Refine
Year of publication
- 2020 (24) (remove)
Document Type
- Doctoral Thesis (20)
- Article (3)
- Book (1)
Language
- English (24) (remove)
Has Fulltext
- yes (24)
Is part of the Bibliography
- no (24)
Keywords
- Energieversorgung (2)
- Achtsamkeit (1)
- Advanced Metering Infrastructure (1)
- Algebraic fault attack (1)
- Algebraic normal form (1)
- Anomalie (1)
- Approximation (1)
- Arbeitsbeziehungen (1)
- Arising phenomena (1)
- Asymptotic lower error bounds (1)
Institute
The autonomic composition of Virtual Networks (VNs) and Service Function Chains (SFCs)based on application requirements is significant for complex environments. In this paper, we use graph transformation in order to compose an Extended Virtual Network (EVN) that is based on
different requirements, such as locations, low latency, redundancy, and security functions. The EVN can represent physical environment devices and virtual application and network functions. We build
a generic Virtual Network Embedding (VNE) framework for transforming an Application Request (AR) to an EVN. Subsequently, we define a set of transformations that reflect preliminary topological, performance, reliability, and security policies. These transformations update the entities and demands of the VN and add SFCs that include the required Virtual Network Functions (VNFs). Additionally, we propose a greedy proactive heuristic for path-independent embedding of the composed SFCs. This heuristic is appropriate for real complex environments, such as industrial networks. Furthermore, we present an Industrail Internet of Things (IIoT) use case that was inspired by Industry 4.0 concepts,in which EVNs for remote asset management are deployed over three levels; manufacturing halls and edge and cloud computing. We also implement the developed methods in Alevin and show exemplary mapping results from our use case. Finally, we evaluate the chain embedding heuristic while using a random topology that is typical for such a use case, and show that it can improve the admission ratio and resource utilization with minimal overhead.
Earlier research showed that religion is related to participation
among adolescents. It emphasized the effects of belonging (affiliation to groups and traditions) on community service among Western populations. This article takes one step further and focuses on religiosity as a potential motivation for community problem solving during adolescence and young adulthood, in the Eastern European Orthodox cultural setting. Data comes from several semistructured interviews with participants in a civic project conducted in the city of Timisoara (Romania). Findings indicated a low impact of the social religious component on engagement. The cognitive dimension of belief and the emotional bonding (prayer, ritual connection to the higher reality) function as indirect motivators, through the moral element of behavior. Results also showed a privatization of spiritual life at young adults (the invisible religion): estrangement from doctrines and the development of an individualistic type of morality, meant to drive volunteer activities further.
Southeast Asia is one of the most dynamic regions in the world. This volume offers a timely approach to Southeast Asian Studies, covering recent transitions in the realms of urbanism, rural development, politics, and media. While most of the contributions deal with the era of post-independence, some tackle the colonial period and the resulting developments. The volume also includes insights from Southern India.
As a tribute to the interdisciplinary project of Southeast Asian Studies, this book brings together authors from disciplines as diverse as area studies, sociology, history, geography, and journalism.
This study explores the integration of data journalism within three European legacy news organisations through the lens of organisational structure and professional culture. Interviews with data journalists and editors suggest that professional routines resonate with established data journalism epistemologies, values, and norms that appear to be constitutional for an inter-organisational data journalism subculture. At the same time, organisational structure either integrates the journalistic subculture by increasing levels of complexity, formalisation, and centralisation or rejects it by not accommodating it structurally or culturally. The three data teams work along epistemologies of computer-assisted reporting, investigative journalism, and data journalism but differentiate themselves through nuanced understandings of data journalism practice, driven by individual journalists. After a structureless episode, one team sets itself apart as it diverges from data-driven routines and orients itself towards technological and interdisciplinary interactive journalism. The findings show an interdependence of individual efforts, varying conceptualisations of data journalism practice, and interplay between organisational structure and professional culture.
The current electricity grid is undergoing major changes. There is increasing pressure to move away from power generation from fossil fuels, both due to ecological concerns and fear of dependencies on scarce natural resources. Increasing the share of decentralized generation from renewable sources is a widely accepted way to a more sustainable power infrastructure. However, this comes at the price of new challenges: generation from solar or wind power is not controllable and only forecastable with limited accuracy. To compensate for the increasing volatility in power generation, exerting control on the demand side is a promising approach. By providing flexibility on demand side, imbalances between power generation and demand may be mitigated.
