Resource Discovery Service Research Articles

Research on the Integration of ESP and Big Data in Modern College English Teaching

In the context of big data, it analyzes ESP-based college English teaching. First, it explains the big data theory in ESP, and then discusses the resource discovery service, information storage service, resource organization service, and information retrieval service of English teaching. On the basis of the service content of ESP in college English teaching, it expounds the self-learning mode of college English based on ESP theory from the aspects of one-stop resource service, subject knowledge service, information visualization service and smart service.

A Novel Sensing as a Service Model Based on SSN Ontology and Android Automotive

The automotive sensor technology is advancing rapidly and is actually a vital part of any modern automobile design. These sensors generate a large quantity of data that are exploited to implement intelligent functions in the vehicle (improvement of driving efficiency, safety, convenience, and so on). 5G next-generation networks are expected to meet various communication requirements for vehicles. This will enable the creation of a large market of services with the exploitation of the generated data from in-vehicle sensors. However, with the dynamic nature of vehicular networks and the heterogeneity of in-vehicle sensors data, it is a major challenge for applications/services to meet the 4A vision (anywhere, anytime, by anyone and anything). In this paper, we propose a Sensing as a Service (S2aaS) model based on the novel architecture for the collection and the transformation of in-vehicle sensors data. Sensor semantic network ontology is employed to effectively model heterogeneous sensors data and sensors proprieties. This ontology allows the deployment of vehicle sensing resource discovery service, ranking, and selection of sensing data based on user and application requirements. The proposition of caching and distributed decision-making systems allow the reduction of network overhead and latency compared with others works in the literature. Then, a practical example of the use of the S2aaS is presented. Android automotive architecture with the proposed API and App to support S2aaS is presented at the end of this paper.

An Inductive Content-Augmented Network Embedding Model for Edge Artificial Intelligence

Real-time data processing applications demand dynamic resource provisioning and efficient service discovery, which is particularly challenging in resource-constraint edge computing environments. Network embedding techniques can potentially aid effective resource discovery services in edge environments, by achieving a proximity-preserving representation of the network resources. Most of the existing techniques of network embedding fail to capture accurate proximity information among the network nodes and further lack exploiting information beyond the second-order neighbourhood. This paper leverages artificial intelligence for network representation and proposes a deep learning model, named inductive content augmented network embedding (ICANE), which integrates the network structure and resource content attributes into a feature vector. Secondly, a hierarchical aggregation approach is introduced to explicitly learn the network representation through sampling the nodes and aggregating features from the higher-order neighbourhood. A semantic proximity search model is then designed to generate the top-k ranking of relevant nodes using the learned network representation. Experiments conducted on real-world datasets demonstrate the superiority of the proposed model over the existing popular methods in terms of resource discovery and the query resolving performance.

Designing web-scale discovery systems using the VuFind open source software

PurposeThis paper aims to provide an overview of the emergence of resource discovery systems and services along with their advantages and best practices including current landscapes. It reports the development of a resource discovery system by using the “VuFind” software and describes other technological tools, software, standards and protocols required for the development of the prototype.Design/methodology/approachThis paper describes the process of integrating VuFind (resource discovery tool) with Koha (integrated library system), DSpace (repository software) and Apache Tika (as full-text extractor for full-text searching), etc.FindingsThe proposed model performs like other existing commercial and open source Web-scale resource discovery systems and is capable of harvesting resources from different subscribed or external sources replacing a library’s OPAC.Originality/valueThis discovery system is an important add-on to designing a one-stop access in place of the existing retrieval silos in libraries. This system is capable of indexing a variety of content within and beyond library collections. This work may help library professionals and administrators in designing their discovery system, as well as vendors to improve their products, to provide different library-friendly services.

From Integrated Library System (ILS) to Library Service Platform (LSP): Role of Library Discovery System (LDS)

This paper shows the evolution of the web-scale resource discovery services in libraries along with different discovery software available both in commercial and open source domain. The paper discusses several discovery tools and identifies several key parameters on the basis of which can compare the usability and accessibility of different discovery software. It will be identifies tools possibilities of applications of these interactive, collaborative and participative tools in enhancing existing library services and the feasibility of introducing next generation library services. Therefore, today all world look-over the newly made association which is library discovery system. Library discovery system make a software like 'VuFind' as open source software, digital library software to distributed across the globe.

