@article{PengLiuWangetal.2018, author = {Peng, Junjie and Liu, Danxu and Wang, Yingtao and Zeng, Ying and Cheng, Feng and Zhang, Wenqiang}, title = {Weight-based strategy for an I/O-intensive application at a cloud data center}, series = {Concurrency and computation : practice \& experience}, volume = {30}, journal = {Concurrency and computation : practice \& experience}, number = {19}, publisher = {Wiley}, address = {Hoboken}, issn = {1532-0626}, doi = {10.1002/cpe.4648}, pages = {14}, year = {2018}, abstract = {Applications with different characteristics in the cloud may have different resources preferences. However, traditional resource allocation and scheduling strategies rarely take into account the characteristics of applications. Considering that an I/O-intensive application is a typical type of application and that frequent I/O accesses, especially small files randomly accessing the disk, may lead to an inefficient use of resources and reduce the quality of service (QoS) of applications, a weight allocation strategy is proposed based on the available resources that a physical server can provide as well as the characteristics of the applications. Using the weight obtained, a resource allocation and scheduling strategy is presented based on the specific application characteristics in the data center. Extensive experiments show that the strategy is correct and can guarantee a high concurrency of I/O per second (IOPS) in a cloud data center with high QoS. Additionally, the strategy can efficiently improve the utilization of the disk and resources of the data center without affecting the service quality of applications.}, language = {en} } @article{KoehlerKoehlerDeckwartetal.2018, author = {Koehler, Friedrich and Koehler, Kerstin and Deckwart, Oliver and Prescher, Sandra and Wegscheider, Karl and Winkler, Sebastian and Vettorazzi, Eik and Polze, Andreas and Stangl, Karl and Hartmann, Oliver and Marx, Almuth and Neuhaus, Petra and Scherf, Michael and Kirwan, Bridget-Anne and Anker, Stefan D.}, title = {Telemedical Interventional Management in Heart Failure II (TIM-HF2), a randomised, controlled trial investigating the impact of telemedicine on unplanned cardiovascular hospitalisations and mortality in heart failure patients}, series = {European Journal of Heart Failure}, volume = {20}, journal = {European Journal of Heart Failure}, number = {10}, publisher = {Wiley}, address = {Hoboken}, issn = {1388-9842}, doi = {10.1002/ejhf.1300}, pages = {1485 -- 1493}, year = {2018}, abstract = {Background Heart failure (HF) is a complex, chronic condition that is associated with debilitating symptoms, all of which necessitate close follow-up by health care providers. Lack of disease monitoring may result in increased mortality and more frequent hospital readmissions for decompensated HF. Remote patient management (RPM) in this patient population may help to detect early signs and symptoms of cardiac decompensation, thus enabling a prompt initiation of the appropriate treatment and care before a manifestation of HF decompensation. Objective The objective of the present article is to describe the design of a new trial investigating the impact of RPM on unplanned cardiovascular hospitalisations and mortality in HF patients. Methods The TIM-HF2 trial is designed as a prospective, randomised, controlled, parallel group, open (with randomisation concealment), multicentre trial with pragmatic elements introduced for data collection. Eligible patients with HF are randomised (1:1) to either RPM + usual care or to usual care only and are followed for 12 months. The primary outcome is the percentage of days lost due to unplanned cardiovascular hospitalisations or all-cause death. The main secondary outcomes are all-cause and cardiovascular mortality. Conclusion The TIM-HF2 trial will provide important prospective data on the potential beneficial effect of telemedical monitoring and RPM on unplanned cardiovascular hospitalisations and mortality in HF patients.}, language = {en} } @article{vonSchorlemerWeiss2019, author = {von Schorlemer, Stephan and Weiß, Christian-Cornelius}, title = {data4life - Eine nutzerkontrollierte Gesundheitsdaten-Infrastruktu}, publisher = {Medizinisch Wissenschaftliche Verlagsgesellschaft}, address = {Berlin}, isbn = {978-3-95466-448-1}, pages = {249 -- 258}, year = {2019}, language = {de} } @misc{HerzogHoenigSchroederPreikschatetal.2019, author = {Herzog, Benedict and H{\"o}nig, Timo and Schr{\"o}der-Preikschat, Wolfgang and Plauth, Max and K{\"o}hler, Sven and Polze, Andreas}, title = {Bridging the Gap}, series = {e-Energy '19: Proceedings of the Tenth ACM International Conference on Future Energy Systems}, journal = {e-Energy '19: Proceedings of the Tenth ACM International Conference on Future Energy Systems}, publisher = {Association for Computing Machinery}, address = {New York}, isbn = {978-1-4503-6671-7}, doi = {10.1145/3307772.3330176}, pages = {428 -- 430}, year = {2019}, abstract = {The recent restructuring of the electricity grid (i.e., smart grid) introduces a number of challenges for today's large-scale computing systems. To operate reliable and efficient, computing systems must adhere not only to technical limits (i.e., thermal constraints) but they must also reduce operating costs, for example, by increasing their energy efficiency. Efforts to improve the energy efficiency, however, are often hampered by inflexible software components that hardly adapt to underlying hardware characteristics. In this paper, we propose an approach to bridge the gap between inflexible software and heterogeneous hardware architectures. Our proposal introduces adaptive software components that dynamically adapt to heterogeneous processing units (i.e., accelerators) during runtime to improve the energy efficiency of computing systems.