Refine
Year of publication
- 2015 (29) (remove)
Document Type
- Article (12)
- Monograph/Edited Volume (11)
- Doctoral Thesis (3)
- Conference Proceeding (2)
- Preprint (1)
Is part of the Bibliography
- yes (29)
Keywords
- BPMN (2)
- Cloud Computing (2)
- Forschungskolleg (2)
- Geschäftsprozessmanagement (2)
- Hasso Plattner Institute (2)
- Hasso-Plattner-Institut (2)
- JavaScript (2)
- Klausurtagung (2)
- Lively Kernel (2)
- Ph.D. retreat (2)
- Service-oriented Systems Engineering (2)
- service-oriented systems engineering (2)
- "Big Data"-Dienste (1)
- 3D information visualization (1)
- 3D semiotic model (1)
- Abstraktion (1)
- Algorithmen (1)
- Analyse (1)
- BPM (1)
- Batchprozesse (1)
- Behavioral querying (1)
- Biomedicine (1)
- Blockheizkraftwerke (1)
- Business process management (1)
- Business processes (1)
- CEP (1)
- Change Management (1)
- CoExist (1)
- Cyber-Physical Systems (1)
- Data (1)
- Data exchange (1)
- Data integration (1)
- Data modeling (1)
- Daten (1)
- Datenextraktion (1)
- Datenkorrektheit (1)
- Datenobjekte (1)
- Datenzustände (1)
- Deadline-Verbreitung (1)
- Design Thinking (1)
- Duration prediction (1)
- Dynamic pricing and advertising (1)
- Effizienz (1)
- Energiesparen (1)
- Ereignisabstraktion (1)
- Ereignisse (1)
- Event normalization (1)
- Event processing (1)
- Events (1)
- Evolution in MDE (1)
- Experimentation (1)
- Fallstudie (1)
- Feedback Loops (1)
- Feedback heuristics (1)
- Finite horizon (1)
- Forschungsprojekte (1)
- Future SOC Lab (1)
- Geschäftsprozesse (1)
- Graphdatenbanken (1)
- Graphtransformationen (1)
- Image filtering (1)
- In-Memory Technologie (1)
- Innovation (1)
- Innovationsmanagement (1)
- Innovationsmethode (1)
- Interaction (1)
- Inventory holding costs (1)
- Inventory systems (1)
- JIT compilers (1)
- Kollaborationen (1)
- Languages (1)
- Leadership (1)
- Level of abstraction (1)
- MDE Ansatz (1)
- MDE settings (1)
- Management (1)
- Measurement (1)
- Mehrfamilienhäuser (1)
- Modellgetrieben (1)
- Modellierung (1)
- Modelltransformation (1)
- Multi-Instanzen (1)
- Multicore Architekturen (1)
- Natural language processing (1)
- Network graph (1)
- Network monitoring (1)
- Network topology (1)
- Object Versioning (1)
- Objekt-Constraint Programmierung (1)
- Optimal stochastic and deterministic (1)
- Optimierungen (1)
- Organisationsveränderung (1)
- Performance (1)
- Process Mining (1)
- Process Monitoring (1)
- Process choreographies (1)
- Process model repositories (1)
- Process model search (1)
- Process modeling (1)
- Prognosen (1)
- Programming Environments (1)
- Prozess- und Datenintegration (1)
- Prozessarchitektur (1)
- Prozessautomatisierung (1)
- Prozessverfeinerung (1)
- Question answering (1)
- Racket (1)
- Research School (1)
- Risk control (1)
- SQL (1)
- Service detection (1)
- Skript-Entwicklungsumgebungen (1)
- Smalltalk (1)
- Sprachspezifikation (1)
- Squeak (1)
- Stochastic Petri nets (1)
- Studie (1)
- System of Systems (1)
- Texturing (1)
- Trace inclusion (1)
- Verifikation (1)
- Verwaltung von Rechenzentren (1)
- Verzögerungs-Verbreitung (1)
- Virtual 3D scenes (1)
- Visualisierung (1)
- Visualization (1)
- Wartung von Graphdatenbanksichten (1)
- Web browsers (1)
- Werkzeuge (1)
- abstraction (1)
- adaptive Systeme (1)
- adaptive systems (1)
- adoption (1)
- algorithms (1)
- analysis (1)
- ausführbare Semantiken (1)
- batch processing (1)
- big data services (1)
- bpm (1)
- business process architecture (1)
- business process management (1)
- business processes (1)
- cartographic design (1)
- case study (1)
- change management (1)
- cloud computing (1)
- cogeneration units (1)
- collaboration (1)
- conformance analysis (1)
