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Institute
- Hasso-Plattner-Institut für Digital Engineering gGmbH (173) (remove)
Modern 3D geovisualization systems (3DGeoVSs) are complex and evolving systems that are required to be adaptable and leverage distributed resources, including massive geodata. This article focuses on 3DGeoVSs built based on the principles of service-oriented architectures, standards and image-based representations (SSI) to address practically relevant challenges and potentials. Such systems facilitate resource sharing and agile and efficient system construction and change in an interoperable manner, while exploiting images as efficient, decoupled and interoperable representations. The software architecture of a 3DGeoVS and its underlying visualization model have strong effects on the system's quality attributes and support various system life cycle activities. This article contributes a software reference architecture (SRA) for 3DGeoVSs based on SSI that can be used to design, describe and analyze concrete software architectures with the intended primary benefit of an increase in effectiveness and efficiency in such activities. The SRA integrates existing, proven technology and novel contributions in a unique manner. As the foundation for the SRA, we propose the generalized visualization pipeline model that generalizes and overcomes expressiveness limitations of the prevalent visualization pipeline model. To facilitate exploiting image-based representations (IReps), the SRA integrates approaches for the representation, provisioning and styling of and interaction with IReps. Five applications of the SRA provide proofs of concept for the general applicability and utility of the SRA. A qualitative evaluation indicates the overall suitability of the SRA, its applications and the general approach of building 3DGeoVSs based on SSI.
In today's world, many applications produce large amounts of data at an enormous rate. Analyzing such datasets for metadata is indispensable for effectively understanding, storing, querying, manipulating, and mining them. Metadata summarizes technical properties of a dataset which rang from basic statistics to complex structures describing data dependencies. One type of dependencies is inclusion dependency (IND), which expresses subset-relationships between attributes of datasets. Therefore, inclusion dependencies are important for many data management applications in terms of data integration, query optimization, schema redesign, or integrity checking. So, the discovery of inclusion dependencies in unknown or legacy datasets is at the core of any data profiling effort.
For exhaustively detecting all INDs in large datasets, we developed S-indd++, a new algorithm that eliminates the shortcomings of existing IND-detection algorithms and significantly outperforms them. S-indd++ is based on a novel concept for the attribute clustering for efficiently deriving INDs. Inferring INDs from our attribute clustering eliminates all redundant operations caused by other algorithms. S-indd++ is also based on a novel partitioning strategy that enables discording a large number of candidates in early phases of the discovering process. Moreover, S-indd++ does not require to fit a partition into the main memory--this is a highly appreciable property in the face of ever-growing datasets. S-indd++ reduces up to 50% of the runtime of the state-of-the-art approach.
None of the approach for discovering INDs is appropriate for the application on dynamic datasets; they can not update the INDs after an update of the dataset without reprocessing it entirely. To this end, we developed the first approach for incrementally updating INDs in frequently changing datasets. We achieved that by reducing the problem of incrementally updating INDs to the incrementally updating the attribute clustering from which all INDs are efficiently derivable. We realized the update of the clusters by designing new operations to be applied to the clusters after every data update. The incremental update of INDs reduces the time of the complete rediscovery by up to 99.999%.
All existing algorithms for discovering n-ary INDs are based on the principle of candidate generation--they generate candidates and test their validity in the given data instance. The major disadvantage of this technique is the exponentially growing number of database accesses in terms of SQL queries required for validation. We devised Mind2, the first approach for discovering n-ary INDs without candidate generation. Mind2 is based on a new mathematical framework developed in this thesis for computing the maximum INDs from which all other n-ary INDs are derivable. The experiments showed that Mind2 is significantly more scalable and effective than hypergraph-based algorithms.