}, language = {en} } @misc{MarweckiWilsonOfeketal.2019, author = {Marwecki, Sebastian and Wilson, Andrew D. and Ofek, Eyal and Franco, Mar Gonzalez and Holz, Christian}, title = {Mise-Unseen}, series = {UIST '19: Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology}, journal = {UIST '19: Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology}, publisher = {Association for Computing Machinery}, address = {New York}, isbn = {978-1-4503-6816-2}, doi = {10.1145/3332165.3347919}, pages = {777 -- 789}, year = {2019}, abstract = {Creating or arranging objects at runtime is needed in many virtual reality applications, but such changes are noticed when they occur inside the user's field of view. We present Mise-Unseen, a software system that applies such scene changes covertly inside the user's field of view. Mise-Unseen leverages gaze tracking to create models of user attention, intention, and spatial memory to determine if and when to inject a change. We present seven applications of Mise-Unseen to unnoticeably modify the scene within view (i) to hide that task difficulty is adapted to the user, (ii) to adapt the experience to the user's preferences, (iii) to time the use of low fidelity effects, (iv) to detect user choice for passive haptics even when lacking physical props, (v) to sustain physical locomotion despite a lack of physical space, (vi) to reduce motion sickness during virtual locomotion, and (vii) to verify user understanding during story progression. We evaluated Mise-Unseen and our applications in a user study with 15 participants and find that while gaze data indeed supports obfuscating changes inside the field of view, a change is rendered unnoticeably by using gaze in combination with common masking techniques.}, language = {en} } @misc{BjoerkHoelze2019, author = {Bj{\"o}rk, Jennie and H{\"o}lze, Katharina}, title = {Editorial}, series = {Creativity and innovation management}, volume = {28}, journal = {Creativity and innovation management}, number = {3}, publisher = {Wiley}, address = {Hoboken}, issn = {0963-1690}, doi = {10.1111/caim.12336}, pages = {289 -- 290}, year = {2019}, language = {en} } @article{YousfiWeske2019, author = {Yousfi, Alaaeddine and Weske, Mathias}, title = {Discovering commute patterns via process mining}, series = {Knowledge and Information Systems}, volume = {60}, journal = {Knowledge and Information Systems}, number = {2}, publisher = {Springer}, address = {London}, issn = {0219-1377}, doi = {10.1007/s10115-018-1255-1}, pages = {691 -- 713}, year = {2019}, abstract = {Ubiquitous computing has proven its relevance and efficiency in improving the user experience across a myriad of situations. It is now the ineluctable solution to keep pace with the ever-changing environments in which current systems operate. Despite the achievements of ubiquitous computing, this discipline is still overlooked in business process management. This is surprising, since many of today's challenges, in this domain, can be addressed by methods and techniques from ubiquitous computing, for instance user context and dynamic aspects of resource locations. This paper takes a first step to integrate methods and techniques from ubiquitous computing in business process management. To do so, we propose discovering commute patterns via process mining. Through our proposition, we can deduce the users' significant locations, routes, travel times and travel modes. This information can be a stepping-stone toward helping the business process management community embrace the latest achievements in ubiquitous computing, mainly in location-based service. To corroborate our claims, a user study was conducted. The significant places, routes, travel modes and commuting times of our test subjects were inferred with high accuracies. All in all, ubiquitous computing can enrich the processes with new capabilities that go beyond what has been established in business process management so far.