- contracts (1)
- control (1)
- cyber-physical systems (1)
- data (1)
- data center management (1)
- data correctness checking (1)
- data extraction (1)
- data objects (1)
- data states (1)
- deadline propagation (1)
- delay propagation (1)
- design thinking (1)
- diffusion (1)
- efficiency (1)
- energy savings (1)
- event abstraction (1)
- events (1)
- evolution in MDE (1)
- executable semantics (1)
- feedback loops (1)
- forecasts (1)
- formal framework (1)
- formales Framework (1)
- formalism (1)
- functional languages (1)
- graph databases (1)
- graph transformation (1)
- incremental graph pattern matching (1)
- inductive invariant checking (1)
- induktives Invariant Checking (1)
- inkrementelles Graph Pattern Matching (1)
- innovation (1)
- innovation capabilities (1)
- innovation management (1)
- künstliche Intelligenz (1)
- language specification (1)
- leadership (1)
- lively kernel (1)
- location-based (1)
- management (1)
- maschinelles Lernen (1)
- model transformation (1)
- model-driven (1)
- model-driven engineering (1)
- modeling (1)
- modellgetriebene Entwicklung (1)
- monitoring (1)
- multi-instances (1)
- multi-family residential buildings (1)
- object-constraint programming (1)
- optimizations (1)
- organizational change (1)
- orts-basiert (1)
- partial application conditions (1)
- partielle Anwendungsbedingungen (1)
- process and data integration (1)
- process automation (1)
- process mining (1)
- process refinement (1)
- real-time rendering (1)
- research school (1)
- scripting environments (1)
- study (1)
- system of systems (1)
- tools (1)
- tracing (1)
- user interaction (1)
- verification (1)
- view maintenance (1)
- visualization (1)
- Übereinstimmungsanalyse (1)
- Überwachung (1)
Institute
- Hasso-Plattner-Institut für Digital Engineering gGmbH (29) (remove)
Texture mapping is a key technology in computer graphics. For the visual design of 3D scenes, in particular, effective texturing depends significantly on how important contents are expressed, e.g., by preserving global salient structures, and how their depiction is cognitively processed by the user in an application context. Edge-preserving image filtering is one key approach to address these concerns. Much research has focused on applying image filters in a post-process stage to generate artistically stylized depictions. However, these approaches generally do not preserve depth cues, which are important for the perception of 3D visualization (e.g., texture gradient). To this end, filtering is required that processes texture data coherently with respect to linear perspective and spatial relationships. In this work, we present an approach for texturing 3D scenes with perspective coherence by arbitrary image filters. We propose decoupled deferred texturing with (1) caching strategies to interactively perform image filtering prior to texture mapping and (2) for each mipmap level separately to enable a progressive level of abstraction, using (3) direct interaction interfaces to parameterize the visualization according to spatial, semantic, and thematic data. We demonstrate the potentials of our method by several applications using touch or natural language inputs to serve the different interests of users in specific information, including illustrative visualization, focus+context visualization, geometric detail removal, and semantic depth of field. The approach supports frame-to-frame coherence, order-independent transparency, multitexturing, and content-based filtering. In addition, it seamlessly integrates into real-time rendering pipelines and is extensible for custom interaction techniques. (C) 2015 Elsevier Ltd. All rights reserved.
