The KLU faculty, post-docs, and PhD candidates regularly publish the results of their research in scientific journals. You will find a complete overview of all KLU publications below (e.g. articles in peer-reviewed journals, professional journals, books, working papers, and conference proceedings). Search for relevant terms and keywords, or filter the list by name, year of publication or type of publication. The references include DOIs and abstracts where available, and you can download them to your own reference database or platform. We regularly update the database with new publications.

Book Chapters

Copy reference link   DOI: doi:10.1007/978-3-319-29582-4_9

Abstract: The adoption of the workflow technology in the eScience domain has contributed to the increase of simulation-based applications orchestrating different services in a flexible and error-free manner. The nature of the provisioning and execution of such simulations makes them potential candidates to be migrated and executed in Cloud environments. The wide availability of Infrastructure-as-a-Service (IaaS) Cloud offerings and service providers has contributed to a raise in the number of supporters of partially or completely migrating and running their scientific experiments in the Cloud. Focusing on Scientific Workflow-based Simulation Environments (SWfSE) applications and their corresponding underlying runtime support, in this research work we aim at empirically analyzing and evaluating the impact of migrating such an environment to multiple IaaS infrastructures. More specifically, we focus on the investigation of multiple Cloud providers and their corresponding optimized and non-optimized IaaS offerings with respect to their offered performance, and its impact on the incurred monetary costs when migrating and executing a SWfSE. The experiments show significant performance improvements and reduced monetary costs when executing the simulation environment in off-premise Clouds.

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Copy reference link   DOI: 10.1007/978-3-642-24755-2_23

Abstract: In the field of natural and engineering science, computer simulations play an increasingly important role to explain or predict phenomena of the real world. Although the software landscape is crucial to support scientists in their every day work, we recognized during our work with scientific institutes that many simulation programs can be considered legacy monolithic applications. They are developed without adhering to known software engineering guidelines, lack an acceptable software ergonomics, run sequentially on single workstations and require tedious manual tasks. We are convinced that SOA concepts and the service composition technology can help to improve this situation. In this paper we report on the results of our work on the service- and service composition-based re-engineering of a legacy scientific application for the simulation of the ageing process in copper-alloyed. The underlying general concept for a distributed, service-based simulation infrastructure is also applicable to other scenarios. Core of the infrastructure is a resource manager that steers server work load and handles simulation data.

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Conference Proceedings

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Abstract: Blockchain is an emergent technology concept that enables the decentralized and im-mutable storage of verified data. Over the last few years, it has increasingly attracted the attention of different industries. Especially in Fintech, Blockchain is hyped as the silver bullet that might overthrow today’s payment handling. Slowly, the logistics and supply chain man-agement community realizes how profoundly Blockchain could affect their industry. To shed light on this emerging field, we conducted an online survey and asked logistics professionals for their opinion on use case exemplars, barriers, facilitators, and the general prospects of Blockchain in logistics and supply chain management. We found most of our participants are fairly positive about this new technology and the benefits it offers. However, factors like the hierarchical level, Blockchain experiences, and the industry sector have a significant impact on the participants’ evaluation. We reason that the benefits over existing IT solutions must be carved out more carefully and use cases must be further explored to get a rather conservative industry, like logistics, more excited about Blockchain.

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Abstract: Expatriation research has predominantly focused on company-backed expatriates (CBEs), who are sent abroad by their employer, and on examining how their levels of on-the-job embeddedness affect their intention to prematurely repatriate. Yet, most expatriates are not CBEs but self-initiated expatriates (SIEs). In this article we hypothesize that for their behavioral and demographic features, CBEs and SIEs differ substantially in their levels of on-the job and off-the-job embeddedness. Moreover, these difference lay ground for moderating effects resulting in different explanations for the repatriation intention of CBEs and SIEs. Drawing on a unique sample of 345 expatriates from 40 different countries we show that while SIEs experience a higher degree of off-the-job embeddedness than CBEs, the two expatriate types do not differ in their levels of on-the-job embeddedness. Also, off-the-job embeddedness is more important for explaining the repatriation intention of CBEs than of SIEs. Most importantly, whereas for SIEs low levels of on-the-job embeddedness increase their intention to repatriate, for CBEs high-not low-levels increase their intention to repatriate. Our findings carry important theoretical implications for research on expatriates and provide managerial implications related to the choice, hiring criteria, and support programs for expatriates.