}, language = {en} } @article{KastiusSchlosser2022, author = {Kastius, Alexander and Schlosser, Rainer}, title = {Dynamic pricing under competition using reinforcement learning}, series = {Journal of revenue and pricing management}, volume = {21}, journal = {Journal of revenue and pricing management}, number = {1}, publisher = {Springer Nature Switzerland AG}, address = {Cham}, issn = {1476-6930}, doi = {10.1057/s41272-021-00285-3}, pages = {50 -- 63}, year = {2022}, abstract = {Dynamic pricing is considered a possibility to gain an advantage over competitors in modern online markets. The past advancements in Reinforcement Learning (RL) provided more capable algorithms that can be used to solve pricing problems. In this paper, we study the performance of Deep Q-Networks (DQN) and Soft Actor Critic (SAC) in different market models. We consider tractable duopoly settings, where optimal solutions derived by dynamic programming techniques can be used for verification, as well as oligopoly settings, which are usually intractable due to the curse of dimensionality. We find that both algorithms provide reasonable results, while SAC performs better than DQN. Moreover, we show that under certain conditions, RL algorithms can be forced into collusion by their competitors without direct communication.}, language = {en} } @article{MendlingWebervanderAalstetal.2018, author = {Mendling, Jan and Weber, Ingo and van der Aalst, Wil and Brocke, Jan Vom and Cabanillas, Cristina and Daniel, Florian and Debois, Soren and Di Ciccio, Claudio and Dumas, Marlon and Dustdar, Schahram and Gal, Avigdor and Garcia-Banuelos, Luciano and Governatori, Guido and Hull, Richard and La Rosa, Marcello and Leopold, Henrik and Leymann, Frank and Recker, Jan and Reichert, Manfred and Reijers, Hajo A. and Rinderle-Ma, Stefanie and Solti, Andreas and Rosemann, Michael and Schulte, Stefan and Singh, Munindar P. and Slaats, Tijs and Staples, Mark and Weber, Barbara and Weidlich, Matthias and Weske, Mathias and Xu, Xiwei and Zhu, Liming}, title = {Blockchains for Business Process Management}, series = {ACM Transactions on Management Information Systems}, volume = {9}, journal = {ACM Transactions on Management Information Systems}, number = {1}, publisher = {Association for Computing Machinery}, address = {New York}, issn = {2158-656X}, doi = {10.1145/3183367}, pages = {1 -- 16}, year = {2018}, abstract = {Blockchain technology offers a sizable promise to rethink the way interorganizational business processes are managed because of its potential to realize execution without a central party serving as a single point of trust (and failure). To stimulate research on this promise and the limits thereof, in this article, we outline the challenges and opportunities of blockchain for business process management (BPM). We first reflect how blockchains could be used in the context of the established BPM lifecycle and second how they might become relevant beyond. We conclude our discourse with a summary of seven research directions for investigating the application of blockchain technology in the context of BPM.}, language = {en} } @article{KossmannHalfpapJankriftetal.2020, author = {Kossmann, Jan and Halfpap, Stefan and Jankrift, Marcel and Schlosser, Rainer}, title = {Magic mirror in my hand, which is the best in the land?}, series = {Proceedings of the VLDB Endowment}, volume = {13}, journal = {Proceedings of the VLDB Endowment}, number = {11}, publisher = {Association for Computing Machinery}, address = {New York}, issn = {2150-8097}, doi = {10.14778/3407790.3407832}, pages = {2382 -- 2395}, year = {2020}, abstract = {Indexes are essential for the efficient processing of database workloads. Proposed solutions for the relevant and challenging index selection problem range from metadata-based simple heuristics, over sophisticated multi-step algorithms, to approaches that yield optimal results. The main challenges are (i) to accurately determine the effect of an index on the workload cost while considering the interaction of indexes and (ii) a large number of possible combinations resulting from workloads containing many queries and massive schemata with possibly thousands of attributes.
In this work, we describe and analyze eight index selection algorithms that are based on different concepts and compare them along different dimensions, such as solution quality, runtime, multi-column support, solution granularity, and complexity. In particular, we analyze the solutions of the algorithms for the challenging analytical Join Order, TPC-H, and TPC-DS benchmarks. Afterward, we assess strengths and weaknesses, infer insights for index selection in general and each approach individually, before we give recommendations on when to use which approach.