26 research outputs found

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

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    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

    Energy Modeling of Wireless Sensor Nodes Based on Petri Nets

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    Energy minimization is of great importance in wireless sensor networks in extending the battery lifetime. Accurately understanding the energy consumption characteristics of each sensor node is a critical step for the design of energy saving strategies. This paper develops a detailed probabilistic model based on Petri nets to evaluate the energy consumption of a wireless sensor node. The model factors critical components of a sensor node, including processors with emerging energy-saving features, wireless communication components, and an open or closed workload generator. Experimental results show that this model is more flexible and accurate than Markov models. The model provides a useful simulation platform to study energy saving strategies in wireless sensor networks

    Effiziente simulationsbasierte Optimierung farbiger stochastischer Petri-Netze

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    Modelle erleichtern das Verstehen und Verbesserung technischer Systeme. Dabei werden durch Abstraktion komplexer Systeme nur noch wesentliche Bestandteile von Design und Verhalten nachgebildet, das Modell ist damit deutlich leichter handhabbar und verständlicher als das reale System. Durch Anpassung des Modells bzw. seiner Konfiguration wird eine Optimierung des Systems erleichtert oder überhaupt erst ermöglicht. Optimierung eines Modells bedeutet dabei, aus der Menge aller Systemkonfigurationen diejenige(n) zu bestimmen, für die sich das Modell - und damit später auch das reale System - hinsichtlich bestimmter Bewertungskriterien bestmöglich verhält. Aufgrund zufälliger Einflussgrößen wird das Finden einer optimalen Systemkonfiguration auf konventionellem Wege unmöglich oder zumindest unrealistisch schwer. Hier setzt die indirekte Optimierung durch Simulation an. Ein großes Problem ist dabei der enorme Zeitbedarf von Simulationen. Thema der Arbeit ist die Frage, wie die Effizienz simulationsbasierter Optimierung durch Kombination bekannter und neuer Verfahren erhöht werden kann. Dafür wurde ein neues Verfahren der adaptiven Genauigkeitssteuerung mittels Multiphasen-Optimierung entwickelt. Für die Beantwortung der Frage wurde zunächst ein Analysewerkzeug erstellt, mit dem die verschiedenen Verfahren zur simulationsbasierten Optimierung untersucht werden können. Um auf bisherige Vorarbeiten und Veröffentlichungen am Fachgebiet aufzubauen, wurde für diese Arbeit das Simulationssystem TimeNET verwendet. Als formales Modell für komplexe, diskrete Systeme kommen farbige, stochastische Petri-Netze (Stochastic Colored Petri Nets) zum Einsatz. Typische Probleme simulationsbasierter Optimierung werden betrachtet. Es werden bekannte Verfahren verglichen und ein neues Verfahren vorgestellt, welches den Simulationszeitbedarf in Betracht zieht und damit auf die Anwendung für simulationsbasierte Optimierung zugeschnitten ist. Abschließend werden die Verfahren anhand von SCPN-Simulationen und Benchmarkfunktionen bewertet.Models facilitate the understanding and improvement of technical systems. By abstracting complex systems, only essential components of design and behavior are reproduced, making the model much easier to handle and more understandable than the real system. By adapting the model or its configuration, an optimization of the system is made easier or even possible. Optimization of a model means to determine from the set of all system configurations the one for which the model - and thus later also the real system - behaves best in terms of certain evaluation criteria. Due to random factors, finding an optimal system configuration by conventional means, e.g. through (Mixed Integer) Linear Programming often is impossible or at least unrealistic hard. This is where indirect optimization through simulation comes into play. A big challenge is the amount of time required by simulations. Topic of this thesis is increasing the efficiency of simulation-based optimization by combining well known and new methods. For this purpose, a new method of adaptive accuracy control using multi-phase optimization has been developed and integrated into a prototype software tool. To build on previous work and publications, the simulation system TimeNET was used for this work. Therefore (Stochastic Colored Petri Nets) are used as a formal model for complex, discrete systems. Typical problems of simulation-based optimization are considered. Known methods are compared and a new method is presented, which takes into account the required simulation time and thus is tailored to simulation-based optimization. Finally, the presented methods are evaluated using SCPN simulations and benchmark function