Edge-Centric Distributed Discovery and Access in the Internet of Things

Massive diffusion of constrained devices communicating through low-power wireless technologies in the future Internet of Things (IoT) will require in many scenarios the deployment of IoT gateways to allow applications to discover and access IoT resources. In this context, Fog/Edge computing will represent an opportunity to deploy IoT gateways in proximity of IoT domains, meeting the requirements of applications needing low-latency interactions with devices. In this paper, we present an edge-centric distributed architecture to provide resource discovery and access services to IoT applications. The proposed approach leverages the CoRE Resource Directory interface and the Constrained Application Protocol (CoAP) to expose a standard interface for global discovery and access. Multiple IoT gateways are federated through a peer-to-peer overlay implemented by a distributed hash table, which is exploited to share the information on IoT resources available across multiple domains. The proposed solution is validated by means of a small-scale prototype, and extensively evaluated through emulation in large scale deployment in comparison to a centralized Cloud-based approach. Experimental results demonstrated that the proposed approach guarantees lower latencies than a centralized solution and can ensure scalability for small to medium sized deployments.

Efficient Opportunistic Overlay Prototype with Reliable Routing and Distributed Resource Discovery Services

Efficient Opportunistic Overlay Prototype with Reliable Routing and Distributed Resource Discovery Services

HARD: Hybrid Adaptive Resource Discovery for Jungle Computing

In recent years, Jungle Computing has emerged as a distributed computing paradigm based on simultaneous combination of various hierarchical and distributed computing environments which are composed by large number of heterogeneous resources. In such a computing environment, the resources and the underlying computation and communication infrastructures are highly-hierarchical and heterogeneous. This creates a lot of difficulty and complexity for finding the proper resources in a precise way in order to run a particular job on the system efficiently. This paper proposes Hybrid Adaptive Resource Discovery (HARD), a novel efficient and highly scalable resource-discovery approach which is built upon a virtual hierarchical overlay based on self-organization and self-adaptation of processing resources in the system, where the computing resources are organized into distributed hierarchies according to a proposed hierarchical multi-layered resource description model. The proposed approach supports distributed query processing within and across hierarchical layers by deploying various distributed resource discovery services and functionalities in the system which are implemented using different adapted algorithms and mechanisms in each level of hierarchy. The proposed approach addresses the requirements for resource discovery in Jungle Computing environments such as high-hierarchy, high-heterogeneity, high-scalability and dynamicity. Simulation results show significant scalability and efficiency of the proposed approach over highly heterogeneous, hierarchical and dynamic computing environments.

A Proximity and Semantic-Aware Optimisation Model for Sub-Domain-Based Decentralised Resource Discovery in Grid Computing

One of the fundamental issues in Grid decentralised resource discovery services is high communication overheads that affect the Grid system’s performance significantly. The rationale is that Grid resources are geographically distributed across the world through a wide area network under various virtual organisations. To address the issue, a significant amount of effort has been made by proposing various decentralised overlay algorithms with semantic solutions. Current Grid literature reveals that when semantic features are added into discovery services, the probability of finding resources is enhanced and communication overheads could be better. However, most of the existing decentralised resource discovery models utilise a domain-based semantic ontology with First Come First Serve (FCFS) basis scheduling for allocating Grid resources that can cause job rejection at run time and can pick resources that are far from the user nodes. As a result, communication overheads of the models are affected as the proximity criterion is not being considered in the selection process. To overcome these issues and enhance the application performance, we propose a Unification of Proximity and Semantic similarity for Appropriate Resource Selection (UPSARS) algorithm in a decentralised resource discovery model by using a sub-domain ontology structure for Grid computing environments. The purpose of this unification is to get optimised resources for user jobs (Gridlets) so that Grid brokers could select optimum resources in terms of proximity with high semantic relevancy. The algorithm considers both semantic and proximity criteria and selects the nearby nodes resources and reduces the communication overheads in terms of proximity and latency. We design and implement the model using the GridSim and the FreePastry simulation and modelling toolkits. The experimental results provide promising outcomes to reduce communication overheads and enhance resource allocation performance.

The Impact of RDS on Usage of Electronic Content in UK Academic Libraries: Selected Results from a UKSG-Funded Project

Resource discovery services (RDS), also called web-scale discovery services (WDS), have attracted considerable attention in recent years. This article aims to provide an environmental scan of the adoption of RDS in UK higher education libraries and provide an analysis of RDS resource usage data to gauge whether RDS have an impact on the overall usage of ejournals and ebooks. Findings show that there appears to be a positive impact in most cases, although the extent of this impact varies across libraries and publishers. There is undeniably a degree of complexity in the usage analysis owing to the multidimensional nature of the environment.

