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 Automated composition of adaptive pervasive applications in heterogeneous environments(2012) Schuhmann, Stephan Andreas; Rothermel, Kurt (Prof. Dr. rer. nat. Dr. h. c.)Distributed applications for Pervasive Computing represent a research area of high interest. Configuration processes are needed before the application execution to find a composition of components that provides the required functionality. As dynamic pervasive environments and device failures may yield unavailability of arbitrary components and devices at any time, finding and maintaining such a composition represents a nontrivial task. Obviously, many degrees of decentralization and even completely centralized approaches are possible in the calculation of valid configurations, spanning a wide spectrum of possible solutions. As configuration processes produce latencies which are noticed by the application user as undesired waiting times, configurations have to be calculated as fast as possible. While completely distributed configuration is inevitable in infrastructure-less Ad Hoc scenarios, many realistic Pervasive Computing environments are located in heterogeneous environments, where additional computation power of resource-rich devices can be utilized by centralized approaches. However, in case of strongly heterogeneous pervasive environments including several resource-rich and resource-weak devices, both centralized and decentralized approaches may lead to suboptimal results concerning configuration latencies: While the resource-weak devices may be bottlenecks for decentralized configuration, the centralized approach faces the problem of not utilizing parallelism. Most of the conducted projects in Pervasive Computing only focus on one specific type of environment: Either they concentrate on heterogeneous environments, which rely on additional infrastructure devices, leading to inapplicability in infrastructure-less environments. Or they address homogeneous Ad Hoc environments and treat all involved devices as equal, which leads to suboptimal results in case of present resource-rich devices, as their additional computation power is not exploited. Therefore, in this work we propose an advanced comprehensive adaptive approach that particularly focuses on the efficient support of heterogeneous environments, but is also applicable in infrastructure-less homogeneous scenarios. We provide multiple configuration schemes with different degrees of decentralization for distributed applications, optimized for specific scenarios. Our solution is adaptive in a way that the actual scheme is chosen based on the current system environment and calculates application compositions in a resource-aware efficient manner. This ensures high efficiency even in dynamically changing environments. Beyond this, many typical pervasive environments contain a fixed set of applications and devices that are frequently used. In such scenarios, identical resources are part of subsequent configuration calculations. Thus, the involved devices undergo a quite similar configuration process whenever an application is launched. However, starting the configuration from scratch every time not only consumes a lot of time, but also increases communication overhead and energy consumption of the involved devices. Therefore, our solution integrates the results from previous configurations to reduce the severity of the configuration problem in dynamic scenarios. We prove in prototypical real-world evaluations as well as by simulation and emulation that our comprehensive approach provides efficient automated configuration in the complete spectrum of possible application scenarios. This extensive functionality has not been achieved by related projects yet. Thus, our work supplies a significant contribution towards seamless application configuration in Pervasive Computing.Item Open Access Interacting with large high-resolution display workplaces(2018) Lischke, Lars; Schmidt, Albrecht (Prof.)Large visual spaces provide a unique opportunity to communicate large and complex pieces of information; hence, they have been used for hundreds of years for varied content including maps, public notifications and artwork. Understanding and evaluating complex information will become a fundamental part of any office work. Large high-resolution displays (LHRDs) have the potential to further enhance the traditional advantages of large visual spaces and combine them with modern computing technology, thus becoming an essential tool for understanding and communicating data in future office environments. For successful deployment of LHRDs in office environments, well-suited interaction concepts are required. In this thesis, we build an understanding of how concepts for interaction with LHRDs in office environments could be designed. From the human-computer interaction (HCI) perspective three aspects are fundamental: (1) The way humans perceive and react to large visual spaces is essential for interaction with content displayed on LHRDs. (2) LHRDs require adequate input techniques. (3) The actual content requires well-designed graphical user interfaces (GUIs) and suitable input techniques. Perceptions influence how users can perform input on LHRD setups, which sets boundaries for the design of GUIs for LHRDs. Furthermore, the input technique has to be reflected in the design of the GUI. To understand how humans perceive and react to large visual information on LHRDs, we have focused on the influence of visual resolution and physical space. We show that increased visual resolution has an effect on the perceived media quality and the perceived effort and that humans can overview large visual spaces without being overwhelmed. When the display is wider than 