Cartography-Oriented Design of 3D Geospatial Information Visualization - Overview and Techniques
(2015)
In economy, society and personal life map-based interactive geospatial visualization becomes a natural element of a growing number of applications and systems. The visualization of 3D geospatial information, however, raises the question how to represent the information in an effective way. Considerable research has been done in technology-driven directions in the fields of cartography and computer graphics (e.g., design principles, visualization techniques). Here, non-photorealistic rendering (NPR) represents a promising visualization category - situated between both fields - that offers a large number of degrees for the cartography-oriented visual design of complex 2D and 3D geospatial information for a given application context. Still today, however, specifications and techniques for mapping cartographic design principles to the state-of-the-art rendering pipeline of 3D computer graphics remain to be explored. This paper revisits cartographic design principles for 3D geospatial visualization and introduces an extended 3D semiotic model that complies with the general, interactive visualization pipeline. Based on this model, we propose NPR techniques to interactively synthesize cartographic renditions of basic feature types, such as terrain, water, and buildings. In particular, it includes a novel iconification concept to seamlessly interpolate between photorealistic and cartographic representations of 3D landmarks. Our work concludes with a discussion of open challenges in this field of research, including topics, such as user interaction and evaluation.
Business processes are vital to managing organizations as they sustain a company's competitiveness. Consequently, these organizations maintain collections of hundreds or thousands of process models for streamlining working procedures and facilitating process implementation. Yet, the management of large process model collections requires effective searching capabilities. Recent research focused on similarity search of process models, but querying process models is still a largely open topic. This article presents an approach to querying process models that takes a process example as input and discovers all models that allow replaying the behavior of the query. To this end, we provide a notion of behavioral inclusion that is based on trace semantics and abstraction. Additional to deciding a match, a closeness score is provided that describes how well the behavior of the query is represented in the model and can be used for ranking. The article introduces the formal foundations of the approach and shows how they are applied to querying large process model collections. An experimental evaluation has been conducted that confirms the suitability of the solution as well as its applicability and scalability in practice.
During the execution of business processes several events happen that are recorded in the company's information systems. These events deliver insights into process executions so that process monitoring and analysis can be performed resulting, for instance, in prediction of upcoming process steps or the analysis of the run time of single steps. While event capturing is trivial when a process engine with integrated logging capabilities is used, manual process execution environments do not provide automatic logging of events, so that typically external devices, like bar code scanners, have to be used. As experience shows, these manual steps are error-prone and induce additional work. Therefore, we use object state transitions as additional monitoring information, so-called object state transition events. Based on these object state transition events, we reason about the enablement and termination of activities and provide the basis for process monitoring and analysis in terms of a large event log. In this paper, we present the concept to utilize information from these object state transition events for capturing process progress. Furthermore, we discuss a methodology to create the required design time artifacts that then are used for monitoring at run time. In a proof-of-concept implementation, we show how the design time and run time side work and prove applicability of the introduced concept of object state transition events. (C) 2015 Elsevier B.V. All rights reserved.
We present Pycket, a high-performance tracing JIT compiler for Racket. Pycket supports a wide variety of the sophisticated features in Racket such as contracts, continuations, classes, structures, dynamic binding, and more. On average, over a standard suite of benchmarks, Pycket outperforms existing compilers, both Racket's JIT and other highly-optimizing Scheme compilers. Further, Pycket provides much better performance for Racket proxies than existing systems, dramatically reducing the overhead of contracts and gradual typing. We validate this claim with performance evaluation on multiple existing benchmark suites.
The Pycket implementation is of independent interest as an application of the RPython meta-tracing framework (originally created for PyPy), which automatically generates tracing JIT compilers from interpreters. Prior work on meta-tracing focuses on bytecode interpreters, whereas Pycket is a high-level interpreter based on the CEK abstract machine and operates directly on abstract syntax trees. Pycket supports proper tail calls and first-class continuations. In the setting of a functional language, where recursion and higher-order functions are more prevalent than explicit loops, the most significant performance challenge for a tracing JIT is identifying which control flows constitute a loop-we discuss two strategies for identifying loops and measure their impact.
