Universität Stuttgart
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Item Open Access Goal-driven context-sensitive production processes : a case study using BPMN(2016) Kar, DebasisThe Fourth Industrial Revolution, also known as Industry 4.0 or Industrial Internet, predicts that Smart Factories driven by Internet of Things (IoT) and Cyber-Physical Systems, will reinvent the traditional manufacturing industry into a digitalized, a context-aware, and an automated manufacturing that will flourish with contemporary Information and Communication Technology (ICT). As the IoT are being deployed across production cites of the manufacturing companies, the need of decision making inside a business process based upon the received contextual data such as employee availability, machine status, etc. from the execution environment has transpired. Production processes need to be updated and optimized frequently to stay competitive in the market. Context-sensitive Adaptive Production Processes is an adept concept that illustrates how a business process can be context-sensitive keeping itself aligned with the abstract organizational goals. The notion of Context-sensitive Adaptive Production Processes leads us to Context-sensitive Execution Step (CES), a logical construct, that encompasses multiple alternative processes, albeit the best-fitting alternative can only be selected, optimized, and executed in runtime. Realization of the context-sensitive business processes requires a model-driven approach. Being Business Process Model and Notation (BPMN) the de-facto standard for business processes modeling, business experts of manufacturing companies can use custom CES construct of BPMN to model and execute context-sensitive business processes in a model-driven approach. This case study is based upon a scenario where there exists multiple alternatives to achieve the same goal in production, nevertheless all the alternatives are not suitable at a certain point of time as changes in business objectives and execution environment makes adaption tougher. Properties of intelligent production processes are different from traditional processes. Such properties along with the scrutinized properties of standard BPMN facilitates modeling CES integrated processes in BPMN. From the requirements inferred from these properties, standard BPMN is extended with extensions such that context-sensitive business processes can be modeled and executed seamlessly. Developed extensions include a new type of process construct and a new type of process definition that are technology agnostic. Thus, CES approach provides a comprehensive solution that makes production processes contextsensitive as well as goal-driven in unison.Item Open Access Feature based volumetric terrain generation(2016) Becher, MichaelTwo-dimensional heightfields are the most common data structure used for storing and rendering of terrain in offline rendering and especially real-time computer graphics. By its very nature, a 2D heightfield cannot store terrain structures with multiple vertical layers such as overhangs and caves. This restriction is lifted if a volumetric data structure is chosen in place of a 2D heightfield. However, the workflow of manual modelling and editing of volumetric terrain usually involves a large number of minor edits and adjustments and is very time consuming. Therefore, I propose to use three-dimensional curve-based primitives to efficiently model prominent, large scale terrain features and present techniques for volumetric generation of a complete terrain surface from the sparse input data by means of diffusion-based algorithms. By combining an efficient, feature-based toolset with a volumetric terrain representation, the modelling workflow is accelerated and simplified while offering the full artistic freedom of volumetric terrain.Item Open Access The GRACE event calendar(2012) Vishwakarma, Bramha DuttGRACE mission is a joint venture of NASA and GFZ. This mission was launched to provide with unprecedented accuracy, estimates of the global high resolution models of the Earth’s gravity field. The study of time-variability of Earth’s gravity field is very helpful in climate sciences and earth’s sciences studies. People have done a lot of work to demonstrate the effect of many natural phenomenon on gravity. Gravity estimates from GRACE are used for estimating mass redistribution at continental scale. So, we can observe hydrology, seismology and glaciology potential areas where GRACE can be useful. This research work focuses on identifying the hydrological events such as floods and drought, seismic events such as earthquakes and volcanic activity and also the glacier melting in the GRACE time-series. The work includes the development of strategy for the analysis of these events keeping in mind their behaviour and GRACE limitations of spatial resolution and sensitivity. Further in this work we would produce a event calendar for such events stating whether gravity changes caused by such events are visible to GRACE. Calendars are generated for hydrological events, floods and droughts separately and also for earthquake events. For rest of the phenomenon we have not generated calendars since these events are very few in numbers. This