2 m users perceive higher physical effort. When multiple users share an LHRD, they change their movement behavior depending whether a task is collaborative or competitive. For building LHRDs consideration must be given to the increased complexity of higher resolutions and physically large displays. Lower screen resolutions provide enough display quality to work efficiently, while larger physical spaces enable users to overview more content without being overwhelmed. To enhance user input on LHRDs in order to interact with large information pieces, we built working prototypes and analyzed their performance in controlled lab studies. We showed that eye-tracking based manual and gaze input cascaded (MAGIC) pointing can enhance target pointing to distant targets. MAGIC pointing is particularly beneficial when the interaction involves visual searches between pointing to targets. We contributed two gesture sets for mid-air interaction with window managers on LHRDs and found that gesture elicitation for an LHRD was not affected by legacy bias. We compared shared user input on an LHRD with personal tablets, which also functioned as a private working space, to collaborative data exploration using one input device together for interacting with an LHRD. The results showed that input with personal tablets lowered the perceived workload. Finally, we showed that variable movement resistance feedback enhanced one-dimensional data input when no visual input feedback was provided. We concluded that context-aware input techniques enhance the interaction with content displayed on an LHRD so it is essential to provide focus for the visual content and guidance for the user while performing input. To understand user expectations of working with LHRDs we prototyped with potential users how an LHRD work environment could be designed focusing on the physical screen alignment and the placement of content on the display. Based on previous work, we implemented novel alignment techniques for window management on LHRDs and compared them in a user study. The results show that users prefer techniques, that enhance the interaction without breaking well-known desktop GUI concepts. Finally, we provided the example of how an application for browsing scientific publications can benefit from extended display space. Overall, we show that GUIs for LHRDs should support the user more strongly than GUIs for smaller displays to arrange content meaningful or manage and understand large data sets, without breaking well-known GUI-metaphors. In conclusion, this thesis adopts a holistic approach to interaction with LHRDs in office environments. Based on enhanced knowledge about user perception of large visual spaces, we discuss novel input techniques for advanced user input on LHRDs. Furthermore, we present guidelines for designing future GUIs for LHRDs. Our work creates the design space of LHRD workplaces and identifies challenges and opportunities for the development of future office environments.Item Open Access Partnerübergreifende Geschäftsprozesse und ihre Realisierung in BPEL(2016) Kopp, Oliver; Leymann, Frank (Prof. Dr. Dr. h. c.)Diese Arbeit beschäftigt sich mit Geschäftsprozessen, die die Grenzen von Organisationen überspannen. Solche Geschäftsprozesse werden Choreographien genannt. In der Arbeit wird die CREAM-Methode vorgestellt, die zeigt, wie Choreographien modelliert werden können. Im Gegensatz zu Choreographien bezeichnen Orchestrierungen ausführbare Geschäftsprozesse einer einzelnen Organisation, die Dienste nutzen, um ein Geschäftsziel zu erreichen. Eine Variante der CREAM-Methode erlaubt, von einer Orchestrierung durch Aufteilung der Orchestrierung eine Choreographie zu erhalten. Um hierbei die impliziten orchestrierungsinternen Datenabhängigkeiten in Nachrichtenaustausche zu transformieren, wird der explizite Datenfluss der Orchestrierung benötigt. Die Web Services Business Process Execution Language (BPEL) ist eine verbreitete Sprache zur Modellierung von Geschäftsprozessen. In ihr wird der Datenfluss implizit modelliert und somit wird ein Verfahren benötigt, das den expliziten Datenfluss bestimmt. In dieser Arbeit wird ein solches Verfahren vorgestellt. Um eine Choreographie zu modellieren, wird eine Choreographiesprache benötigt. Zur Identifikation einer geeigneten Sprache werden in dieser Arbeit Kriterien zur Evaluation von Choreographiesprachen vorgestellt und damit Choreographiesprachen im Web-Service-Umfeld bewertet. Da keine der betrachteten Sprachen alle Kriterien erfüllt, wird die Sprache BPEL4Chor vorgestellt, die alle Kriterien erfüllt. Um die wohldefinierte Ausführungssemantik von BPEL wiederzuverwenden, verwendet BPEL4Chor die Sprache BPEL als Beschreibungssprache des Verhaltens jedes Teilnehmers in der Choreographie. BPEL4Chor verwendet analog zu BPEL XML als Serialisierungsformat und spezifiziert keine eigene graphische Repräsentation. Die Business Process Modeling Notation (BPMN) ist der de-facto Standard, um Geschäftsprozesse graphisch darzustellen. Deshalb wird in dieser Arbeit BPMN so erweitert, dass alle in BPEL4Chor verfügbaren Konstrukte mittels BPMN modelliert werden können.Item Open Access Task-oriented specialization techniques for entity retrieval(2020) Glaser, Andrea; Kuhn, Jonas (Prof. Dr.)Finding information on the internet has become very important nowadays, and online encyclopedias or websites specialized in certain topics offer users a great amount of information. Search engines support users when trying to find information. However, the vast amount of information makes it difficult to separate relevant from irrelevant facts for a specific information need. In this thesis we explore two areas of natural language processing in the context of retrieving information about entities: named entity