Communication between organizations is formalized as process choreographies in daily business. While the correct ordering of exchanged messages can be modeled and enacted with current choreography techniques, no approach exists to describe and automate the exchange of data between processes in a choreography using messages. This paper describes an entirely model-driven approach for BPMN introducing a few concepts that suffice to model data retrieval, data transformation, message exchange, and correlation four aspects of data exchange. For automation, this work utilizes a recent concept to enact data dependencies in internal processes. We present a modeling guideline to derive local process models from a given choreography; their operational semantics allows to correctly enact the entire choreography from the derived models only including the exchange of data. Targeting on successful interactions, we discuss means to ensure correct process choreography modeling. Finally, we implemented our approach by extending the camunda BPM platform with our approach and show its feasibility by realizing all service interaction patterns using only model-based concepts. (C) 2015 Elsevier Ltd. All rights reserved.
We examine a special class of dynamic pricing and advertising models for the sale of perishable goods, including marginal unit costs and inventory holding costs. The time horizon is assumed to be finite and we allow several model parameters to be dependent on time. For the stochastic version of the model, we derive closed-form expressions of the value function as well as of the optimal pricing and advertising policy in feedback form. Moreover, we show that for small unit shares, the model converges to a deterministic version of the problem, whose explicit solution is characterized by an overage and an underage case. We quantify the close relationship between the open-loop solution of the deterministic model and the expected evolution of optimally controlled stochastic sales processes. For both models, we derive sensitivity results. We find that in the case of positive holding costs, on average, optimal prices increase in time and advertising rates decrease. Furthermore, we analytically verify the excellent quality of optimal feedback policies of deterministic models applied in stochastic models. (C) 2015 Elsevier B.V. All rights reserved.
Companies need to efficiently manage their business processes to deliver products and services in time. Therefore, they monitor the progress of individual cases to be able to timely detect undesired deviations and to react accordingly. For example, companies can decide to speed up process execution by raising alerts or by using additional resources, which increases the chance that a certain deadline or service level agreement can be met. Central to such process control is accurate prediction of the remaining time of a case and the estimation of the risk of missing a deadline.
To achieve this goal, we use a specific kind of stochastic Petri nets that can capture arbitrary duration distributions. Thereby, we are able to achieve higher prediction accuracy than related approaches. Further, we evaluate the approach in comparison to state of the art approaches and show the potential of exploiting a so far untapped source of information: the elapsed time since the last observed event. Real-world case studies in the financial and logistics domain serve to illustrate and evaluate the approach presented. (C) 2015 Elsevier Ltd. All rights reserved.
Business process management (BPM) is a systematic and structured approach to model, analyze, control, and execute business operations also referred to as business processes that get carried out to achieve business goals. Central to BPM are conceptual models. Most prominently, process models describe which tasks are to be executed by whom utilizing which information to reach a business goal. Process models generally cover the perspectives of control flow, resource, data flow, and information systems.
Execution of business processes leads to the work actually being carried out. Automating them increases the efficiency and is usually supported by process engines. This, though, requires the coverage of control flow, resource assignments, and process data. While the first two perspectives are well supported in current process engines, data handling needs to be implemented and maintained manually. However, model-driven data handling promises to ease implementation, reduces the error-proneness through graphical visualization, and reduces development efforts through code generation.
This thesis addresses the modeling, analysis, and execution of data in business processes and presents a novel approach to execute data-annotated process models entirely model-driven. As a first step and formal grounding for the process execution, a conceptual framework for the integration of processes and data is introduced. This framework is complemented by operational semantics through a Petri net mapping extended with data considerations. Model-driven data execution comprises the handling of complex data dependencies, process data, and data exchange in case of communication between multiple process participants. This thesis introduces concepts from the database domain into BPM to enable the distinction of data operations, to specify relations between data objects of the same as well as of different types, to correlate modeled data nodes as well as received messages to the correct run-time process instances, and to generate messages for inter-process communication. The underlying approach, which is not limited to a particular process description language, has been implemented as proof-of-concept.