}, language = {en} } @article{KoumarelasPapenbrockNaumann2020, author = {Koumarelas, Ioannis and Papenbrock, Thorsten and Naumann, Felix}, title = {MDedup}, series = {Proceedings of the VLDB Endowment}, volume = {13}, journal = {Proceedings of the VLDB Endowment}, number = {5}, publisher = {Association for Computing Machinery}, address = {New York}, issn = {2150-8097}, doi = {10.14778/3377369.3377379}, pages = {712 -- 725}, year = {2020}, abstract = {Duplicate detection is an integral part of data cleaning and serves to identify multiple representations of same real-world entities in (relational) datasets. Existing duplicate detection approaches are effective, but they are also hard to parameterize or require a lot of pre-labeled training data. Both parameterization and pre-labeling are at least domain-specific if not dataset-specific, which is a problem if a new dataset needs to be cleaned. For this reason, we propose a novel, rule-based and fully automatic duplicate detection approach that is based on matching dependencies (MDs). Our system uses automatically discovered MDs, various dataset features, and known gold standards to train a model that selects MDs as duplicate detection rules. Once trained, the model can select useful MDs for duplicate detection on any new dataset. To increase the generally low recall of MD-based data cleaning approaches, we propose an additional boosting step. Our experiments show that this approach reaches up to 94\% F-measure and 100\% precision on our evaluation datasets, which are good numbers considering that the system does not require domain or target data-specific configuration.}, language = {en} } @article{MattisBeckmannReinetal.2022, author = {Mattis, Toni and Beckmann, Tom and Rein, Patrick and Hirschfeld, Robert}, title = {First-class concepts}, series = {Journal of object technology : JOT / ETH Z{\"u}rich, Department of Computer Science}, volume = {21}, journal = {Journal of object technology : JOT / ETH Z{\"u}rich, Department of Computer Science}, number = {2}, publisher = {ETH Z{\"u}rich, Department of Computer Science}, address = {Z{\"u}rich}, issn = {1660-1769}, doi = {10.5381/jot.2022.21.2.a6}, pages = {1 -- 15}, year = {2022}, abstract = {Ideally, programs are partitioned into independently maintainable and understandable modules. As a system grows, its architecture gradually loses the capability to accommodate new concepts in a modular way. While refactoring is expensive and not always possible, and the programming language might lack dedicated primary language constructs to express certain cross-cutting concerns, programmers are still able to explain and delineate convoluted concepts through secondary means: code comments, use of whitespace and arrangement of code, documentation, or communicating tacit knowledge.
Secondary constructs are easy to change and provide high flexibility in communicating cross-cutting concerns and other concepts among programmers. However, such secondary constructs usually have no reified representation that can be explored and manipulated as first-class entities through the programming environment.
In this exploratory work, we discuss novel ways to express a wide range of concepts, including cross-cutting concerns, patterns, and lifecycle artifacts independently of the dominant decomposition imposed by an existing architecture. We propose the representation of concepts as first-class objects inside the programming environment that retain the capability to change as easily as code comments. We explore new tools that allow programmers to view, navigate, and change programs based on conceptual perspectives. In a small case study, we demonstrate how such views can be created and how the programming experience changes from draining programmers' attention by stretching it across multiple modules toward focusing it on cohesively presented concepts. Our designs are geared toward facilitating multiple secondary perspectives on a system to co-exist in symbiosis with the original architecture, hence making it easier to explore, understand, and explain complex contexts and narratives that are hard or impossible to express using primary modularity constructs.}, language = {en} } @article{Schlosser2020, author = {Schlosser, Rainer}, title = {Risk-sensitive control of Markov decision processes}, series = {Computers \& operations research : and their applications to problems of world concern}, volume = {123}, journal = {Computers \& operations research : and their applications to problems of world concern}, publisher = {Elsevier}, address = {Oxford}, issn = {0305-0548}, doi = {10.1016/j.cor.2020.104997}, pages = {14}, year = {2020}, abstract = {In many revenue management applications risk-averse decision-making is crucial. In dynamic settings, however, it is challenging to find the right balance between maximizing expected rewards and minimizing various kinds of risk. In existing approaches utility functions, chance constraints, or (conditional) value at risk considerations are used to influence the distribution of rewards in a preferred way. Nevertheless, common techniques are not flexible enough and typically numerically complex. In our model, we exploit the fact that a distribution is characterized by its mean and higher moments. We present a multi-valued dynamic programming heuristic to compute risk-sensitive feedback policies that are able to directly control the moments of future rewards. Our approach is based on recursive formulations of higher moments and does not require an extension of the state space. Finally, we propose a self-tuning algorithm, which allows to identify feedback policies that approximate predetermined (risk-sensitive) target distributions. We illustrate the effectiveness and the flexibility of our approach for different dynamic pricing scenarios. (C) 2020 Elsevier Ltd. All rights reserved.