Addressing the challenge of managing large-scale digital multimedia libraries

Traditional Digital Libraries require human editorial control over the lifecycles of digital objects contained therein. This imposes an inherent (human) overhead on the maintenance of these digital libraries, which becomes unwieldy once the number of important information units in the digital library becomes too large. A revised framework is needed for digital libraries that takes the onus off the editor and allows the digital library to directly control digital object lifecycles, by employing a set of transformation rules that operate directly on the digital objects themselves. In this paper we motivate and describe a revised digital library framework that utilises transformation rules to automatically optimise system resources. We evaluate this library in three scenarios and also outline how we could apply concepts from this revised framework to address other challenges for digital libraries and digital information access in general

Context Aware Computing for The Internet of Things: A Survey

As we are moving towards the Internet of Things (IoT), the number of sensors deployed around the world is growing at a rapid pace. Market research has shown a significant growth of sensor deployments over the past decade and has predicted a significant increment of the growth rate in the future. These sensors continuously generate enormous amounts of data. However, in order to add value to raw sensor data we need to understand it. Collection, modelling, reasoning, and distribution of context in relation to sensor data plays critical role in this challenge. Context-aware computing has proven to be successful in understanding sensor data. In this paper, we survey context awareness from an IoT perspective. We present the necessary background by introducing the IoT paradigm and context-aware fundamentals at the beginning. Then we provide an in-depth analysis of context life cycle. We evaluate a subset of projects (50) which represent the majority of research and commercial solutions proposed in the field of context-aware computing conducted over the last decade (2001-2011) based on our own taxonomy. Finally, based on our evaluation, we highlight the lessons to be learnt from the past and some possible directions for future research. The survey addresses a broad range of techniques, methods, models, functionalities, systems, applications, and middleware solutions related to context awareness and IoT. Our goal is not only to analyse, compare and consolidate past research work but also to appreciate their findings and discuss their applicability towards the IoT.Comment: IEEE Communications Surveys & Tutorials Journal, 201

A Machine Learning-Based Anomaly Prediction Service for Software-Defined Networks

Software-defined networking (SDN) has gained tremendous growth and can be exploited in different network scenarios, from data centers to wide-area 5G networks. It shifts control logic from the devices to a centralized entity (programmable controller) for efficient traffic monitoring and flow management. A software-based controller enforces rules and policies on the requests sent by forwarding elements; however, it cannot detect anomalous patterns in the network traffic. Due to this, the controller may install the flow rules against the anomalies, reducing the overall network performance. These anomalies may indicate threats to the network and decrease its performance and security. Machine learning (ML) approaches can identify such traffic flow patterns and predict the systems’ impending threats. We propose an ML-based service to predict traffic anomalies for software-defined networks in this work. We first create a large dataset for network traffic by modeling a programmable data center with a signature-based intrusion-detection system. The feature vectors are pre-processed and are constructed against each flow request by the forwarding element. Then, we input the feature vector of each request to a machine learning classifier for training to predict anomalies. Finally, we use the holdout cross-validation technique to evaluate the proposed approach. The evaluation results specify that the proposed approach is highly accurate. In contrast to baseline approaches (random prediction and zero rule), the performance improvement of the proposed approach in average accuracy, precision, recall, and f-measure is (54.14%, 65.30%, 81.63%, and 73.70%) and (4.61%, 11.13%, 9.45%, and 10.29%), respectively

An enhanced dynamic replica creation and eviction mechanism in data grid federation environment