disambiguation and sentiment analysis. The goal of this thesis is to use methods from these areas to develop task-oriented specialization techniques for entity retrieval. Named entity disambiguation is concerned with linking referring expressions (e.g., proper names) in text to their corresponding real world or fictional entity. Identifying the correct entity is an important factor in finding information on the internet as many proper names are ambiguous and need to be disambiguated to find relevant information. To that end, we introduce the notion of r-context, a new type of structurally informed context. This r-context consists of sentences that are relevant to the entity only to capture all important context clues and to avoid noise. We then show the usefulness of this r-context by performing a systematic study on a pseudo-ambiguity dataset. Identifying less known named entities is a challenge in named entity disambiguation because usually there is not much data available from which a machine learning algorithm can learn. We propose an approach that uses an aggregate of textual data about other entities which share certain properties with the target entity, and learn information from it by using topic modelling, which is then used to disambiguate the less known target entity. We use a dataset that is created automatically by exploiting the link structure in Wikipedia, and show that our approach is helpful for disambiguating entities without training material and with little surrounding context. Retrieving the relevant entities and information can produce many search results. Thus, it is important to effectively present the information to a user. We regard this step beyond the entity retrieval and employ sentiment analysis, which is used to analyze opinions expressed in text, in the context of effectively displaying information about product reviews to a user. We present a system that extracts a supporting sentence, a single sentence that captures both the sentiment of the author as well as a supportingfact. This supporting sentence can be used to provide users with an easy way to assess information in order to make informed choices quickly. We evaluate our approach by using the crowdsourcing service Amazon Mechanical Turk.Item Open Access Visualization challenges in distributed heterogeneous computing environments(2015) Panagiotidis, Alexandros; Ertl, Thomas (Prof. Dr.)Large-scale computing environments are important for many aspects of modern life. They drive scientific research in biology and physics, facilitate industrial rapid prototyping, and provide information relevant to everyday life such as weather forecasts. Their computational power grows steadily to provide faster response times and to satisfy the demand for higher complexity in simulation models as well as more details and higher resolutions in visualizations. For some years now, the prevailing trend for these large systems is the utilization of additional processors, like graphics processing units. These heterogeneous systems, that employ more than one kind of processor, are becoming increasingly widespread since they provide many benefits, like higher performance or increased energy efficiency. At the same time, they are more challenging and complex to use because the various processing units differ in their architecture and programming model. This heterogeneity is often addressed by abstraction but existing approaches often entail restrictions or are not universally applicable. As these systems also grow in size and complexity, they become more prone to errors and failures. Therefore, developers and users become more interested in resilience besides traditional aspects, like performance and usability. While fault tolerance is well researched in general, it is mostly dismissed in distributed visualization or not adapted to its special requirements. Finally, analysis and tuning of these systems and their software is required to assess their status and to improve their performance. The available tools and methods to capture and evaluate the necessary information are often isolated from the context or not designed for interactive use cases. These problems are amplified in heterogeneous computing environments, since more data is available and required for the analysis. Additionally, real-time feedback is required in distributed visualization to correlate user interactions to performance characteristics and to decide on the validity and correctness of the data and its visualization. This thesis presents contributions to all of these aspects. Two approaches to abstraction are explored for general purpose computing on graphics processing units and visualization in heterogeneous computing environments. The first approach hides details of different processing units and allows using them in a unified manner. The second approach employs per-pixel linked lists as a generic framework for compositing and simplifying order-independent transparency for distributed visualization. Traditional methods for fault tolerance in high performance computing systems are discussed in the context of distributed visualization. On this basis, strategies for fault-tolerant distributed visualization are derived and organized in a taxonomy. Example implementations of these strategies, their trade-offs, and resulting implications are discussed. For analysis, local graph exploration and tuning of volume visualization are evaluated. Challenges in dense graphs like visual clutter, ambiguity, and inclusion of additional attributes are tackled in node-link diagrams using a lens metaphor as well as supplementary views. An exploratory approach for performance analysis and tuning of parallel volume visualization on a large, high-resolution display is evaluated. This thesis