05 Fakultät Informatik, Elektrotechnik und Informationstechnik
Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/6
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Item Open Access Spatial aware geographic Forwarding for mobile ad hoc networks(2002) Tian, Jing; Stepanov, Illya; Rothermel, KurtStateless greedy forwarding based on physical positions of nodes is considered to be more scalable than conventional topology-based routing. However, the stateless nature of geographic forwarding also prevents it from predicting holes in node distribution. Thus, frequent topology holes can significantly degrade the performance of geographic forwarding. So far the approaches mostly depend on excessive state maintenance at nodes to avoid forwarding failures at topology holes. In this paper, we propose and analyse spatial aware geographic forwarding (SAGF), a new approach that proactively avoids constant topology holes caused by spatial constraints while still preserving the advantage of stateless forwarding. Geographic source routes (GSR) based on intermediate locations are selected to bypass topology holes. Proactive route selection based on the spatial knowledge is a general approach, and thus can be used with any geographic forwarding algorithms. We evaluate our approach by extending greedy forwarding with spatial knowledge. Simulation results comparing with GPSR show that even simple spatial information can effectively improve the performance of geographic forwarding.Item Open Access System mechanisms for partial rollback of mobile agent execution(1999) Straßer, Markus; Rothermel, KurtMobile agent technology has been proposed for various fault-sensitive application areas, including electronic commerce, systems management and active messaging. Recently proposed protocols providing the exactly-once execution of mobile agents allow the usage of mobile agents in these application areas. Based on these protocols, a mechanism for the application-initiated partial rollback of the agent execution is presented in this paper. The rollback mechanism uses compensating operations to roll back the effects of the agent execution on the resources and uses a mixture of physical logging and compensating operations to rollback the state of the agent. The introduction of different types of compensating operations and the integration of an itinerary concept with the rollback mechanism allows performance improvements during the agent rollback as well as during the normal agent execution.Item Open Access Routinen zur Auswertung von Simulationen mit ESPResSo zur virtuellen Weiterentwicklung von Innenraumfiltern(2016) Lekar, DominikInnenraumfilter dienen dazu, die Insassen und das Lüftungsgerät vor Staub, Pollen und anderen Partikeln zu schützen. Die derzeitige Entwicklung von solchen Filtermedien erfolgt meist nach der Trial-and-Error-Methode und erfordert daher einen hohen Versuchsaufwand. Um die Entwicklung der Filtermedien voranzubringen, wird in dieser Arbeit ein Skript für die Software für Molekulardynamik „ESPResSo“ erweitert. Ziel ist die kontinuierliche Beladung einzelner Fasern mit unterschiedlichen Partikeltypen. Die Evaluierung des Skripts geschieht durch die Auswertung von gewonnenen Simulationsergebnissen. Aus diesen wird ersichtlich, dass der Abscheidegrad eines Partikeltyps von seiner Trägheit abhängt und dieser durch die Wahl unterschiedlicher Parameter beeinflusst werden kann.Item Open Access Integration von Data Mining und Online Analytical Processing : eine Analyse von Datenschemata, Systemarchitekturen und Optimierungsstrategien(2003) Schwarz, Holger; Mitschang, Bernhard (Prof. Dr.-Ing. habil.)Die technischen Möglichkeiten, Daten zu erfassen und dauerhaft zu speichern, sind heute so ausgereift, dass insbesondere in Unternehmen und anderen Organisationen große Datenbestände verfügbar sind. In diesen Datenbeständen, häufig als Data Warehouse bezeichnet, sind alle relevanten Informationen zu den Organisationen selbst, den in ihnen ablaufenden Prozessen sowie deren Interaktion mit anderen Organisationen enthalten. Vielfach stellt die zielgerichtete Analyse der Datenbestände den entscheidenden Erfolgsfaktor für Organisationen dar. Zur Analyse der Daten in einem Data Warehouse sind verschiedenste Ansätze verfügbar und erprobt. Zwei der wichtigsten Vertreter sind das Online Analytical Processing (OLAP) und das Data Mining. Beide setzen unterschiedliche Schwerpunkte und werden bisher in der Regel weitgehend isoliert eingesetzt. In dieser Arbeit wird zunächst gezeigt, dass eine umfassende Analyse der Datenbestände in einem Data Warehouse nur durch den integrierten Einsatz beider Analyseansätze erzielt werden kann. Einzelne Fragestellungen, die sich aus diesem Integrationsbedarf ergeben werden ausführlich diskutiert. Zu den betrachteten Fragestellungen gehört die geeignete Modellierung der Daten in einem Data Warehouse. Bei der Bewertung gängiger Modellierungsansätze fließen insbesondere die Anforderungen ein, die sich durch den beschriebenen Integrationsansatz ergeben. Als