Automation of data handling in business processes requires data-annotated and correct process models. Targeting the former, algorithms are introduced to extract information about data nodes, their states, and data dependencies from control information and to annotate the process model accordingly. Usually, not all required information can be extracted from control flow information, since some data manipulations are not specified. This requires further refinement of the process model. Given a set of object life cycles specifying allowed data manipulations, automated refinement of the process model towards containment of all data manipulations is enabled. Process models are an abstraction focusing on specific aspects in detail, e.g., the control flow and the data flow views are often represented through activity-centric and object-centric process models. This thesis introduces algorithms for roundtrip transformations enabling the stakeholder to add information to the process model in the view being most appropriate.
Targeting process model correctness, this thesis introduces the notion of weak conformance that checks for consistency between given object life cycles and the process model such that the process model may only utilize data manipulations specified directly or indirectly in an object life cycle. The notion is computed via soundness checking of a hybrid representation integrating control flow and data flow correctness checking. Making a process model executable, identified violations must be corrected. Therefore, an approach is proposed that identifies for each violation multiple, alternative changes to the process model or the object life cycles.
Utilizing the results of this thesis, business processes can be executed entirely model-driven from the data perspective in addition to the control flow and resource perspectives already supported before. Thereby, the model creation is supported by algorithms partly automating the creation process while model consistency is ensured by data correctness checks.
An increasing demand on functionality and flexibility leads to an integration of beforehand isolated system solutions building a so-called System of Systems (SoS). Furthermore, the overall SoS should be adaptive to react on changing requirements and environmental conditions. Due SoS are composed of different independent systems that may join or leave the overall SoS at arbitrary point in times, the SoS structure varies during the systems lifetime and the overall SoS behavior emerges from the capabilities of the contained subsystems. In such complex system ensembles new demands of understanding the interaction among subsystems, the coupling of shared system knowledge and the influence of local adaptation strategies to the overall resulting system behavior arise. In this report, we formulate research questions with the focus of modeling interactions between system parts inside a SoS. Furthermore, we define our notion of important system types and terms by retrieving the current state of the art from literature. Having a common understanding of SoS, we discuss a set of typical SoS characteristics and derive general requirements for a collaboration modeling language. Additionally, we retrieve a broad spectrum of real scenarios and frameworks from literature and discuss how these scenarios cope with different characteristics of SoS. Finally, we discuss the state of the art for existing modeling languages that cope with collaborations for different system types such as SoS.
Business Process Management has become an integral part of modern organizations in the private and public sector for improving their operations. In the course of Business Process Management efforts, companies and organizations assemble large process model repositories with many hundreds and thousands of business process models bearing a large amount of information. With the advent of large business process model collections, new challenges arise as structuring and managing a large amount of process models, their maintenance, and their quality assurance.
This is covered by business process architectures that have been introduced for organizing and structuring business process model collections. A variety of business process architecture approaches have been proposed that align business processes along aspects of interest, e. g., goals, functions, or objects. They provide a high level categorization of single processes ignoring their interdependencies, thus hiding valuable information. The production of goods or the delivery of services are often realized by a complex system of interdependent business processes. Hence, taking a holistic view at business processes interdependencies becomes a major necessity to organize, analyze, and assess the impact of their re-/design. Visualizing business processes interdependencies reveals hidden and implicit information from a process model collection.
In this thesis, we present a novel Business Process Architecture approach for representing and analyzing business process interdependencies on an abstract level. We propose a formal definition of our Business Process Architecture approach, design correctness criteria, and develop analysis techniques for assessing their quality. We describe a methodology for applying our Business Process Architecture approach top-down and bottom-up. This includes techniques for Business Process Architecture extraction from, and decomposition to process models while considering consistency issues between business process architecture and process model level. Using our extraction algorithm, we present a novel technique to identify and visualize data interdependencies in Business Process Data Architectures. Our Business Process Architecture approach provides business process experts,managers, and other users of a process model collection with an overview that allows reasoning about a large set of process models,
understanding, and analyzing their interdependencies in a facilitated way. In this regard we evaluated our Business Process Architecture approach in an experiment and provide implementations of selected techniques.
