Service Quality and Profit Control in Utility Computing Service Life Cycles

Utility Computing is one of the most discussed business models in the context of Cloud Computing. Service providers are more and more pushed into the role of utilities by their customer's expectations. Subsequently, the demand for predictable service availability and pay-per-use pricing models increases. Furthermore, for providers, a new opportunity to optimise resource usage offers arises, resulting from new virtualisation techniques. In this context, the control of service quality and profit depends on a deep understanding of the representation of the relationship between business and technique. This research analyses the relationship between the business model of Utility Computing and Service-oriented Computing architectures hosted in Cloud environments. The relations are clarified in detail for the entire service life cycle and throughout all architectural layers. Based on the elaborated relations, an approach to a delivery framework is evolved, in order to enable the optimisation of the relation attributes, while the service implementation passes through business planning, development, and operations. Related work from academic literature does not cover the collected requirements on service offers in this context. This finding is revealed by a critical review of approaches in the fields of Cloud Computing, Grid Computing, and Application Clusters. The related work is analysed regarding appropriate provision architectures and quality assurance approaches. The main concepts of the delivery framework are evaluated based on a simulation model. To demonstrate the ability of the framework to model complex pay-per-use service cascades in Cloud environments, several experiments have been conducted. First outcomes proof that the contributions of this research undoubtedly enable the optimisation of service quality and profit in Cloud-based Service-oriented Computing architectures

Methodology to sustain common information spaces for research collaborations

Information and knowledge sharing collaborations are essential for scientific research and innovation. They provide opportunities to pool expertise and resources. They are required to draw on today’s wealth of data to address pressing societal challenges. Establishing effective collaborations depends on the alignment of intellectual and technical capital. In this thesis we investigate implications and influences of socio-technical aspects of research collaborations to identify methods of facilitating their formation and sustained success. We draw on our experience acquired in an international federated seismological context, and in a large research infrastructure for solid-Earth sciences. We recognise the centrality of the users and propose a strategy to sustain their engagement as actors participating in the collaboration. Our approach promotes and enables their active contribution in the construction and maintenance of Common Information Spaces (CISs). These are shaped by conceptual agreements that are captured and maintained to facilitate mutual understanding and to underpin their collaborative work. A user-driven approach shapes the evolution of a CIS based on the requirements of the communities involved in the collaboration. Active users’ engagement is pursued by partitioning concerns and by targeting their interests. For instance, application domain experts focus on scientific and conceptual aspects; data and information experts address knowledge representation issues; and architects and engineers build the infrastructure that populates the common space. We introduce a methodology to sustain CIS and a conceptual framework that has its foundations on a set of agreed Core Concepts forming a Canonical Core (CC). A representation of such a CC is also introduced that leverages and promotes reuse of existing standards: EPOS-DCAT-AP. The application of our methodology shows promising results with a good uptake and adoption by the targeted communities. This encourages us to continue applying and evaluating such a strategy in the future

Multi-agent based architecture for digital libraries

Digital Libraries (DL) generally contain a collection of independently maintained data sets, in different formats, which may be queried by geographically dispersed users. The general problem of managing such large digital data archives is particularly challenging when the system must cope with data which is processed on demand. This dissertation proposes a Multi-Agent System (MAS) architecture for the utilisation of an active DL that provides computing services in addition to data-retrieval services, so that users can initiate computing jobs on remote supercomputers for processing, mining, and filtering of the data in the library. The system architecture is based on a collaborative set of agents, where each agent undertakes a pre-defined role, and is responsible for offering a particular type of service. The integration of services is based on a user defined query which can range in complexity from simple queries, to specialised algorithms which are transmitted to image processing archives as mobile agents. The proposed architecture enables new information sources and services to be integrated into the system dynamically, supports autonomous and dynamic on-demand data processing based on collaboration between agents, capable of handling a large number of concurrent users. Focus is based on the management of mobile agents which roam through the servers that constitute the DL to serve user queries. A new load balancing scheme is proposed for managing agent load among the available servers, based on the system state information and predictions about lifetime of agent tasks and server status. The system architecture is further extended by defining a gateway to provide interoperability with other heterogeneous agent-based systems. Interoperability in this sense enables agents from different types of platforms to communicate between themselves and use services provided by other systems. The novelty of the proposed gateway approach lies in the ability to adapt an existing legacy system for use with the agent-based approach (and one that adheres to FIPA standards). A prototype has been developed as a proof-of-concept to outline the principles and ideas involved, with reference to the Synthetic Aperture Radar Atlas (SARA) DL composed of multi-spectral remote-sensing imagery of the Earth. Although, the work presented in this dissertation has been evaluated in the context of SARA DL, the proposed techniques suggest useful guidelines that may be employed by other active archival systems

Archives, Access and Artificial Intelligence

Digital archives are transforming the Humanities and the Sciences. Digitized collections of newspapers and books have pushed scholars to develop new, data-rich methods. Born-digital archives are now better preserved and managed thanks to the development of open-access and commercial software. Digital Humanities have moved from the fringe to the center of academia. Yet, the path from the appraisal of records to their analysis is far from smooth. This book explores crossovers between various disciplines to improve the discoverability, accessibility, and use of born-digital archives and other cultural assets

A complexity perspective on organisational change: making sense of emerging patterns in self-organising systems

This thesis adopts a complexity perspective to further understanding of organisational change and its leadership. It uses complexity to reframe organisational change as self-organising; a continuous process with emergent outcomes. Then it considers individual potency of reflexive agents within self-organising change, by asking what emerging organisational patterns change leaders notice, interpret and respond to as they pursue change in organisations. That question is explored within a longitudinal, multi-level, largely qualitative, case study. The study focuses deeply on an organisation in the midst of change from the perspective of change leaders. Multiple data sources are used: in-depth interviews; observation; documents; a workshop; and a social networks/change leader survey. Within an inductive analytic strategy, the study employs a combination of analytic procedures to make sense of rich, eclectic, case data. It takes an interpretive epistemological stance, while retaining the realist ontological thread of a complex reality. The research findings highlight the challenges facing change leaders trying to make sense of emerging patterns, in far-from-equilibrium conditions, when they too are ‘on the receiving end’ of change. The findings illustrate that change leaders notice and interpret emerging organisational patterns in particular spheres of human activity: patterns of events; ‘changing patterns of relations’; and ‘changing patterns of attention’. Multi-level triangulation highlights fractal self-similarity in the patterning of emergent responses across levels: responses of individual change leaders and organisational response patterns across a population of interdependent people can both be categorised in affective, cognitive and behavioural terms. The major contributions of this study are (1) its identification of domains of emergent organisational change; and (2) its development of a multi-level typology of domains of emergent change. While organisational change outcomes are emergent and inherently unpredictable, these findings may help scholars and practitioners to theoretically anticipate and make sense of emerging organisational patterns

Long-term landscape changes in relation to rainfall variability and natural resources management in the northern Ethiopian highlands

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