Blockchain
(2018)
Der Begriff Blockchain ist in letzter Zeit zu einem Schlagwort geworden, aber nur wenige wissen, was sich genau dahinter verbirgt. Laut einer Umfrage, die im ersten Quartal 2017 veröffentlicht wurde, ist der Begriff nur bei 35 Prozent der deutschen Mittelständler bekannt. Dabei ist die Blockchain-Technologie durch ihre rasante Entwicklung und die globale Eroberung unterschiedlicher Märkte für Massenmedien sehr interessant.
So sehen viele die Blockchain-Technologie entweder als eine Allzweckwaffe, zu der aber nur wenige einen Zugang haben, oder als eine Hacker-Technologie für geheime Geschäfte im Darknet. Dabei liegt die Innovation der Blockchain-Technologie in ihrer erfolgreichen Zusammensetzung bereits vorhandener Ansätze: dezentrale Netzwerke, Kryptographie, Konsensfindungsmodelle. Durch das innovative Konzept wird ein Werte-Austausch in einem dezentralen System möglich. Dabei wird kein Vertrauen zwischen dessen Knoten (z.B. Nutzer) vorausgesetzt.
Mit dieser Studie möchte das Hasso-Plattner-Institut den Lesern helfen, ihren eigenen Standpunkt zur Blockchain-Technologie zu finden und dabei dazwischen unterscheiden zu können, welche Eigenschaften wirklich innovativ und welche nichts weiter als ein Hype sind.
Die Autoren der vorliegenden Arbeit analysieren positive und negative Eigenschaften, welche die Blockchain-Architektur prägen, und stellen mögliche Anpassungs- und Lösungsvorschläge vor, die zu einem effizienten Einsatz der Technologie beitragen können. Jedem Unternehmen, bevor es sich für diese Technologie entscheidet, wird dabei empfohlen, für den geplanten Anwendungszweck zunächst ein klares Ziel zu definieren, das mit einem angemessenen Kosten-Nutzen-Verhältnis angestrebt werden kann. Dabei sind sowohl die Möglichkeiten als auch die Grenzen der Blockchain-Technologie zu beachten. Die relevanten Schritte, die es in diesem Zusammenhang zu beachten gilt, fasst die Studie für die Leser übersichtlich zusammen.
Es wird ebenso auf akute Fragestellungen wie Skalierbarkeit der Blockchain, geeigneter Konsensalgorithmus und Sicherheit eingegangen, darunter verschiedene Arten möglicher Angriffe und die entsprechenden Gegenmaßnahmen zu deren Abwehr. Neue Blockchains etwa laufen Gefahr, geringere Sicherheit zu bieten, da Änderungen an der bereits bestehenden Technologie zu Schutzlücken und Mängeln führen können.
Nach Diskussion der innovativen Eigenschaften und Probleme der Blockchain-Technologie wird auf ihre Umsetzung eingegangen. Interessierten Unternehmen stehen viele Umsetzungsmöglichkeiten zur Verfügung. Die zahlreichen Anwendungen haben entweder eine eigene Blockchain als Grundlage oder nutzen bereits bestehende und weitverbreitete Blockchain-Systeme. Zahlreiche Konsortien und Projekte bieten „Blockchain-as-a-Service“ an und unterstützen andere Unternehmen beim Entwickeln, Testen und Bereitstellen von Anwendungen.
Die Studie gibt einen detaillierten Überblick über zahlreiche relevante Einsatzbereiche und Projekte im Bereich der Blockchain-Technologie. Dadurch, dass sie noch relativ jung ist und sich schnell entwickelt, fehlen ihr noch einheitliche Standards, die Zusammenarbeit der verschiedenen Systeme erlauben und an die sich alle Entwickler halten können. Aktuell orientieren sich Entwickler an Bitcoin-, Ethereum- und Hyperledger-Systeme, diese dienen als Grundlage für viele weitere Blockchain-Anwendungen.
Ziel ist, den Lesern einen klaren und umfassenden Überblick über die Blockchain-Technologie und deren Möglichkeiten zu vermitteln.
