A model driven approach to web-based traffic simulation.

As the world population increases the number of vehicles in the traffic increases as well, and so the traffic becomes more complex. Problems in the urban traffic such as traffic congestion, car accidents, parking difficulties, etc. have a large impact on people's lives as well as the environment. Therefore, researchers, policy makers, decision takers and planners use expert tools to find the best solutions for traffic and transportation problems. Traffic modeling and simulation has been used for analyzing, designing, planning and managing urban traffic for many years. Various techniques have been proposed and many tools have been developed by researchers to assist the modeling and simulation activities in the traffic domain for more than half a century. However, improving the existing methods and developing new tools for traffic simulation are gaining importance due to the emerging technologies. Web-based modeling and simulation has been popular in the last decade, and has a great promise in terms of collaborative and distributed simulations. Model driven approaches are employed in the simulation field for a long time and have provided rapid development solutions. In this paper, a model driven Web-based traffic simulation framework is proposed and a prototype implementation is presented

An Architectural Framework for Performance Analysis: Supporting the Design, Configuration, and Control of DIS /HLA Simulations

Technology advances are providing greater capabilities for most distributed computing environments. However, the advances in capabilities are paralleled by progressively increasing amounts of system complexity. In many instances, this complexity can lead to a lack of understanding regarding bottlenecks in run-time performance of distributed applications. This is especially true in the domain of distributed simulations where a myriad of enabling technologies are used as building blocks to provide large-scale, geographically disperse, dynamic virtual worlds. Persons responsible for the design, configuration, and control of distributed simulations need to understand the impact of decisions made regarding the allocation and use of the logical and physical resources that comprise a distributed simulation environment and how they effect run-time performance. Distributed Interactive Simulation (DIS) and High Level Architecture (HLA) simulation applications historically provide some of the most demanding distributed computing environments in terms of performance, and as such have a justified need for performance information sufficient to support decision-makers trying to improve system behavior. This research addresses two fundamental questions: (1) Is there an analysis framework suitable for characterizing DIS and HLA simulation performance? and (2) what kind of mechanism can be used to adequately monitor, measure, and collect performance data to support different performance analysis objectives for DIS and HLA simulations? This thesis presents a unified, architectural framework for DIS and HLA simulations, provides details on a performance monitoring system, and shows its effectiveness through a series of use cases that include practical applications of the framework to support real-world U.S. Department of Defense (DoD) programs. The thesis also discusses the robustness of the constructed framework and its applicability to performance analysis of more general distributed computing applications

Modeling and Simulation of Message-Driven Self-Adaptive Systems

Dynamische, sich selbst rekonfigurierende Systeme nutzen Nachrichtenwarteschlangen als gängige Methode zum Erreichen von Entkopplung zwischen Sendern und Empfängern. Das Vorhersagen der Qualität von Systemen zur Entwurfszeit ist wesentlich, da Änderungen in späteren Phasen der Entwicklung sehr viel aufwändiger und teurer sind. Momentan gibt es keine Methode, Nachrichtenwarteschlangen auf architekturellem Level darzustellen und deren Qualitätseinfluss auf Systeme vorherzusagen. Existierende Ansätze modellieren Warteschlangen nicht explizit sondern abstrahieren sie. Warteschlangeneffekte sowie Details der Nachrichten-Infrastruktur wie zum Beispiel Flusskontrolle werden nicht beachtet. Diese Arbeit schlägt ein Meta-Modell vor, das eine solche Repräsentation ermöglicht, und eine Simulations-Schnittstelle zwischen einer Simulation einer komponentenbasierten Architekturbeschreibungssprache und einer Nachrichtenaustausch-Simulation. Das Meta-Modell wurde als Erweiterung des Palladio Komponentenmodells realisiert. Die Schnittstelle wurde implementiert für den Palladio-Simulator SimuLizar und eine von RabbitMQ inspirierte Simulation, die dem AMQP 0.9.1 Protokoll folgt. Dies ermöglicht architekturelle Repräsentation von Nachrichtenaustausch und das Vorhersagen von Qualitätsattributen von nachrichtengetriebenen, selbst-adaptiven Systemen. Die Evaluation anhand einer Fallstudie zeigt die Anwendbarkeit des Ansatzes und seine Vorhersagegenauigkeit für Punkt-zu-Punkt-Kommunikation. Außerdem konnten andere qualitätsbezogene Metriken, wie etwa Nachrichtenwarteschlangenlänge, Ein- und Ausgangsraten von Nachrichtenwarteschlangen, sowie Speicherverbrauch korrekt vorhergesagt werden. Das ermöglicht tiefere Einsichten in die Qualität eines Systems. Wir argumentieren weiterhin, dass der Ansatz in dieser Arbeit selbst-adaptive nachrichtengetriebene Systeme, die sich basierend auf verschiedenen Metriken rekonfigurieren, simulieren kann