takes a broader look at the issues of distributed visualization on large displays and heterogeneous computing environments for the first time. While the presented approaches all solve individual challenges and are successfully employed in this context, their joint utility form a solid basis for future research in this young field. In its entirety, this thesis presents building blocks for robust distributed visualization on current and future heterogeneous visualization environments.Item Open Access German clause-embedding predicates : an extraction and classification approach(2010) Lapshinova-Koltunski, Ekaterina; Heid, Ulrich (Prof. Dr. phil. habil.)This thesis describes a semi-automatic approach to the analysis of subcategorisation properties of verbal, nominal and multiword predicates in German. We semi-automatically classify predicates according to their subcategorisation properties by means of extracting them from German corpora along with their complements. In this work, we concentrate exclusively on sentential complements, such as dass, ob and w-clauses, although our methods can be also applied for other complement types. Our aim is not only to extract and classify predicates but also to compare subcategorisation properties of morphologically related predicates, such as verbs and their nominalisations. It is usually assumed that subcategorisation properties of nominalisations are taken over from their underlying verbs. However, our tests show that there exist different types of relations between them. Thus, we review subcategorisation properties of morphologically related words and analyse their correspondences and differences. For this purpose, we elaborate a set of semi-automatic procedures, which allow us not only to classify extracted units according to their subcategorisation properties, but also to compare the properties of verbs and their nominalisations, which occur both freely in corpora and within a multiword expression. The lexical data are created to serve symbolic NLP, especially large symbolic grammars for deep processing, such as HPSG or LFG, cf. work in the LinGO project (Copestake et al. 2004) and the Pargram project (Butt et al. 2002). HPSG and LFG need detailed linguistic knowledge. Besides that, subcategorisation iformation can be applied in applications for IE, cf. (Surdeanu et al. 2003). Moreover, this information is necessary for linguistic, lexicographic, SLA and translation work. Our extraction and classification procedures are precision-oriented, which means that we focus on high accuracy of our extraction and classification results. High precision is opposed to completeness, which is compensated by the application of extraction procedures on larger corpora.Item Open Access The perfect time span : on the present perfect in German, Swedish and English(2006) Rothstein, Björn Michael; Kamp, Hans (Prof. Dr. h.c. PhD)This study proposes a discourse based approach to the present perfect in German, Swedish and English. It is argued that the present perfect is best analysed by applying an ExtendedNow-approach. It introduces a perfect time span in which the event time expressed by the present perfect is contained. The present perfects in these languages differ with respect to the boundaries of perfect time span. In English, the right boundary is identical to the point of speech, in Swedish it can be either at or after the moment of speech and in German it can also be before the moment of speech. The left boundary is unspecified. The right boundary is set by context.Item Open Access Segmental factors in language proficiency : degree of velarization, coarticulatory resistance and vowel formant frequency distribution as a signature of talent(2011) Baumotte, Henrike; Dogil, Grzegorz (Prof. Dr.)The present PhD proposes a reason for German native speakers of various proficiency levels and multiple English varieties producing their L2 English with different degrees of a foreign accent. The author took into account phonetic measurements to investigate the degree of velarization and coarticulation or coarticulatory resistance respectively in German and English, taking non-words and natural language stimuli. To get an impression of the differences between the productions of proficient, average and less proficient speakers in German and English, the mean F2 and Fv values in /ə/ before /l/ and in /l/ were calculated, for then comparing the degree of velarization in /əlV/ non-word sequences with each other. Proficient speakers gained lower formant frequencies for F2 and Fv in /ə/ than less proficient speakers, i.e. proficient speakers velarized more than less proficient speakers. Within the comparisons with respect to coarticulation or coarticulatory resistance results respectively the difference values for F2 and F2' out of /ə/ in /əleɪ/ vs. /əlu:/, /əly/ vs. /əleɪ/ and /əly/ vs. /əlaɪ/ were created. In the whole series of measurements, an overwhelming trend for proficient speakers being more coarticulatory resistant, i.e. velarizing more, and more precisely pronouncing English vowel characteristics than less proficient speakers was present, while average speakers did not continuously behave according to prediction, as a result of being sometimes “worse” than less proficient speakers. On the basis of Díaz et al. (2008) who pled for pre-existing individual differences in phonetic discrimination ability which enormously influence the achievement of a foreign sound system, it is claimed for a derivation of foreign language from native phonetic abilities.Item Open Access Elastic parallel systems for high performance cloud computing(2020) Kehrer, Stefan; Blochinger, Wolfgang (Prof. Dr.)High Performance Computing (HPC) enables significant progress in both science and industry. Whereas