work is a qualitative analysis, so we could observe whether GRACE signal is able to observe these events or not. Hydrological events are observed by searching outliers in the grace observed time-series. The large floods such as 2009 Amazon floods can be seen when we take whole catchment, but the small floods affecting smaller region such as Sao Paulo flood is not visible in catchment time-series, so we have to go for selected area time-series generation. The factors such as time period for floods and droughts are very important factors when we want to observe them by GRACE. Earthquakes visibility depends on range rate amplitude, and also the quality of ΔC20, we have discussed these aspects while analysing earthquakes occurred in last decade from GRACE. We have given the possible explanation for the events not visible, and those visible have helped in the development of a methodology for analysis of a particular event. The volcanic activity in Caldera and Bolivia are pushing earth upward so we can expect some signal, but the spatial extent of these areas is small with caldera area greater than that of Bolivia, only caldera showed a trend. We also did trend analysis for 2 Asian glaciers and a part of Greenland for observing the melting of these ice masses. The work finally produces a series of events which we were able to observe by GRACE and we also get the methodology suitable for analysis of an event.Item Open Access Online visualization of German power plants and their production(2017) Ullah, Kazi RiazMaps are used for centuries to visualize geographical or topological information and nowadays, with modern technology, we can create interactive maps that allow us to display and access additional information. Some of them have even become part of our daily life, such as, almost real-time traffic information. Furthermore, maps are often used to display data of population densities, temperatures and spatial distribution of geographical phenomenon. Fraunhofer Institute of Solar Energy ISE decided to build an interactive map that shows the locations of all power plants listed on the European Energy Exchange (EEX). Since July 2014, the Fraunhofer ISE has been providing interactive charts on electricity production and other related information about electricity and power generation in Germany. These charts became very popular and widely used by people from different professions, namely scientists, politicians, journalists as well as online/printed media. Due to the high popularity of these interactive energy charts, an interactive map has been added to the Energy Charts data visualization portal to make the framework more informative and interesting for users. The map has several search options and levels of detail for searching different power plant locations, technical data, and connectivity to the high voltage transmission lines. Furthermore, this new visualization framework is interconnected with the existing energy charts. The dynamic linking, brushing and filtering technique in both map and energy charts have enhanced the framework by an additional layer providing more visibility and information on the selected power plants.Item Open Access Analysing and improving the crypto ecosystem of Rust(2017) Keck, PhilippContext: Rust is an emerging systems programming language that suits security-critical applications because it guarantees memory safety without a garbage collector. Its growing ecosystem already encompasses several crypto libraries, though the competition is still open. Previous cryptography research found that vulnerabilities are often due to misunderstandings and misuse of cryptographic APIs rather than bugs in the libraries themselves. Aim: This thesis presents a holistic analysis of Rust's current crypto ecosystem and aims to improve its further development. A particular focus is on API design because all libraries are still open to change their APIs and it will become increasingly difficult to change them later. Method: All parts of the ecosystem are systematically analysed, guided by the general structure of a crypto ecosystem. Research methods include a systematic search for libraries, a survey among contributors, GitHub analyses as well as a self-experiment and a controlled experiment to test the usability. Results: The contributors are typical open source developers and they collaborate in typical ways on GitHub. Most libraries have a clear main developer and there is a general lack of contributors. While two of the major libraries focus on usability and are consequently easier to use and more resistant to misuse, the two most widespread libraries consciously neglect these topics and exhibit flaws known from crypto libraries in other languages. Conclusion: The misuse resistant Rust crypto libraries should be advertised more actively. In the medium term, an officially endorsed API could improve interoperability and foster competition. For such an API and for the improvement of existing APIs, the thesis discusses a number of design decisions and their usability implications.Item Open Access Addressing TCAM limitations in an SDN-based pub/sub system(2017) Balogh, AlexanderContent-based publish/subscribe is a popular paradigm that enables asynchronous exchange of events