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Abstract: This work aims to discuss modeling issues on solving the transport distribution problem in freight transport. The traditional distribution model – the Gravity Model – is introduced in detail with the focus on its forecasting capability of freight transport distribution. Through analyses on the base of observed and predicted data of freight transport in Germany, it is found that, compared to applying the Gravity Model, directly balancing the observed distribution from the last period using the Furness Method can generate more closer predictions to the official predictions in a planning project of the German Federal Ministry of Transport, Building and Urban Development. However, the re is a doubt about whether this Furness Method itself brings about an impact on the deterrence exponent. Based on the proposition that the Furness Method dilutes the deterrence effect of transport costs, a compensating procedure is developed in this work as a supplement to the traditional process, offering a new thinking to improve the prediction performance of distribution models.

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Abstract: Proactive event processing constitutes the next phase in the evolution of complex event processing. Proactive event processing makes it possible to anticipate potential issues during process execution and thereby enables proactive process management. One industry domain that can expect relevant benefits from applying proactive event processing is transportation. Transportation companies face numerous stochastic issues when managing the shipment of goods. One such issue faced in airfreight is the exact volume, weight, and number of pieces that a shipper wants to have shipped. Because of the high cost of air shipments, discrepancies between what has been booked by a shipper and the actual volume that is delivered impose costs that create problems for all participants in a shipment. One potential approach to addressing this problem is to use real-time monitoring and proactive alerting to assist air freight companies in anticipating actual delivered weights, volumes, and piece counts. In this paper we address the issue of cargo shipments by leveraging real-time monitoring data collected from an industry-standard monitoring system of a large freight forwarding company. Our evidence indicates that by using a novel proactive event-driven software engine, prediction about the weight of shipments can be developed and used in a proactive manner to assist air freight planners in making better estimates and plans for the shipment of goods. We demonstrate that through the use of this proactive approach, predictions concerning over and under-weight loads can be made days in advance of a shipment, thus enabling the air freight planner to optimize their load plans and thus maximize the revenue that they generate from shipments.

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Copy reference link   DOI: 10.1007/978-3-642-38827-9_26

Abstract: The logistics service industry is characterized by a high level of collaboration between logistics customers and providers. In fact, sophisticated, knowledge-intense business models such as fourth party and lead logistics evolved in recent years that are responsible for planning, coordination, and monitoring entire supply chains across logistics companies. The Logistics Service Engineering and Management (LSEM) platform is a service-oriented infrastructure for the development and management of collaborative contract logistics enabling fourth party and lead logistics. The service modeling framework (SMF) is a central element of the LSEM-platform. It allows users of the platform to define, manage and combine logistics services from different providers and allows for an integrated view on complex services setups. In this paper, the Service Meta Modeling Editor is presented as an essential part of the SMF. It allows connecting and integrating various types of service models and avoids the need to define and maintain a complex, global service model. Instead a comprehensive service model is built bottom-up in that elements from different models are linked on a metamodel level.

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Abstract: In disassemble-to-order (DTO) systems randomness of recoverable parts gained from used products creates a major challenge for appropriate planning. Typically, it is assumed that yields from disassembly are either stochastically proportional (SP) or follow a binomial (BI) process. In the case of yield misspecification, it can be shown that the BI yield assumption usually results in a lower penalty than the SP yield assumption. For BI yield, however, a suitable, powerful heuristic is needed in order to facilitate DTO problems olving for complex realworld product structures. We present a heuristic approach that is based on a ecomposition procedure for the underlying non-linear stochastic optimization problem and that can be applied to problems of arbitrary size. A numerical performance study reveals that this heuristic yields close - to - optimal results.

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