    MACHS: Mitigating the Achilles Heel of the Cloud through High Availability and Performance-aware Solutions

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    Cloud computing is continuously growing as a business model for hosting information and communication technology applications. However, many concerns arise regarding the quality of service (QoS) offered by the cloud. One major challenge is the high availability (HA) of cloud-based applications. The key to achieving availability requirements is to develop an approach that is immune to cloud failures while minimizing the service level agreement (SLA) violations. To this end, this thesis addresses the HA of cloud-based applications from different perspectives. First, the thesis proposes a component’s HA-ware scheduler (CHASE) to manage the deployments of carrier-grade cloud applications while maximizing their HA and satisfying the QoS requirements. Second, a Stochastic Petri Net (SPN) model is proposed to capture the stochastic characteristics of cloud services and quantify the expected availability offered by an application deployment. The SPN model is then associated with an extensible policy-driven cloud scoring system that integrates other cloud challenges (i.e. green and cost concerns) with HA objectives. The proposed HA-aware solutions are extended to include a live virtual machine migration model that provides a trade-off between the migration time and the downtime while maintaining HA objective. Furthermore, the thesis proposes a generic input template for cloud simulators, GITS, to facilitate the creation of cloud scenarios while ensuring reusability, simplicity, and portability. Finally, an availability-aware CloudSim extension, ACE, is proposed. ACE extends CloudSim simulator with failure injection, computational paths, repair, failover, load balancing, and other availability-based modules

    Performance and Reliability of Non-Markovian Heterogeneous Distributed Computing Systems

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    Average service time, quality-of-service (QoS), and service reliability associated with heterogeneous parallel and distributed computing systems (DCSs) are analytically characterized in a realistic setting for which tangible, stochastic communication delays are present with nonexponential distributions. The departure from the traditionally assumed exponential distributions for event times, such as task-execution times, communication arrival times and load-transfer delays, gives rise to a non-Markovian dynamical problem for which a novel age dependent, renewal-based distributed queuing model is developed. Numerical examples offered by the model shed light on the operational and system settings for which the Markovian setting, resulting from employing an exponential-distribution assumption on the event times, yields inaccurate predictions. A key benefit of the model is that it offers a rigorous framework for devising optimal dynamic task reallocation (DTR) policies systematically in heterogeneous DCSs by optimally selecting the fraction of the excess loads that need to be exchanged among the servers, thereby controlling the degree of cooperative processing in a DCSs. Key results on performance prediction and optimization of DCSs are validated using Monte-Carlo (MC) simulation as well as experiments on a distributed computing testbed. The scalability, in the number of servers, of the age-dependent model is studied and a linearly scalable analytical approximation is derived

    Toward a decision support system for the clinical pathways assessment

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    This paper presents a decision support system to be used in hospital management taskswhich is based on the clinical pathways. We propose a very simple graphical modeling lan-guage based on a small number of primitive elements through which the medical doctorscould introduce a clinical pathway for a specific disease. Three essential aspects relatedto a clinical pathway can be specified in this language: (1) patient flow; (2) resource uti-lization; and (3) information interchange. This high-level language is a domain specificmodeling language calledHealthcare System Specification (HSS), and it is defined as anUnified Modeling Language (UML) profile. A model to model transformation is also pro-posed in order to obtain, from the pathways HSS specification, a Stochastic Well-formedNet (SWN) model that enables a formal analysis of the modeled system and, if needed, toapply synthesis methods enforcing specified requirements. The transformation is based onthe application of local rules. The clinical pathway of hip fracture from the “Lozano Blesa”University hospital in Zaragoza is taken as an example