}, language = {en} } @article{KoumarelasJiangNaumann2020, author = {Koumarelas, Ioannis and Jiang, Lan and Naumann, Felix}, title = {Data preparation for duplicate detection}, series = {Journal of data and information quality : (JDIQ)}, volume = {12}, journal = {Journal of data and information quality : (JDIQ)}, number = {3}, publisher = {Association for Computing Machinery}, address = {New York}, issn = {1936-1955}, doi = {10.1145/3377878}, pages = {24}, year = {2020}, abstract = {Data errors represent a major issue in most application workflows. Before any important task can take place, a certain data quality has to be guaranteed by eliminating a number of different errors that may appear in data. Typically, most of these errors are fixed with data preparation methods, such as whitespace removal. However, the particular error of duplicate records, where multiple records refer to the same entity, is usually eliminated independently with specialized techniques. Our work is the first to bring these two areas together by applying data preparation operations under a systematic approach prior to performing duplicate detection.
Our process workflow can be summarized as follows: It begins with the user providing as input a sample of the gold standard, the actual dataset, and optionally some constraints to domain-specific data preparations, such as address normalization. The preparation selection operates in two consecutive phases. First, to vastly reduce the search space of ineffective data preparations, decisions are made based on the improvement or worsening of pair similarities. Second, using the remaining data preparations an iterative leave-one-out classification process removes preparations one by one and determines the redundant preparations based on the achieved area under the precision-recall curve (AUC-PR). Using this workflow, we manage to improve the results of duplicate detection up to 19\% in AUC-PR.}, language = {en} } @misc{SerthPodlesnyBornsteinetal.2017, author = {Serth, Sebastian and Podlesny, Nikolai and Bornstein, Marvin and Lindemann, Jan and Latt, Johanna and Selke, Jan and Schlosser, Rainer and Boissier, Martin and Uflacker, Matthias}, title = {An interactive platform to simulate dynamic pricing competition on online marketplaces}, series = {2017 IEEE 21st International Enterprise Distributed Object Computing Conference (EDOC)}, journal = {2017 IEEE 21st International Enterprise Distributed Object Computing Conference (EDOC)}, publisher = {Institute of Electrical and Electronics Engineers}, address = {New York}, isbn = {978-1-5090-3045-3}, issn = {2325-6354}, doi = {10.1109/EDOC.2017.17}, pages = {61 -- 66}, year = {2017}, abstract = {E-commerce marketplaces are highly dynamic with constant competition. While this competition is challenging for many merchants, it also provides plenty of opportunities, e.g., by allowing them to automatically adjust prices in order to react to changing market situations. For practitioners however, testing automated pricing strategies is time-consuming and potentially hazardously when done in production. Researchers, on the other side, struggle to study how pricing strategies interact under heavy competition. As a consequence, we built an open continuous time framework to simulate dynamic pricing competition called Price Wars. The microservice-based architecture provides a scalable platform for large competitions with dozens of merchants and a large random stream of consumers. Our platform stores each event in a distributed log. This allows to provide different performance measures enabling users to compare profit and revenue of various repricing strategies in real-time. For researchers, price trajectories are shown which ease evaluating mutual price reactions of competing strategies. Furthermore, merchants can access historical marketplace data and apply machine learning. By providing a set of customizable, artificial merchants, users can easily simulate both simple rule-based strategies as well as sophisticated data-driven strategies using demand learning to optimize their pricing strategies.}, language = {en} } @article{SeiffertHolsteinSchlosseretal.2017, author = {Seiffert, Martin and Holstein, Flavio and Schlosser, Rainer and Schiller, Jochen}, title = {Next generation cooperative wearables}, series = {IEEE access : practical research, open solutions}, volume = {5}, journal = {IEEE access : practical research, open solutions}, publisher = {Institute of Electrical and Electronics Engineers}, address = {Piscataway}, issn = {2169-3536}, doi = {10.1109/ACCESS.2017.2749005}, pages = {16793 -- 16807}, year = {2017}, abstract = {Currently available wearables are usually based on a single sensor node with integrated capabilities for classifying different activities. The next generation of cooperative wearables could be able to identify not only activities, but also to evaluate them qualitatively using the data of several sensor nodes attached to the body, to provide detailed feedback for the improvement of the execution. Especially within the application domains