thus to apply the approach to a wider set of problems. The resulting process is of the jump-diffusion type. We illustrate by examples that the jump-diffusion approximation which extends to bounded domains can be much more informative than that based on ODEs as it can provide accurate quantity distributions even when they are multi-modal and even for relatively small population levels. Moreover, we show that the method is faster than simulating the original Markov chain

    Multiple sclerosis disease: A computational approach for investigating its drug interactions

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    Multiple Sclerosis (MS) is a chronic and potentially highly disabling disease that can cause permanent damage and deterioration of the central nervous system. In Europe it is the leading cause of non-traumatic disabilities in young adults, since more than 700,000 EU people suffer from MS. Although recent studies on MS pathophysiology have been performed, providing interesting results, MS remains a challenging disease. In this context, thanks to recent advances in software and hardware technologies, computational models and computer simulations are becoming appealing research tools to support scientists in the study of such disease. Motivated by this consideration, we propose in this paper a new model to study the evolution of MS in silico, and the effects of the administration of the daclizumab drug, taking into account also spatiality and temporality of the involved phenomena. Moreover, we show how the intrinsic symmetries of the model we have developed can be exploited to drastically reduce the complexity of its analysis
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