We report our experience in implementing SqueakJS, a bitcompatible implementation of Squeak/Smalltalk written in pure JavaScript. SqueakJS runs entirely in theWeb browser with a virtual file system that can be directed to a server or client-side storage. Our implementation is notable for simplicity and performance gained through adaptation to the host object memory and deployment leverage gained through the Lively Web development environment. We present several novel techniques as well as performance measurements for the resulting virtual machine. Much of this experience is potentially relevant to preserving other dynamic language systems and making them available in a browser-based environment.
We present object versioning as a generic approach to preserve access to previous development and application states. Version-aware references can manage the modifications made to the target object and record versions as desired. Such references can be provided without modifications to the virtual machine. We used proxies to implement the proposed concepts and demonstrate the Lively Kernel running on top of this object versioning layer. This enables Lively users to undo the effects of direct manipulation and other programming actions.
Biologists often pose queries to search engines and biological databases to obtain answers related to ongoing experiments. This is known to be a time consuming, and sometimes frustrating, task in which more than one query is posed and many databases are consulted to come to possible answers for a single fact. Question answering comes as an alternative to this process by allowing queries to be posed as questions, by integrating various resources of different nature and by returning an exact answer to the user. We have surveyed the current solutions on question answering for Biology, present an overview on the methods which are usually employed and give insights on how to boost performance of systems in this domain. (C) 2014 Elsevier Inc. All rights reserved.
Nowadays, business processes are increasingly supported by IT services that produce massive amounts of event data during process execution. Aiming at a better process understanding and improvement, this event data can be used to analyze processes using process mining techniques. Process models can be automatically discovered and the execution can be checked for conformance to specified behavior. Moreover, existing process models can be enhanced and annotated with valuable information, for example for performance analysis. While the maturity of process mining algorithms is increasing and more tools are entering the market, process mining projects still face the problem of different levels of abstraction when comparing events with modeled business activities. Mapping the recorded events to activities of a given process model is essential for conformance checking, annotation and understanding of process discovery results. Current approaches try to abstract from events in an automated way that does not capture the required domain knowledge to fit business activities. Such techniques can be a good way to quickly reduce complexity in process discovery. Yet, they fail to enable techniques like conformance checking or model annotation, and potentially create misleading process discovery results by not using the known business terminology.
In this thesis, we develop approaches that abstract an event log to the same level that is needed by the business. Typically, this abstraction level is defined by a given process model. Thus, the goal of this thesis is to match events from an event log to activities in a given process model. To accomplish this goal, behavioral and linguistic aspects of process models and event logs as well as domain knowledge captured in existing process documentation are taken into account to build semiautomatic matching approaches. The approaches establish a pre--processing for every available process mining technique that produces or annotates a process model, thereby reducing the manual effort for process analysts. While each of the presented approaches can be used in isolation, we also introduce a general framework for the integration of different matching approaches.
The approaches have been evaluated in case studies with industry and using a large industry process model collection and simulated event logs. The evaluation demonstrates the effectiveness and efficiency of the approaches and their robustness towards nonconforming execution logs.
ecoControl
(2015)
Eine dezentrale Energieversorgung ist ein erster Schritt in Richtung Energiewende. Dabei werden auch in Mehrfamilienhäusern vermehrt verschiedene Strom- und Wärmeerzeuger eingesetzt.
Besonders in Deutschland kommen in diesem Zusammenhang Blockheizkraftwerke immer häufiger zum Einsatz, weil sie Gas sehr effizient in Strom und Wärme umwandeln können. Außerdem ermöglichen sie, im Zusammenspiel mit anderen Energiesystemen wie beispielsweise Photovoltaik-Anlagen, eine kontinuierliche und dezentrale Energieversorgung.
Bei dem Betrieb von unterschiedlichen Energiesystemen ist es wünschenswert, dass die Systeme aufeinander abgestimmt arbeiten. Allerdings ist es bisher schwierig, heterogene Energiesysteme effizient miteinander zu betreiben. Dadurch bleiben Einsparungspotentiale ungenutzt.