Data Grid Federation system is an infrastructure that connects several grid systems, which facilitates sharing of large amount of data, as well as storage and computing resources. The existing mechanisms on data replication focus on finding file values based on the number of files access in deciding which file to replicate, and place new replicas on locations that provide minimum read cost. DRCEM finds file values based on logical dependencies in deciding which file to replicate, and allocates new replicas on locations that provide minimum replica placement cost. This thesis presents an enhanced data replication strategy known as Dynamic Replica Creation and Eviction Mechanism (DRCEM) that utilizes the usage of data grid resources, by allocating appropriate replica sites around the federation. The proposed mechanism uses three schemes: 1) Dynamic Replica Evaluation and Creation Scheme, 2) Replica Placement Scheme, and 3) Dynamic Replica Eviction Scheme. DRCEM was evaluated using OptorSim network simulator based on four performance metrics: 1) Jobs Completion Times, 2) Effective Network Usage, 3) Storage Element Usage, and 4) Computing Element Usage. DRCEM outperforms ELALW and DRCM mechanisms by 30% and 26%, in terms of Jobs Completion Times. In addition, DRCEM consumes less storage compared to ELALW and DRCM by 42% and 40%. However, DRCEM shows lower performance compared to existing mechanisms regarding Computing Element Usage, due to additional computations of files logical dependencies. Results revealed better jobs completion times with lower resource consumption than existing approaches. This research produces three replication schemes embodied in one mechanism that enhances the performance of Data Grid Federation environment. This has contributed to the enhancement of the existing mechanism, which is capable of deciding to either create or evict more than one file during a particular time. Furthermore, files logical dependencies were integrated into the replica creation scheme to evaluate data files more accurately

An empirical investigation of wood product information valued by young consumers

Recent media reports regarding wood products question the trustworthiness of wood origin declaration, the sustainability of production methods and the product quality. In light of this question, it becomes important to ensure consumer trust in wood and wood-based products. Current research indicates that providing product information enhances product trust and purchase intentions, while young consumers in particular seek detailed product information. However, it is necessary to determine which wood product information young consumers strongly value because providing a high amount leads to information overload. As information needs may vary between different consumer segments, the present work aims at identifying segments of young consumers and their preferred wood-product information. The importance of different wood product information items concerning the purchase decision was investigated with a German-language online survey (N = 185, age range 18–30). A cluster analysis revealed four consumer segments. Thereof, three segments (an environmentally oriented, an environmentally and quality oriented, and a quality oriented segment) valued the provision of wood product information. The preferred information types differed among the three segments. Overall, this paper provides insights into young consumers' preferences for wood product information and the consumer segments on which marketing should focus

Visual approaches to knowledge organization and contextual exploration

This thesis explores possible visual approaches for the representation of semantic structures, such as zz-structures. Some holistic visual representations of complex domains have been investigated through the proposal of new views - the so-called zz-views - that allow both to make visible the interconnections between elements and to support a contextual and multilevel exploration of knowledge. The potential of this approach has been examined in the context of two case studies that have led to the creation of two Web applications. The \ufb01rst domain of study regarded the visual representation, analysis and management of scienti\ufb01c bibliographies. In this context, we modeled a Web application, we called VisualBib, to support researchers in building, re\ufb01ning, analyzing and sharing bibliographies. We adopted a multi-faceted approach integrating features that are typical of three di\ufb00erent classes of tools: bibliography visual analysis systems, bibliographic citation indexes and personal research assistants. The evaluation studies carried out on a \ufb01rst prototype highlighted the positive impact of our visual model and encouraged us to improve it and develop further visual analysis features we incorporated in the version 3.0 of the application. The second case study concerned the modeling and development of a multimedia catalog of Web and mobile applications. The objective was to provide an overview of a significant number of tools that can help teachers in the implementation of active learning approaches supported by technology and in the design of Teaching and Learning Activities (TLAs). We analyzed and documented 281 applications, preparing for each of them a detailed multilingual card and a video-presentation, organizing all the material in an original purpose-based taxonomy, visually represented through a browsable holistic view. The catalog, we called AppInventory, provides contextual exploration mechanisms based on zz-structures, collects user contributions and evaluations about the apps and o\ufb00ers visual analysis tools for the comparison of the applications data and user evaluations. The results of two user studies carried out on groups of teachers and students shown a very positive impact of our proposal in term of graphical layout, semantic structure, navigation mechanisms and usability, also in comparison with two similar catalogs