Nowadays, graph data models are employed, when relationships between entities have to be stored and are in the scope of queries. For each entity, this graph data model locally stores relationships to adjacent entities. Users employ graph queries to query and modify these entities and relationships. These graph queries employ graph patterns to lookup all subgraphs in the graph data that satisfy certain graph structures. These subgraphs are called graph pattern matches. However, this graph pattern matching is NP-complete for subgraph isomorphism. Thus, graph queries can suffer a long response time, when the number of entities and relationships in the graph data or the graph patterns increases.
One possibility to improve the graph query performance is to employ graph views that keep ready graph pattern matches for complex graph queries for later retrieval. However, these graph views must be maintained by means of an incremental graph pattern matching to keep them consistent with the graph data from which they are derived, when the graph data changes. This maintenance adds subgraphs that satisfy a graph pattern to the graph views and removes subgraphs that do not satisfy a graph pattern anymore from the graph views.
Current approaches for incremental graph pattern matching employ Rete networks. Rete networks are discrimination networks that enumerate and maintain all graph pattern matches of certain graph queries by employing a network of condition tests, which implement partial graph patterns that together constitute the overall graph query. Each condition test stores all subgraphs that satisfy the partial graph pattern. Thus, Rete networks suffer high memory consumptions, because they store a large number of partial graph pattern matches. But, especially these partial graph pattern matches enable Rete networks to update the stored graph pattern matches efficiently, because the network maintenance exploits the already stored partial graph pattern matches to find new graph pattern matches. However, other kinds of discrimination networks exist that can perform better in time and space than Rete networks. Currently, these other kinds of networks are not used for incremental graph pattern matching.
This thesis employs generalized discrimination networks for incremental graph pattern matching. These discrimination networks permit a generalized network structure of condition tests to enable users to steer the trade-off between memory consumption and execution time for the incremental graph pattern matching. For that purpose, this thesis contributes a modeling language for the effective definition of generalized discrimination networks. Furthermore, this thesis contributes an efficient and scalable incremental maintenance algorithm, which updates the (partial) graph pattern matches that are stored by each condition test. Moreover, this thesis provides a modeling evaluation, which shows that the proposed modeling language enables the effective modeling of generalized discrimination networks. Furthermore, this thesis provides a performance evaluation, which shows that a) the incremental maintenance algorithm scales, when the graph data becomes large, and b) the generalized discrimination network structures can outperform Rete network structures in time and space at the same time for incremental graph pattern matching.
Design and Implementation of service-oriented architectures imposes a huge number of research questions from the fields of software engineering, system analysis and modeling, adaptability, and application integration. Component orientation and web services are two approaches for design and realization of complex web-based system. Both approaches allow for dynamic application adaptation as well as integration of enterprise application.
Commonly used technologies, such as J2EE and .NET, form de facto standards for the realization of complex distributed systems. Evolution of component systems has lead to web services and service-based architectures. This has been manifested in a multitude of industry standards and initiatives such as XML, WSDL UDDI, SOAP, etc. All these achievements lead to a new and promising paradigm in IT systems engineering which proposes to design complex software solutions as collaboration of contractually defined software services.
Service-Oriented Systems Engineering represents a symbiosis of best practices in object-orientation, component-based development, distributed computing, and business process management. It provides integration of business and IT concerns.
The annual Ph.D. Retreat of the Research School provides each member the opportunity to present his/her current state of their research and to give an outline of a prospective Ph.D. thesis. Due to the interdisciplinary structure of the research school, this technical report covers a wide range of topics. These include but are not limited to: Human Computer Interaction and Computer Vision as Service; Service-oriented Geovisualization Systems; Algorithm Engineering for Service-oriented Systems; Modeling and Verification of Self-adaptive Service-oriented Systems; Tools and Methods for Software Engineering in Service-oriented Systems; Security Engineering of Service-based IT Systems; Service-oriented Information Systems; Evolutionary Transition of Enterprise Applications to Service Orientation; Operating System Abstractions for Service-oriented Computing; and Services Specification, Composition, and Enactment.