Ergebnis wird ein konzeptuelles Datenmodell vorgestellt, das Informationen in einer Weise strukturiert, die für OLAP und Data Mining gleichermaßen geeignet ist. Im Bereich der logischen Modellierung werden schließlich diejenigen Schematypen identifiziert, die die Integration der Analyseansätze geeignet unterstützen. Im nächsten Schritt sind die für Data Mining und OLAP unterschiedlichen Systemarchitekturen Gegenstand dieser Arbeit. Deren umfassende Diskussion ergibt eine Reihe von Defiziten. Dies führt schließlich zu einer erweiterten Systemarchitektur, die die Schwachstellen beseitigt und die angestrebte Integration geeignet unterstützt. Die erweiterte Systemarchitektur weist eine Komponente zur anwendungsunabhängigen Optimierung unterschiedlicher Analyseanwendungen auf. Ein dritter Schwerpunkt dieser Arbeit besteht in der Identifikation geeigneter Optimierungsansätze hierfür. Die Bewertung der Ansätze wird einerseits qualitativ durchgeführt. Andererseits wird das Optimierungspotenzial der einzelnen Ansätze auch auf der Grundlage umfangreicher Messreihen gezeigt.Item Open Access Scalable computer network emulation using node virtualization and resource monitoring(2011) Maier, Steffen Dirk; Rothermel, Kurt (Prof. Dr. rer. nat. Dr. h. c.)Ongoing development of computer network technology requires new communication protocols on all layers of the protocol stack to adapt to and to exploit technology specifics. The performance of new protocol implementations has to be evaluated before deployment. Computer network emulation enables the execution of real unmodified protocol implementations within a configurable synthetic environment. Since network properties are reproduced synthetically, emulation supports reproducible measurement results for wired and wireless networks. Meaningful evaluation scenarios typically involve a large number of communicating nodes. Reproducing the network properties of the medium access control layer can be accomplished efficiently on cheap common off the shelf computers and allows to evaluate network protocols, transport protocols, and applications. However, meaningful emulation scenario sizes often require more nodes than affordable computers. To scale the number of nodes in an emulation scenario beyond the available computers, we discuss approaches to virtualization and operating system partitioning. Focusing on the latter, we argue for virtual protocol stacks, which provide an extremely lightweight node virtualization enabling the execution of multiple instances of software to be evaluated on each physical computer. To connect virtual nodes on the same and on different computers, we design and implement a highly efficient software communication switch. A centralized emulation control component distributes dynamic network property updates which result from node mobility for instance. To handle the large number of nodes and thus increased updates, we propose a hierarchical control where the central component delegates updates to sub-components distributed over the computers of an emulation system. Extensive evaluations show the scalability of our virtualized network emulation system. Virtual nodes executed on the same computer share its limited resources. Hosting too many virtual nodes on the same computer may lead to resource contention. This can cause unrealistic measurement results and is thus undesirable. Discussing different approaches to handle resource contention, we argue for detection and recovery. We define quality criteria that allow the detection of resource contention. In order to observe those quality criteria during emulation experiments, we propose a highly lightweight monitoring approach. Our monitoring is based on instrumenting an operating system kernel and observing basic resource scheduling events. This enables the detection of even peak resource usage within a split second. Thorough evaluations demonstrate the effectiveness of quality criteria and monitoring as well as the negligible overhead of our monitoring approach.Item Open Access Development and analysis of a window manager concept for consolidated 3D rendering on an embedded platform(2015) Zhao, HanNowadays with the information technology rapidly developing, an increasing number of 2D and 3D graphics are used in automotive displaying systems, to provide vehicle information, driving assistance, etc. With the demand of 3D models interacting with each other, an implementation should have a 3D compositing capability. However, traditional 2D compositing implementations are not capable of 3D models compositing tasks. In order to composite 3D graphics on embedded platform, the 3D compositing implementation is necessary. Therefore, a concept of window manager is developed aiming to composite 3D graphics with an optimized efficiency for embedded platform. Specially for automotive platforms, a virtualization is made to unify multiple Electronic Control Units (ECUs) into one single ECU platform. On this platform, a server and multiple clients are implemented with dedicated