This work is concerned with developing methods to provide grid support on demand side while limiting the associated costs. This is done in four major steps: first, the target power curve to follow is derived taking both goals of a grid authority and costs of the respective load into account. In the following, the special case of data centers as an instance of significant loads inside a power grid are focused on more closely. Data center services are adapted in a way such as to achieve the previously derived power curve. By means of hardware power demand models, the required adaptation of hardware utilization can be derived. The possibilities of adapting software services are investigated for the special use case of live video encoding. A method to minimize quality of experience loss while reducing power demand is presented. Finally, the possibility of applying probabilistic model checking to a continuous demand-response scenario is demonstrated.
Fundamental changes in business-to-business (B2B) buying behavior confront B2B supplier firms with unprecedented challenges. On the one hand, a rising share of industrial buyers demands digitalized offerings and processes from suppliers. Consequently, suppliers are urged to implement digital transformations by expanding the range of both digital offerings and processes. On the other hand, B2B buyers increasingly expect suppliers to provide individually tailored solutions to their idiosyncratic needs. Hence, suppliers are also required to implement non-digital transformations by providing offerings and processes that are customized to each customers’ specific requirements.
The rise of these digital and non-digital transformations calls established knowledge into question. Thus, B2B marketing research and practice are urged to create a comprehensive understanding of digital and non-digital transformations by means of novel and empirically grounded insights and derive actionable response strategies. In respond, my dissertation addresses the overall research question of how B2B supplier firms can successfully implement both digital and non-digital transformations in three individual essays.
In Essay 1, I offer a broader perspective on both digital and non-digital transformations by investigating digital service customization (i.e., the tailoring of digital B2B services to customers’ individual needs). Through a systematic literature review and bibliometric analysis, I outline a comprehensive set of factors that favor the application of distinct digital service customization strategies. Essay 2 represents a deep dive into digital transformations of sales processes. By making use of two rich sets of qualitative interview material from supplier and buyer firms, I identify the challenges resulting for B2B salespeople from the introduction of digital sales channels into personal selling. Moreover, I uncover facilitating mechanisms that sales managers can employ to support salespeople in coping with digital sales channels. Finally, Essay 3 constitutes a deep dive into non-digital transformations. Based on qualitative interview material and survey data from matched sales manager–salesperson dyads, the essay explores how configurations of individual salespeople’s personal and procedural competencies facilitate success at selling customer solutions (i.e., highly customized, performance-oriented offerings comprising products and/or services). The essay shows that successfully selling customized offerings like solutions hinges on salespeople’s unique configurations of present and absent competencies.
In a nutshell, these essays provide three major insights on how B2B suppliers can successfully implement digital and non-digital transformations. First, they underscore that a comprehensive understanding of the origins and spillover effects of transformations is a key prerequisite to successfully implementing them. Second, they unveil that digital and non-digital transformations impact on multiple organizational levels. Third, they point out important resources and capabilities that help suppliers to successfully implement transformations, be they digital or non-digital.
With this dissertation, I make substantial contributions to the broader literature on digital and non-digital transformations in B2B contexts. At the same time, my dissertation provides hands-on implications for managers in B2B supplier firms that are facing fundamental transformations in the marketplace—both digital and non-digital in nature.
With the frequency and impact of data breaches raising, it has become essential for organizations to automate intrusion detection via machine learning solutions. This generally comes with numerous challenges, among others high class imbalance, changing target concepts and difficulties to conduct sound evaluation. In this thesis, we adopt a user-centered anomaly detection perspective to address selected challenges of intrusion detection, through a real-world use case in the identity and access management (IAM) domain. In addition to the previous challenges, salient properties of this particular problem are high relevance of categorical data, limited feature availability and total absence of ground truth.
First, we ask how to apply anomaly detection to IAM audit logs containing a restricted set of mixed (i.e. numeric and categorical) attributes. Then, we inquire how anomalous user behavior can be separated from normality, and this separation evaluated without ground truth. Finally, we examine how the lack of audit data can be alleviated in two complementary settings. On the one hand, we ask how to cope with users without relevant activity history ("cold start" problem). On the other hand, we seek how to extend audit data collection with heterogeneous attributes (i.e. categorical, graph and text) to improve insider threat detection.
After aggregating IAM audit data into sessions, we introduce and compare general anomaly detection methods for mixed data to a user identification approach, designed to learn the distinction between normal and malicious user behavior. We find that user identification outperforms general anomaly detection and is effective against masquerades. An additional clustering step allows to reduce false positives among similar users. However, user identification is not effective against insider threats. Furthermore, results suggest that the current scope of our audit data collection should be extended.
In order to tackle the "cold start" problem, we adopt a zero-shot learning approach. Focusing on the CERT insider threat use case, we extend an intrusion detection system by integrating user relations to organizational entities (like assignments to projects or teams) in order to better estimate user behavior and improve intrusion detection performance. Results show that this approach is effective in two realistic scenarios.