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

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

Tenth Workshop and Tutorial on Practical Use of Coloured Petri Nets and the CPN Tools Aarhus, Denmark, October 19-21, 2009

This booklet contains the proceedings of the Tenth Workshop on Practical Use of Coloured Petri Nets and the CPN Tools, October 19-21, 2009. The workshop is organised by the CPN group at the Department of Computer Science, University of Aarhus, Denmark. The papers are also available in electronic form via the web pages: http://www.cs.au.dk/CPnets/events/workshop0

Model-Based Systems Engineering Approach to Distributed and Hybrid Simulation Systems

INCOSE defines Model-Based Systems Engineering (MBSE) as the formalized application of modeling to support system requirements, design, analysis, verification, and validation activities beginning in the conceptual design phase and continuing throughout development and later life cycle phases. One very important development is the utilization of MBSE to develop distributed and hybrid (discrete-continuous) simulation modeling systems. MBSE can help to describe the systems to be modeled and help make the right decisions and partitions to tame complexity. The ability to embrace conceptual modeling and interoperability techniques during systems specification and design presents a great advantage in distributed and hybrid simulation systems development efforts. Our research is aimed at the definition of a methodological framework that uses MBSE languages, methods and tools for the development of these simulation systems. A model-based composition approach is defined at the initial steps to identify distributed systems interoperability requirements and hybrid simulation systems characteristics. Guidelines are developed to adopt simulation interoperability standards and conceptual modeling techniques using MBSE methods and tools. Domain specific system complexity and behavior can be captured with model-based approaches during the system architecture and functional design requirements definition. MBSE can allow simulation engineers to formally model different aspects of a problem ranging from architectures to corresponding behavioral analysis, to functional decompositions and user requirements (Jobe, 2008)

Knowledge Management approaches to model pathophysiological mechanisms and discover drug targets in Multiple Sclerosis

Multiple Sclerosis (MS) is one of the most prevalent neurodegenerative diseases for which a cure is not yet available. MS is a complex disease for numerous reasons; its etiology is unknown, the diagnosis is not exclusive, the disease course is unpredictable and therapeutic response varies from patient to patient. There are four established subtypes of MS, which are segregated based on different characteristics. Many environmental and genetic factors are considered to play a role in MS etiology, including viral infection, vitamin D deficiency, epigenetical changes and some genes. Despite the large body of diverse scientific knowledge, from laboratory findings to clinical trials, no integrated model which portrays the underlying mechanisms of the disease state of MS is available. Contemporary therapies only provide reduction in the severity of the disease, and there is an unmet need of efficient drugs. The present thesis provides a knowledge-based rationale to model MS disease mechanisms and identify potential drug candidates by using systems biology approaches. Systems biology is an emerging field which utilizes the computational methods to integrate datasets of various granularities and simulate the disease outcome. It provides a framework to model molecular dynamics with their precise interaction and contextual details. The proposed approaches were used to extract knowledge from literature by state of the art text mining technologies, integrate it with proprietary data using semantic platforms, and build different models (molecular interactions map, agent based models to simulate disease outcome, and MS disease progression model with respect to time). For better information representation, disease ontology was also developed and a methodology of automatic enrichment was derived. The models provide an insight into the disease, and several pathways were explored by combining the therapeutics and the disease-specific prescriptions. The approaches and models developed in this work resulted in the identification of novel drug candidates that are backed up by existing experimental and clinical knowledge

Hybrid architectural framework for C4ISR and Discrete-Event Simulation (DES) to support sensor-driven model synthesis in real-world scenarios