Eine zentrale Steuerung kann deshalb die Effizienz des Gesamtsystems verbessern.
Mit ecoControl stellen wir einen erweiterbaren Prototypen vor, der die Kooperation von Energiesystemen optimiert und Umweltfaktoren miteinbezieht.
Dazu stellt die Software eine einheitliche Bedienungsoberfläche zur Konfiguration aller Systeme zur Verfügung. Außerdem bietet sie die Möglichkeit, Optimierungsalgorithmen mit Hilfe einer Programmierschnittstelle zu entwickeln, zu testen und auszuführen.
Innerhalb solcher Algorithmen können von ecoControl bereitgestellte Vorhersagen genutzt werden. Diese Vorhersagen basieren auf dem individuellen Verhalten von jedem Energiesystem, Wettervorhersagen und auf Prognosen des Energieverbrauchs. Mithilfe einer Simulation können Techniker unterschiedliche Konfigurationen und Optimierungen sofort ausprobieren, ohne diese über einen langen Zeitraum an realen Geräten testen zu müssen.
ecoControl hilft darüber hinaus auch Hausverwaltungen und Vermietern bei der Verwaltung und Analyse der Energiekosten.
Wir haben anhand von Fallbeispielen gezeigt, dass Optimierungsalgorithmen, welche die Nutzung von Wärmespeichern verbessern, die Effizienz des Gesamtsystems erheblich verbessern können.
Schließlich kommen wir zu dem Schluss, dass ecoControl in einem nächsten Schritt unter echten Bedingungen getestet werden muss, sobald eine geeignete Hardwarekomponente verfügbar ist. Über diese Schnittstelle werden die Messwerte an ecoControl gesendet und Steuersignale an die Geräte weitergeleitet.
Every year, the Hasso Plattner Institute (HPI) invites guests from industry and academia to a collaborative scientific workshop on the topic “Operating the Cloud”. Our goal is to provide a forum for the exchange of knowledge and experience between industry and academia. Hence, HPI’s Future SOC Lab is the adequate environment to host this event which is also supported by BITKOM.
On the occasion of this workshop we called for submissions of research papers and practitioners’ reports. “Operating the Cloud” aims to be a platform for productive discussions of innovative ideas, visions, and upcoming technologies in the field of cloud operation and administration.
In this workshop proceedings the results of the second HPI cloud symposium "Operating the Cloud" 2014 are published. We thank the authors for exciting presentations and insights into their current work and research. Moreover, we look forward to more interesting submissions for the upcoming symposium in 2015.
Graph databases provide a natural way of storing and querying graph data. In contrast to relational databases, queries over graph databases enable to refer directly to the graph structure of such graph data. For example, graph pattern matching can be employed to formulate queries over graph data.
However, as for relational databases running complex queries can be very time-consuming and ruin the interactivity with the database. One possible approach to deal with this performance issue is to employ database views that consist of pre-computed answers to common and often stated queries. But to ensure that database views yield consistent query results in comparison with the data from which they are derived, these database views must be updated before queries make use of these database views. Such a maintenance of database views must be performed efficiently, otherwise the effort to create and maintain views may not pay off in comparison to processing the queries directly on the data from which the database views are derived.
At the time of writing, graph databases do not support database views and are limited to graph indexes that index nodes and edges of the graph data for fast query evaluation, but do not enable to maintain pre-computed answers of complex queries over graph data. Moreover, the maintenance of database views in graph databases becomes even more challenging when negation and recursion have to be supported as in deductive relational databases.
In this technical report, we present an approach for the efficient and scalable incremental graph view maintenance for deductive graph databases. The main concept of our approach is a generalized discrimination network that enables to model nested graph conditions including negative application conditions and recursion, which specify the content of graph views derived from graph data stored by graph databases. The discrimination network enables to automatically derive generic maintenance rules using graph transformations for maintaining graph views in case the graph data from which the graph views are derived change. We evaluate our approach in terms of a case study using multiple data sets derived from open source projects.