Finally, to support additional sources of audit data for insider threat detection, we propose a method representing audit events as graph edges with heterogeneous attributes. By performing detection at fine-grained level, this approach advantageously improves anomaly traceability while reducing the need for aggregation and feature engineering. Our results show that this method is effective to find intrusions in authentication and email logs.
Overall, our work suggests that masquerades and insider threats call for different detection methods. For masquerades, user identification is a promising approach. To find malicious insiders, graph features representing user context and relations to other entities can be informative. This opens the door for tighter coupling of intrusion detection with user identities, roles and privileges used in IAM solutions.
New arising phenomena in the occupational realm strongly shape contemporary work settings. These developments heavily affect how individuals work within and beyond organizational boundaries. Two phenomena associated with the changing nature of work have been especially prevalent in work settings and intensively discussed in public debates. First, organizations started to introduce mindfulness practices to their workforce. Rooted in spirituality and formerly used in clinical therapy, mindfulness is applied as a human resource development practice to train employees and managers to cope with the increased work intensification. Second, digitization and the importance of individualization opened up the path for work settings beyond organizational boundaries on crowdworking online platforms. On these online platforms, workers process tasks independently and remotely. Research just started to address the implications and meaning of mindfulness practices in organizations and the rise of crowdworking platforms. Several questions remain unanswered. This dissertation addresses unanswered but pressing questions related to these two phenomena shaping contemporary work settings. Structured in four essays the first two essays address the application and meaning of mindfulness practices. The first essay analyzes the meaning and interpretations of these new practices within organizations. The second essay takes contextual factors of the organizational environment into account and investigates their relevance for the successful implementation of mindfulness practices. The second two essays are dedicated to work attitudes and behavior on crowdworking online platform. Essay three captures individuals’ motivation for working on such platforms and their effects for workers’ work performance. The last essay deals with the role of professional crowdworking online communities in the work experience and asses the effects of social support in these communities on occupational identification, work meaningfulness and finally on work engagement. Each essay in this dissertation generates new insights on arising phenomena in contemporary work settings. They address several timely yet unanswered research questions for these rising phenomena and thereby offer a deeper and more nuanced understanding of the role mindfulness practices and crowdworking online platforms play in the context of the future of work.
The current movement towards a smart grid serves as a solution to present power grid challenges by introducing numerous monitoring and communication technologies. A dependable, yet timely exchange of data is on the one hand an existential prerequisite to enable Advanced Metering Infrastructure (AMI) services, yet on the other a challenging endeavor, because the increasing complexity of the grid fostered by the combination of Information and Communications Technology (ICT) and utility networks inherently leads to dependability challenges.
To be able to counter this dependability degradation, current approaches based on high-reliability hardware or physical redundancy are no longer feasible, as they lead to increased hardware costs or maintenance, if not both. The flexibility of these approaches regarding vendor and regulatory interoperability is also limited. However, a suitable solution to the AMI dependability challenges is also required to maintain certain regulatory-set performance and Quality of Service (QoS) levels.
While a part of the challenge is the introduction of ICT into the power grid, it also serves as part of the solution. In this thesis a Network Functions Virtualization (NFV) based approach is proposed, which employs virtualized ICT components serving as a replacement for physical devices. By using virtualization techniques, it is possible to enhance the performability in contrast to hardware based solutions through the usage of virtual replacements of processes that would otherwise require dedicated hardware. This approach offers higher flexibility compared to hardware redundancy, as a broad variety of virtual components can be spawned, adapted and replaced in a short time. Also, as no additional hardware is necessary, the incurred costs decrease significantly. In addition to that, most of the virtualized components are deployed on Commercial-Off-The-Shelf (COTS) hardware solutions, further increasing the monetary benefit.
The approach is developed by first reviewing currently suggested solutions for AMIs and related services. Using this information, virtualization technologies are investigated for their performance influences, before a virtualized service infrastructure is devised, which replaces selected components by virtualized counterparts. Next, a novel model, which allows the separation of services and hosting substrates is developed, allowing the introduction of virtualization technologies to abstract from the underlying architecture. Third, the performability as well as monetary savings are investigated by evaluating the developed approach in several scenarios using analytical and simulative model analysis as well as proof-of-concept approaches. Last, the practical applicability and possible regulatory challenges of the approach are identified and discussed.
Results confirm that—under certain assumptions—the developed virtualized AMI is superior to the currently suggested architecture. The availability of services can be severely increased and network delays can be minimized through centralized hosting. The availability can be increased from 96.82% to 98.66% in the given scenarios, while decreasing the costs by over 60% in comparison to the currently suggested AMI architecture. Lastly, the performability analysis of a virtualized service prototype employing performance analysis and a Musa-Okumoto approach reveals that the AMI requirements are fulfilled.