of sports and health-care, such immediate feedback to the execution of body movements is crucial for (re-) learning and improving motor skills. To enable such systems for a broad range of activities, generalized approaches for human motion assessment within sensor networks are required. In this paper, we present a generalized trainable activity assessment chain (AAC) for the online assessment of periodic human activity within a wireless body area network. AAC evaluates the execution of separate movements of a prior trained activity on a fine-grained quality scale. We connect qualitative assessment with human knowledge by projecting the AAC on the hierarchical decomposition of motion performed by the human body as well as establishing the assessment on a kinematic evaluation of biomechanically distinct motion fragments. We evaluate AAC in a real-world setting and show that AAC successfully delimits the movements of correctly performed activity from faulty executions and provides detailed reasons for the activity assessment.}, language = {en} } @article{KossmannSchlosser2020, author = {Kossmann, Jan and Schlosser, Rainer}, title = {Self-driving database systems}, series = {Distributed and parallel databases}, volume = {38}, journal = {Distributed and parallel databases}, number = {4}, publisher = {Springer}, address = {Dordrecht}, issn = {0926-8782}, doi = {10.1007/s10619-020-07288-w}, pages = {795 -- 817}, year = {2020}, abstract = {Challenges for self-driving database systems, which tune their physical design and configuration autonomously, are manifold: Such systems have to anticipate future workloads, find robust configurations efficiently, and incorporate knowledge gained by previous actions into later decisions. We present a component-based framework for self-driving database systems that enables database integration and development of self-managing functionality with low overhead by relying on separation of concerns. By keeping the components of the framework reusable and exchangeable, experiments are simplified, which promotes further research in that area. Moreover, to optimize multiple mutually dependent features, e.g., index selection and compression configurations, we propose a linear programming (LP) based algorithm to derive an efficient tuning order automatically. Afterwards, we demonstrate the applicability and scalability of our approach with reproducible examples.}, language = {en} } @article{SchneiderWenigPapenbrock2021, author = {Schneider, Johannes and Wenig, Phillip and Papenbrock, Thorsten}, title = {Distributed detection of sequential anomalies in univariate time series}, series = {The VLDB journal : the international journal on very large data bases}, volume = {30}, journal = {The VLDB journal : the international journal on very large data bases}, number = {4}, publisher = {Springer}, address = {Berlin}, issn = {1066-8888}, doi = {10.1007/s00778-021-00657-6}, pages = {579 -- 602}, year = {2021}, abstract = {The automated detection of sequential anomalies in time series is an essential task for many applications, such as the monitoring of technical systems, fraud detection in high-frequency trading, or the early detection of disease symptoms. All these applications require the detection to find all sequential anomalies possibly fast on potentially very large time series. In other words, the detection needs to be effective, efficient and scalable w.r.t. the input size. Series2Graph is an effective solution based on graph embeddings that are robust against re-occurring anomalies and can discover sequential anomalies of arbitrary length and works without training data. Yet, Series2Graph is no t scalable due to its single-threaded approach; it cannot, in particular, process arbitrarily large sequences due to the memory constraints of a single machine. In this paper, we propose our distributed anomaly detection system, short DADS, which is an efficient and scalable adaptation of Series2Graph. Based on the actor programming model, DADS distributes the input time sequence, intermediate state and the computation to all processors of a cluster in a way that minimizes communication costs and synchronization barriers. Our evaluation shows that DADS is orders of magnitude faster than S2G, scales almost linearly with the number of processors in the cluster and can process much larger input sequences due to its scale-out property.}, language = {en} } @book{MeyerSmirnovWeske2011, author = {Meyer, Andreas and Smirnov, Sergey and Weske, Mathias}, title = {Data in business processes}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, isbn = {978-3-86956-144-8}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-53046}, publisher = {Universit{\"a}t Potsdam}, pages = {40}, year = {2011}, abstract = {Process and data are equally important for business process management. Process data is especially relevant in the context of automated business processes, process controlling, and representation of organizations' core assets. One can discover many process modeling languages, each having a specific set of data modeling capabilities and the level of data awareness. The level of data awareness and data modeling capabilities vary significantly from one language to another. This paper evaluates several process modeling languages with respect to the role of data. To find a common ground for comparison, we develop a framework, which systematically organizes process- and data-related aspects of the modeling languages elaborating on the data aspects. Once the framework is in place, we compare twelve process modeling languages against it. We generalize the results of the comparison and identify clusters of similar languages with respect to data awareness.