between decoupled applications that is practiced in a wide range of domains. Hence, extensive research has been conducted in the area of efficient large-scale pub/sub system. A more recent development are content-based pub/sub systems that utilize software-defined networking (SDN) in order to implement event-filtering in the network layer. By installing content-filters in the ternary content-addressable memory (TCAM) of switches, these systems are able to achieve event filtering and forwarding at line-rate performance. While offering great performance, TCAM is also expensive, power hunger and limited in size. However, current SDN-based pub/sub systems don't address these limitations, thus using TCAM excessively. Therefore, this thesis provides techniques for constraining TCAM usage in such systems. The proposed methods enforce concrete flow limits without dropping any events by selectively merging content-filters into more coarse granular filters. The proposed algorithms leverage information about filter properties, traffic statistics, event distribution and global filter state in order to minimize the increase of unnecessary traffic introduced through merges. The proposed approach is twofold. A local enforcement algorithm ensures that the flow limit of a particular switch is never violated. This local approach is complemented by a periodically executed global optimization algorithm that tries to find a flow configuration on all switches, which minimized to increase in unnecessary traffic, given the current set of advertisements and subscriptions. For both classes, two algorithms with different properties are outlined. The proposed algorithms are integrated into the PLEROMA middleware and evaluated thoroughly in a real SDN testbed as well as in a large-scale network emulation. The evaluations demonstrate the effectiveness of the approaches under diverse and realistic workloads. In some cases, reducing the number of flows by more than 70% while increasing the false positive rate by less than 1% is possible.Item Open Access Memory-efficient lossless video compression using temporal extended JPEG-LS and on-line compression(2011) Chanda, DebasishUse of temporal predictors in lossless video coders play a significant role in terms of compression gain, but comes with a cost of significant memory requirement since this approach requires to save at least one frame in buffer for residue calculation. An improvement to standard JPEG-LS based lossless video coding algorithm is proposed in this work which requires very small amount of memory comparing to the regular approach keeping the computational complexity low. To obtain a higher compression, a combination of spatial and temporal predictor model has been used where appropriate mode is selected adaptively on a pixel based analysis. Using only one reference frame, the context based temporal coder performs its calculation regarding mode selection and prediction error calculation with already reconstructed pixels. This method eliminates the overhead of transmitting the coding mode in the decoder side. The need for storage space to save the only reference frame is further reduced by introducing on-line lossy compression on that frame. Relevant pixels from the stored reference frame are obtained by partial on-the-fly decompression. The combination of temporally extended context based prediction and on-line compression achieves a significant gain in compression ratio comparing to standard frame-by-frame JPEG-LS video coding keeping the memory requirement low, making it usable as a lightweight lossless video coder for embedded systems.Item Open Access Hybrid parallel computing beyond MPI & OpenMP - introducing PGAS & StarSs(2011) Sethi, Muhammad WahajHigh-performance architectures are becoming more and more complex with the passage of time. These large scale, heterogeneous architectures and multi-core system are difficult to program. New programming models are required to make expression of parallelism easier, while keeping productivity of the developer higher. Partition Global Address-space (PGAS) languages such as UPC appeared to augment developer’s productivity for distributed memory systems. UPC provides a simpler, shared memory-like model with a user control over data layout. But it is developer’s responsibility to take care of the data locality, by using appropriate data layouts. SMPSs/StarSs programming model tries to simplify the parallel programming on multicore architectures. It offers task level parallelism, where dependencies among the tasks are determined at the run time. In addition, runtime take cares of the data locality, while scheduling tasks. Hence, providing two-folds improvement in productivity; first, saving developer’s time by using automatic dependency detection, instead of hard coding them. Second, save cache optimization time, as runtime take cares of data locality. The purpose of this thesis is to use the PGAS programming model e.g. UPC for different nodes with the shared memory task based parallelization model i.e. StarSs to take the advantage of the multi core systems and contrast this approach to the legacy MPI and OpenMP combination. Performance as well as programmability is considered in the evaluation. The combination UPC + SMPSs, results in approximately the same execution time as MPI and OpenMP. The current lack of features such as multi-dimensional data distribution or virtual topologies in UPC, make the hybrid UPC + SMPSs/StarSs programming model less programmable than MPI + OpenMP for the application studied in this thesis.Item Open Access Optimizing the efficiency of data-intensive Data Mashups using Map-Reduce(2017) Sarangi, SunayanaIn order to derive knowledge and information from data through data processing, data integration and data analysis, a variety of Data Mashup tools have been developed in the past. Data Mashups are pipelines that process and integrate data based on different interconnected operators that realize data operations such as filter, join, extraction, alteration or integration. The overall goal is to integrate data from different sources into a single one. Most of these Mashup tools offer a grahical modeling platform, enabling the users to model the data sources, data operations and the data flow, thus, creating a so called Mashup Plan. This enables non-IT experts to perform data operations without having to deal with their technical details. Further, by allowing easy re-modeling and re-execution of the Mashup Plan, it also allows an iterative and explorative trial-an-error integration to enable real time insights into the data. These existing Data Mashup tools are efficient in executing small size data sets, however, they do not emphasize on the run-time efficiency of the data operations. This work is motivated by the limitations of current Data Mashup approaches with regard to data-intensive operations. The run-time of a data operation majorly varies depending on the size of the input data. Hence, in scenarios where one data operation expects inputs from multiple Data Mashup pipelines, which are executed in parallel, a data intensive operation in one of the Data Mashup pipelines leads to a bottleneck, thereby delaying the entire process. The efficiency of such scenarios can be greatly improved by executing the data-intensive operations in a distributed manner. This master thesis copes with this issue through an efficiency optimization of pipeline operators based on Map-Reduce. The Map-Reduce approach enables distributed processing of data to improve the run-time. Map-Reduce is divided into two main steps: (i) the Map step divides a data set into multiple smaller data sets, on which the data operations can be applied in parallel, and (ii) the Reduce step aggregates the results into one data set. The goal of this thesis is to enable a dynamic decision making while selecting suitable implementations for the data operations. This mechanism should be able to dynamically decide, which pipeline operators should be processed in a distributed manner, such as using a Map-Reduce implementation, and which operators should be processed by existing technologies, such as in-memory processing by Web Services. This decision is important because Map-Reduce itself can lead to a significant overhead while processing small data sets. Once it is decided that an operation should be processed using Map-Reduce, corresponding Map-Reduce jobs are invoked that process the data. This dynamic decision making can be achieved through WS-Policies. Web Services use policies to declare in a consistent and standardized manner what they are capable of supporting and which constraints and requirements they impose on their potential requestors. By comparing the capabilities of the Web Service with the requirements of the service requestor, it can be decided if the implementation is suitable for executing the data operation.Item Open Access Entwicklung von Algorithmen zur Planung der Wege von fahrerlosen Transportsystemen in einem Logistik-Warehouse(2017) Braunschweiger, DirkIn der Automobilindustrie ist in den letzten Jahren die Anforderungen an die Logistik-Warenhäuser gestiegen. Die steigende Individualisierung von Fahrzeugen ist der Grund dafür. Um die Anforderungen erfüllen zu können, werden in modernen Logistik-Warenhäusern die Waren durch fahrerlose Transportfahrzeuge transportiert. Es existieren viele Algorithmen zur Berechnung des kürzesten Weges für einzelne Fahrzeuge. Diese können in Warenhäusern mit vielen Fahrzeugen nicht eingesetzt werden, da es zu Staus, Deadlocks oder Kollisionen kommen kann. Es existieren bereits Algorithmen, die versuchen diese Probleme zu lösen. Wenige dieser Algorithmen wurden bisher auf die Praxistauglichkeit getestet. Die Algorithmen werden oft mit wenigen Fahrzeugen oder auf kleinen Straßennetzen getestet. Diese Arbeit stellt Algorithmen zur Berechnung von Wegen für mehrere Fahrzeuge vor und analysiert diese anschließend. Die Performanz der Algorithmen wird anhand realer Szenarien aus der Automobilindustrie gemessen. Dafür werden zuerst Straßennetze basierend auf echten Lagerhallen erstellt. Anschließend wird in verschiedenen Benchmarks die Performanz ausgewählter Algorithmen miteinander verglichen. Basierend auf den besten Algorithmen wird ein neuer Algorithmus entwickelt und mit bestehenden Algorithmen verglichen. Der neue Algorithmus benötigt weniger Rechenzeit und berechnet kürzere Wege. Die Ergebnisse werden abschließend mithilfe einer Simulations-Software validiert.