Today, software has become an intrinsic part of complex distributed embedded real-time systems. The next generation of embedded real-time systems will interconnect the today unconnected systems via complex software parts and the service-oriented paradigm. Therefore besides timed behavior and probabilistic behaviour also structure dynamics, where the architecture can be subject to changes at run-time, e.g. when dynamic binding of service end-points is employed or complex collaborations are established dynamically, is required. However, a modeling and analysis approach that combines all these necessary aspects does not exist so far.
To fill the identified gap, we propose Probabilistic Timed Graph Transformation Systems (PTGTSs) as a high-level description language that supports all the necessary aspects of structure dynamics, timed behavior, and probabilistic behavior. We introduce the formal model of PTGTSs in this paper and present a mapping of models with finite state spaces to probabilistic timed automata (PTA) that allows to use the PRISM model checker to analyze PTGTS models with respect to PTCTL properties.
Every year, the Hasso Plattner Institute (HPI) invites guests from industry and academia to a collaborative scientific workshop on the topic 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. Co-located with the event is the HPI's Future SOC Lab day, which offers an additional attractive and conducive environment for scientific and industry related discussions. "Operating the Cloud" aims to be a platform for productive interactions of innovative ideas, visions, and upcoming technologies in the field of cloud operation and administration.
On the occasion of this symposium we called for submissions of research papers and practitioner's reports. A compilation of the research papers realized during the fourth HPI cloud symposium "Operating the Cloud" 2016 are published in this proceedings. 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 later in the year. 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. Co-located with the event is the HPI's Future SOC Lab day, which offers an additional attractive and conducive environment for scientific and industry related discussions. "Operating the Cloud" aims to be a platform for productive interactions of innovative ideas, visions, and upcoming technologies in the field of cloud operation and administration.
While offering significant expressive power, graph transformation systems often come with rather limited capabilities for automated analysis, particularly if systems with many possible initial graphs and large or infinite state spaces are concerned. One approach that tries to overcome these limitations is inductive invariant checking. However, the verification of inductive invariants often requires extensive knowledge about the system in question and faces the approach-inherent challenges of locality and lack of context.
To address that, this report discusses k-inductive invariant checking for graph transformation systems as a generalization of inductive invariants. The additional context acquired by taking multiple (k) steps into account is the key difference to inductive invariant checking and is often enough to establish the desired invariants without requiring the iterative development of additional properties.
To analyze possibly infinite systems in a finite fashion, we introduce a symbolic encoding for transformation traces using a restricted form of nested application conditions. As its central contribution, this report then presents a formal approach and algorithm to verify graph constraints as k-inductive invariants. We prove the approach's correctness and demonstrate its applicability by means of several examples evaluated with a prototypical implementation of our algorithm.
Graphs are ubiquitous in Computer Science. For this reason, in many areas, it is very important to have the means to express and reason about graph properties. In particular, we want to be able to check automatically if a given graph property is satisfiable. Actually, in most application scenarios it is desirable to be able to explore graphs satisfying the graph property if they exist or even to get a complete and compact overview of the graphs satisfying the graph property.
We show that the tableau-based reasoning method for graph properties as introduced by Lambers and Orejas paves the way for a symbolic model generation algorithm for graph properties. Graph properties are formulated in a dedicated logic making use of graphs and graph morphisms, which is equivalent to firstorder logic on graphs as introduced by Courcelle. Our parallelizable algorithm gradually generates a finite set of so-called symbolic models, where each symbolic model describes a set of finite graphs (i.e., finite models) satisfying the graph property. The set of symbolic models jointly describes all finite models for the graph property (complete) and does not describe any finite graph violating the graph property (sound). Moreover, no symbolic model is already covered by another one (compact). Finally, the algorithm is able to generate from each symbolic model a minimal finite model immediately and allows for an exploration of further finite models. The algorithm is implemented in the new tool AutoGraph.