    Distributed Simulation of High-Level Algebraic Petri Nets

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    In the field of Petri nets, simulation is an essential tool to validate and evaluate models. Conventional simulation techniques, designed for their use in sequential computers, are too slow if the system to simulate is large or complex. The aim of this work is to search for techniques to accelerate simulations exploiting the parallelism available in current, commercial multicomputers, and to use these techniques to study a class of Petri nets called high-level algebraic nets. These nets exploit the rich theory of algebraic specifications for high-level Petri nets: Petri nets gain a great deal of modelling power by representing dynamically changing items as structured tokens whereas algebraic specifications turned out to be an adequate and flexible instrument for handling structured items. In this work we focus on ECATNets (Extended Concurrent Algebraic Term Nets) whose most distinctive feature is their semantics which is defined in terms of rewriting logic. Nevertheless, ECATNets have two drawbacks: the occultation of the aspect of time and a bad exploitation of the parallelism inherent in the models. Three distributed simulation techniques have been considered: asynchronous conservative, asynchronous optimistic and synchronous. These algorithms have been implemented in a multicomputer environment: a network of workstations. The influence that factors such as the characteristics of the simulated models, the organisation of the simulators and the characteristics of the target multicomputer have in the performance of the simulations have been measured and characterised. It is concluded that synchronous distributed simulation techniques are not suitable for the considered kind of models, although they may provide good performance in other environments. Conservative and optimistic distributed simulation techniques perform well, specially if the model to simulate is complex or large - precisely the worst case for traditional, sequential simulators. This way, studies previously considered as unrealisable, due to their exceedingly high computational cost, can be performed in reasonable times. Additionally, the spectrum of possibilities of using multicomputers can be broadened to execute more than numeric applications

    Software Perfomance Assessment at Architectural Level: A Methodology and its Application

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    Las arquitecturas software son una valiosa herramienta para la evaluación de las propiedades cualitativas y cuantitativas de los sistemas en sus primeras fases de desarrollo. Conseguir el diseño adecuado es crítico para asegurar la bondad de dichas propiedades. Tomar decisiones tempranas equivocadas puede implicar considerables y costosos cambios en un futuro. Dichas decisiones afectarían a muchas propiedades del sistema, tales como su rendimiento, seguridad, fiabilidad o facilidad de mantenimiento. Desde el punto de vista del rendimiento software, la ingeniería del rendimiento del software (SPE) es una disciplina de investigación madura y comúnmente aceptada que propone una evaluación basada en modelos en las primeras fases del ciclo de vida de desarrollo software. Un problema en este campo de investigación es que las metodologías hasta ahora propuestas no ofrecen una interpretación de los resultados obtenidos durante el análisis del rendimiento, ni utilizan dichos resultados para proponer alternativas para la mejora de la propia arquitectura software. Hasta la fecha, esta interpretación y mejora requiere de la experiencia y pericia de los ingenieros software, en especial de expertos en ingeniería de prestaciones. Además, a pesar del gran número de propuestas para evaluar el rendimiento de sistemas software, muy pocos de estos estudios teóricos son posteriormente aplicados a sistemas software reales. El objetivo de esta tesis es presentar una metodología para el asesoramiento de decisiones arquitecturales para la mejora, desde el punto de vista de las prestaciones, de las sistemas software. La metodología hace uso del Lenguaje Unificado de Modelado (UML) para representar las arquitecturas software y de métodos formales, concretamente redes de Petri, como modelo de prestaciones. El asesoramiento, basado en patrones y antipatrones, intenta detectar los principales problemas que afectan a las prestaciones del sistema y propone posibles mejoras para mejoras dichas prestaciones. Como primer paso, estudiamos y analizamos los resultados del rendimiento de diferentes estilos arquitectónicos. A continuación, sistematizamos los conocimientos previamente obtenidos para proponer una metodología y comprobamos su aplicabilidad asesorando un caso de estudio real, una arquitectura de interoperabilidad para adaptar interfaces a personas con discapacidad conforme a sus capacidades y preferencias. Finalmente, se presenta una herramienta para la evaluación del rendimiento como un producto derivado del propio ciclo de vida software
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