Virtual Machines (VMs). The server is in charge of rendering tasks requested from clients. Based on this, a 3D compositing concept is implemented. It handles efficiently the multiple 3D applications situation using a method of off-screen rendering. A server-side virtualization is also implemented by replacing certain client-side commands during commands forwarding. With this virtualization implementation, multiple applications run simultaneously with accessing single 3D GPU only. Moreover, due to this implementation, monolithic rendering operations affecting all applications, e.g. uniform lighting operation, are possible.Item Open Access Robust execution of workflows in a distributed environment(2013) Schäfer, David RichardIn many business applications, workflows are used to describe business processes. Employees and machines get instructions from a plan (the workflow) to be guided or controlled. The workflows make it easier to create and manage business processes. Therefore, using workflows is the standard procedure in the business area today. The distributed execution of workflows plays an important role as almost all nodes are connected to a network today. The importance even increases with the emerging of pervasive environments. Because these systems are prone to failures, it is important to develop reliability methods that ensure that the system works properly even if failures occur. When the robustness of a system in a distributed environment shall be increased, the service that has to be executed is usually replicated and executed by two or more nodes. This means that the exact same behavior is executed by multiple nodes and thereby increases the reliability of the system by being able to cope with node failures. Changing the order of the activities or using alternative activities to increase the robustness is promising because when each node receives a different workflow that achieves the same goal, the possibility of failures should be further reduced by decoupling the replicas in respect of time and hardware dependencies. We developed a robustness metric that evaluates the robustness of a set of workflow replicas. We also developed methods and algorithms that generate workflows with different orders and alternative tasks within reasonable time. Our evaluations show that our proposed methods work significantly better than deploying a brute-force method to achieve the same behavior.Item Open Access Investigating dynamics by multilevel phase space discretization(2006) Fundinger, Danny Georg; Levi, Paul (Prof. Dr.)The subject of the thesis is the numerical investigation of dynamical systems. The aim is to provide approaches for the localization of several topological structures which are of vital importance for the global analysis of dynamical systems, namely, periodic orbits, the chain recurrent set, repellers, attractors and their domains of attraction as well as stable, unstable and connecting manifolds. The techniques introduced do not require any a priori knowledge about a system, and are also not restricted by the stability of the solution. Furthermore, they can generally be applied to a wide range of dynamical systems. Two theoretical concepts are considered to be at the center of the research - symbolic analysis and the RIM method. The underlying basic approach for both of them is multilevel phase space discretization. This means that a part of the phase space, the area of investigation, is subdivided in a finite number of sets. Then, instead of each point of the phase space, only these sets are subject of further analysis. The main target of every method proposed is to find those sets which contain parts of the solution and subdivide them into smaller parts until a desired accuracy is reached. In case of symbolic analysis, a directed graph is constructed which represents the structure of the state space for the investigated dynamical system. This graph is called the symbolic image of the focused system and can be seen as an approximation of the system flow. The theoretical background regarding the symbolic image graph as well as the constructive methods applied on it were already described in a series of works by G. Osipenko. In this work, strategies are introduced for a practical application. This requires the extension of the theoretical concepts and the development of appropriate algorithms and data structures. In practice, it turned out that these aspects are essential cornerstones for the usability of the discussed methods. Also some sophisticated tunings of the basic methods are proposed in order to extent the field of practical investigation. Although symbolic analysis can be seen as the main stimulation of this work, the investigation was not limited to it. Indeed, several shortcomings regarding the solution of some problems can be observed if the method is applied in practice. This led to the development of the RIM method. The core intention of the method is to solve the root finding problem. The standard approach toward this task is