}, language = {de} } @phdthesis{Kluth2011, author = {Kluth, Stephan}, title = {Quantitative modeling and analysis with FMC-QE}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-52987}, school = {Universit{\"a}t Potsdam}, year = {2011}, abstract = {The modeling and evaluation calculus FMC-QE, the Fundamental Modeling Concepts for Quanti-tative Evaluation [1], extends the Fundamental Modeling Concepts (FMC) for performance modeling and prediction. In this new methodology, the hierarchical service requests are in the main focus, because they are the origin of every service provisioning process. Similar to physics, these service requests are a tuple of value and unit, which enables hierarchical service request transformations at the hierarchical borders and therefore the hierarchical modeling. Through reducing the model complexity of the models by decomposing the system in different hierarchical views, the distinction between operational and control states and the calculation of the performance values on the assumption of the steady state, FMC-QE has a scalable applica-bility on complex systems. According to FMC, the system is modeled in a 3-dimensional hierarchical representation space, where system performance parameters are described in three arbitrarily fine-grained hierarchi-cal bipartite diagrams. The hierarchical service request structures are modeled in Entity Relationship Diagrams. The static server structures, divided into logical and real servers, are de-scribed as Block Diagrams. The dynamic behavior and the control structures are specified as Petri Nets, more precisely Colored Time Augmented Petri Nets. From the structures and pa-rameters of the performance model, a hierarchical set of equations is derived. The calculation of the performance values is done on the assumption of stationary processes and is based on fundamental laws of the performance analysis: Little's Law and the Forced Traffic Flow Law. Little's Law is used within the different hierarchical levels (horizontal) and the Forced Traffic Flow Law is the key to the dependencies among the hierarchical levels (vertical). This calculation is suitable for complex models and allows a fast (re-)calculation of different performance scenarios in order to support development and configuration decisions. Within the Research Group Zorn at the Hasso Plattner Institute, the work is embedded in a broader research in the development of FMC-QE. While this work is concentrated on the theoretical background, description and definition of the methodology as well as the extension and validation of the applicability, other topics are in the development of an FMC-QE modeling and evaluation tool and the usage of FMC-QE in the design of an adaptive transport layer in order to fulfill Quality of Service and Service Level Agreements in volatile service based environments. This thesis contains a state-of-the-art, the description of FMC-QE as well as extensions of FMC-QE in representative general models and case studies. In the state-of-the-art part of the thesis in chapter 2, an overview on existing Queueing Theory and Time Augmented Petri Net models and other quantitative modeling and evaluation languages and methodologies is given. Also other hierarchical quantitative modeling frameworks will be considered. The description of FMC-QE in chapter 3 consists of a summary of the foundations of FMC-QE, basic definitions, the graphical notations, the FMC-QE Calculus and the modeling of open queueing networks as an introductory example. The extensions of FMC-QE in chapter 4 consist of the integration of the summation method in order to support the handling of closed networks and the modeling of multiclass and semaphore scenarios. Furthermore, FMC-QE is compared to other performance modeling and evaluation approaches. In the case study part in chapter 5, proof-of-concept examples, like the modeling of a service based search portal, a service based SAP NetWeaver application and the Axis2 Web service framework will be provided. Finally, conclusions are given by a summary of contributions and an outlook on future work in chapter 6. [1] Werner Zorn. FMC-QE - A New Approach in Quantitative Modeling. In Hamid R. Arabnia, editor, Procee-dings of the International Conference on Modeling, Simulation and Visualization Methods (MSV 2007) within WorldComp '07, pages 280 - 287, Las Vegas, NV, USA, June 2007. CSREA Press. ISBN 1-60132-029-9.}, language = {en} }