While the application of a time-step approach in modeling C4ISR in Missile Defense Warfare (MDW) suffers inaccurate time estimation and relative slow speed, Discrete Event Simulation (DES) can elegantly satisfy these shortages. However, current DES frameworks typically rely on detailed efforts in event analysis for numerous replications before software modification of the simulation scenario can be meaningful. Such approaches have limited adaptability, especially regarding flexibility of scenario design and customizability of entity definition. This dissertation proposes an improved DES framework, Adjustable and Extensible Modeling Framework DES (AEMF-DES), which embeds the primary principles of a topical theme into a program to perform adjustable and extensible studies that can be explored by the analyst. To prove the feasibility of AEMF-DES, a Missile-Defense Simulation application (MDSIM) is also developed during this research. MSDIM simulates the C4ISR processes in Missile Defense Warfare and can estimate the overall effectiveness of a defenders deployment or attackers strategy. Additionally, based on the interest in sensor deployment evaluation, a k-coverage rate problem is also studied. Current k-coverage algorithms can only deal with binary and omnidirectional sensor models which cannot provide enough simulation fidelity if higher resolution is needed. An improved k-coverage rate algorithm is proposed in this research to handle the probabilistic and directional sensor models. A separate simulation test successfully demonstrates the feasibility of this new calculation algorithm in estimation of the k-coverage rate problem with probabilistic and directional sensor models. Considered together, the architecture implemented in this example software illustrates the value of integrating hybrid simulation techniques to support C4ISR analysis related to Missile Defense Warfare.http://archive.org/details/hybridrchitectur1094537598Lieutenant Commander, R.O.C. (Taiwan) NavyApproved for public release; distribution is unlimited

Modularization Approaches in the Context of Monolithic Simulations

Qualitätsmerkmale eines Software-Systems wie Zuverlässigkeit oder Performanz können über dessen Erfolg oder Scheitern entscheiden. Diese Qualitätsmerkmale können im klassischen Software-Ingenieurswesen erst bestimmt werden, wenn der Entwurfsprozess bereits vollendet ist und Teile des Software-Systems implementiert sind. Computer-Simulationen erlauben es jedoch Schätzungen dieser Werte schon während des Software-Entwurfs zu bestimmen. Simulationen werden erstellt um bestimmte Aspekte eines Systems zu analysieren. Die Repräsentation des Systems ist auf diese Analyse spezialisiert. Diese Spezialisierung resultiert oft in einer monolithischen Struktur der Simulation. Solch eine Struktur kann jedoch die Wartbarkeit der Simulation negativ beeinflussen und das Verständnis und die Wiederverwendbarkeit der Repräsentation des Systems verschlechtern. Die Nachteile einer monolithischen Struktur können durch das Konzept der Modularisierung reduziert werden. In diesem Ansatz wird ein Problem in kleinere Teilprobleme zerlegt. Diese Zerlegung ermöglicht ein besseres Veständnis und eine bessere Handhabung der Teilprobleme. In dieser Arbeit wird ein Ansatz präsentiert, um die Kopplung von neu entwickelten oder bereits existierenden Simulationen zu einer modularen Simulation zu beschreiben. Dieser Ansatz besteht aus einer Domänenspezifischen Sprache (DSL), die mit modellgetriebenen Technologien entwickelt wird. Die DSL wird in einer Fallstudie angewendet, um die Kopplung von zwei Simulationen zu beschreiben. Weiterhin wird die Kopplung dieser Simulationen mit einem existierenden Kopplungsansatz gemäß der erzeugten Beschreibung manuell implementiert. In dieser Fallstudie wird die Vollständigkeit der Fähigkeit der DSL untersucht, die Kopplung von mehreren Simulation zu einer modularen Simulation zu beschreiben. Weiterhin wird die Genauigkeit des Modularisierungsansatzes bezüglich der Verhaltensbewahrung der modularen Simulation gegenüber der monolithischen Version evaluiert. Hierfür werden die Resultate der modularen Simulation mit denen der monolithischen Version verglichen. Zudem wird die Skalierbarkeit des Ansatzes durch die Betrachtung der Ausführungszeiten untersucht, wenn mehrere Simulationen gekoppelt werden. Außerdem wird der Effekt der Modularisierung auf die Ausführungszeit in Relation zur monolithischen Simulation betrachtet. Die erhaltenen Resultate zeigen, dass die Kopplung der beiden Simulationen der Fallstudie, mit der DSL beschrieben werden kann. Die Resultate bezüglich der Evaluation der Genauigkeit weisen Probleme bei der Interaktion der Simulationen mit dem Kopplungsansatz auf. Nichts desto trotz bleibt das Verhalten der monolithischen Simulation in der modularen Version insgesamt erhalten. Die Evaluation zeigt, dass die modulare Simulation eine Erhöhung der Ausführungszeit im Vergleich zur monolithischen Version erfährt. Zudem deutet die Analyse der Skalierbarkeit darauf hin, dass die Ausführungszeit der modularen Simulation nicht exponentiell mit der Anzahl der gekoppelten Simulationen wächst