traditionally parallel applications have been developed to address the grand challenges in science, as of today, they are also heavily used to speed up the time-to-result in the context of product design, production planning, financial risk management, medical diagnosis, as well as research and development efforts. However, purchasing and operating HPC clusters to run these applications requires huge capital expenditures as well as operational knowledge and thus is reserved to large organizations that benefit from economies of scale. More recently, the cloud evolved into an alternative execution environment for parallel applications, which comes with novel characteristics such as on-demand access to compute resources, pay-per-use, and elasticity. Whereas the cloud has been mainly used to operate interactive multi-tier applications, HPC users are also interested in the benefits offered. These include full control of the resource configuration based on virtualization, fast setup times by using on-demand accessible compute resources, and eliminated upfront capital expenditures due to the pay-per-use billing model. Additionally, elasticity allows compute resources to be provisioned and decommissioned at runtime, which allows fine-grained control of an application's performance in terms of its execution time and efficiency as well as the related monetary costs of the computation. Whereas HPC-optimized cloud environments have been introduced by cloud providers such as Amazon Web Services (AWS) and Microsoft Azure, existing parallel architectures are not designed to make use of elasticity. This thesis addresses several challenges in the emergent field of High Performance Cloud Computing. In particular, the presented contributions focus on the novel opportunities and challenges related to elasticity. First, the principles of elastic parallel systems as well as related design considerations are discussed in detail. On this basis, two exemplary elastic parallel system architectures are presented, each of which includes (1) an elasticity controller that controls the number of processing units based on user-defined goals, (2) a cloud-aware parallel execution model that handles coordination and synchronization requirements in an automated manner, and (3) a programming abstraction to ease the implementation of elastic parallel applications. To automate application delivery and deployment, novel approaches are presented that generate the required deployment artifacts from developer-provided source code in an automated manner while considering application-specific non-functional requirements. Throughout this thesis, a broad spectrum of design decisions related to the construction of elastic parallel system architectures is discussed, including proactive and reactive elasticity control mechanisms as well as cloud-based parallel processing with virtual machines (Infrastructure as a Service) and functions (Function as a Service). To evaluate these contributions, extensive experimental evaluations are presented.Item Open Access Efficient fault tolerance for selected scientific computing algorithms on heterogeneous and approximate computer architectures(2018) Schöll, Alexander; Wunderlich, Hans-Joachim (Prof. Dr.)Scientific computing and simulation technology play an essential role to solve central challenges in science and engineering. The high computational power of heterogeneous computer architectures allows to accelerate applications in these domains, which are often dominated by compute-intensive mathematical tasks. Scientific, economic and political decision processes increasingly rely on such applications and therefore induce a strong demand to compute correct and trustworthy results. However, the continued semiconductor technology scaling increasingly imposes serious threats to the reliability and efficiency of upcoming devices. Different reliability threats can cause crashes or erroneous results without indication. Software-based fault tolerance techniques can protect algorithmic tasks by adding appropriate operations to detect and correct errors at runtime. Major challenges are induced by the runtime overhead of such operations and by rounding errors in floating-point arithmetic that can cause false positives. The end of Dennard scaling induces central challenges to further increase the compute efficiency between semiconductor technology generations. Approximate computing exploits the inherent error resilience of different applications to achieve efficiency gains with respect to, for instance, power, energy, and execution times. However, scientific applications often induce strict accuracy requirements which require careful utilization of approximation techniques. This thesis provides fault tolerance and approximate computing methods that enable the reliable and efficient execution of linear algebra operations and Conjugate Gradient solvers using heterogeneous and approximate computer architectures. The presented fault tolerance techniques detect and correct errors at runtime with low runtime overhead and high error coverage. At the same time, these fault tolerance techniques are exploited to enable the execution of the Conjugate Gradient solvers on approximate hardware by monitoring the underlying error resilience while adjusting the approximation error accordingly. Besides, parameter evaluation and estimation methods are presented that determine the computational efficiency of application executions on approximate hardware. An extensive experimental evaluation shows the efficiency and efficacy of the presented methods with respect to the runtime overhead to detect and correct errors, the error coverage as well as the achieved energy reduction in executing the Conjugate Gradient solvers on approximate hardware.