the application of an iteration scheme based on the Newton method. However, it has shown that such Newton schemes have several structural disadvantages which are especially crucial in the context of the fields of investigation which are relevant to this work. The RIM method proposes an alternative approach which does not require the application of any Newton-like method. Numerical case studies revealed that in several nontrivial scenarios the RIM method provides better results than both, symbolic analysis as well as Newton-based methods. Two applications of the RIM method for the investigation of dynamical systems are provided. One of them is the detection of periodic points. The other is the computation of stable manifolds. The proposed methods contribute not only to the direct investigation and simulation of specific dynamical processes but also to the research in the field of dynamical system theory in general. This is due to the fact that progress in theory depends to a large extent on the observation and investigation of phenomenons. These phenomenons can often only be revealed, analyzed and verified by numerical experiments. The presented numerical case studies give some concrete examples for the application of the methods. Hereby, the dynamical models are taken from different fields of scientific research, like geography, biology, meteorology, or physics.Item Open Access Extended Business Rules(2011) Liu, JianIn dieser Diplomarbeit wurden der Entwurf, die Implementierung und der Testen des extended Business Rule Managers betrachtet. Dazu wurde zunächst eine grafische Benutzeroberfläche zur Definition Business Regeln bereitgestellt. Dann kamen Web Services als Regel-Prüfer zum Einsatz. Diese Regel-Prüfer müssen nicht nur die erstellten Regeln prüfen, sondern auch sich mit einer Datenbank zur Findung der Werte der operativen Daten verbinden. Schließlich wurde die erstellten Web Services in einem Geschäftsprozess getestet. Darüber hinaus wurden alle benötigen Technologien auch vorgestellt.Item Unknown Large-scale data mining analytics based on MapReduce(2014) Ranjan, SunnyIn this work, we search for possible approaches to large-scale data mining analytics. We perform an exploration about the existing MapReduce and other MapReduce-like frameworks for distributed data processing and the distributed file systems for distributed data storage. We study in detail about Hadoop Distributed File System (HDFS) and Hadoop MapReduce software framework. We analyse the benefits of newer version of Hadoop software framework which provides better scalability solution by segregating the cluster resource management task from MapReduce framework. This version is called YARN and is very flexible in supporting various kinds of distributed data processing other than batchmode processing of MapReduce. We also looked into various implementations of data mining algorithms based on MapReduce to derive a comprehensive concept about developing such algorithms. We also looked for various tools that provided MapRedcue based scalable data mining algorithms. We could only find Mahout as a tool specially based on Hadoop MapReduce. But the tool developer team decided to stop using Hadoop MapReduce and to use instead Apache Spark as the underlying execution engine. WEKA also has a very small subset of data mining algorithms implemented using MapReduce which is not properly maintained and supported by the developer team. Subsequently, we found out that Apache Spark, apart from providing an optimised and a faster execution engine for distributed processing also provided an accompanying library for machine learning algorithms. This library is called Machine Learning library (MLlib). Apache Spark claimed that it is much faster than Hadoop MapReduce as it exploits the advantages of in-memory computations which is particularly more beneficial for iterative workloads in case of data mining. Spark is designed to work on variety of clusters: YARN being one of them. It is designed to process the Hadoop data. We selected to perform a particular data mining task: decision tree learning based classification and regression data mining. We stored properly labelled training data for predictive mining tasks in HDFS. We set up a YARN cluster and run Spark's MLlib applications on this cluster. These applications use the cluster managing capabilities of YARN and the distributed execution framework of Spark core services. We performed several experiments to measure the performance gains, speed-up and scaleup of implementations of decision tree learning algorithms in Spark's MLlib. We found out much better than expected results for our experiments. We achieved a much higher than ideal speed-up when we increased the number of nodes. The scale-up is also very excellent. There is a significant decrease in run-time for training decision tree models by increasing the number of nodes. This demonstrates that Spark's MLlib decision tree learning algorithms for classification and regression analysis are highly scalable.