Die Öffnung der digitalen Magazinbibliothek

Zusammenfassung: Dieser Artikel beschreibt zunächst die Erfahrungen der Universität Konstanz mit Summon als Discovery-Service. Summon wurde im Jahr 2011 als „KonSearch – die Literatursuchmaschine der Universität Konstanz“ eingeführt. Seitdem stiegen die Nutzung und die Akzeptanz dauerhaft an. Im gleichen Jahr wurde an der Universität Konstanz das Projekt Blended Library gestartet. Innerhalb dieses Projekts wurden mehrere Ideen zur Verbindung von gedrucktem und digitalem Bestand und dem Ort Bibliothek entwickelt. Dies führte zum sogenannten Hybrid Bookshelf, das derzeit entwickelt wird.

Evaluation of a Resource Discovery Service: FindIt@Bham

In autumn 2012, the University of Birmingham launched FindIt@Bham, a Primo-based Resource Discovery Service, after a series of focus groups with students and staff to help determine its initial configuration and customization. This article presents the results from a large-scale online survey and focus groups that were conducted to poll users’ attitudes to the service over twelve months later, adding to a small body of research on user satisfaction with established resource discovery services. From the survey the overall level of appreciation was high with 71.13% rating FindIt@Bham to be “Good” or “Very Good.” The level of appreciation was compared across undergraduates, postgraduates (taught and research), and academic staff which revealed that undergraduates are the group of users most happy with the service with academic staff being least satisfied. The reasons for this discrepancy are considered, along with users’ behavior and a discussion of their perceptions of individual functional areas. The survey results led to focus group activities tailored to extract deeper information on system usage and satisfaction. From these combined activities, future customizations and developments to FindIt@Bham such as tuning of result relevancy, improved online help, and additional functionality can be prioritized.

Terminology registries for knowledge organization systems: Functionality, use, and attributes

Terminology registries (TRs) are a crucial element of the infrastructure required for resource discovery services, digital libraries, Linked Data, and semantic interoperability generally. They can make the content of knowledge organization systems (KOS) available both for human and machine access. The paper describes the attributes and functionality for a TR, based on a review of published literature, existing TRs, and a survey of experts. A domain model based on user tasks is constructed and a set of core metadata elements for use in TRs is proposed. Ideally, the TR should allow searching as well as browsing for a KOS, matching a user's search while also providing information about existing terminology services, accessible to both humans and machines. The issues surrounding metadata for KOS are also discussed, together with the rationale for different aspects and the importance of a core set of KOS metadata for future machine‐based access; a possible core set of metadata elements is proposed. This is dealt with in terms of practical experience and in relation to the Dublin Core Application Profile.

Direction-aware resource discovery in large-scale distributed computing environments

As a system scales up, the peer-to-peer (P2P) approach is attractive to distributed computing environments, such as Grids and Clouds, due to the amount of resources increased. The major issue in large-scale distributed systems is to prevent the phenomenon of a communication bottleneck or a single point of failure. Conventional approaches may not be able to apply directly to such environments due to restricted queries and varied resource characteristics. Alternatively, a fully decentralized resource discovery service based on an unstructured overlay, which relies only on the information of resource attributes and characteristics, may be a feasible solution. One major challenge of such service is to locate desired and suitable resources without the global knowledge of distributed sharing resources. As a consequence, the more nodes the resource discovery service involves, the higher the network overhead incurs. In this paper, we proposed a direction-aware strategy which can alleviate the network traffic among unstructured information systems for distributed resource discovery service. Experimental results have demonstrated that the proposed approach achieves higher success rate at low cost and higher scalability.

The Arizona Universities Library Consortium patron-driven e-book model

Building on Arizona State University's patron-driven acquisitions (PDA) initiative in 2009, the Arizona Universities Library Consortium, in partnership with the Ingram Content Group, created a cooperative patron-driven model to acquire electronic books (e-books). The model provides the opportunity for faculty and students at the universities governed by the Arizona Board of Regents (ABOR) to access a core of e-books made accessible through resource discovery services and online catalogs. These books are available for significantly less than a single ABOR university would expend for the same materials. The patron-driven model described is one of many evolving models in digital scholarship, and, although the Arizona Universities Library Consortium reports a successful experience, patron-driven models pose questions to stakeholders in the academic publishing industry.

DISTRIBUTED AND BIG DATA STORAGE MANAGEMENT IN GRID COMPUTING

Big data storage management is one of the most challenging issues for Grid computing environments, since large amount of data intensive applications frequently involve a high degree of data access locality. Grid applications typically deal with large amounts of data. In traditional approaches high-performance computing consists dedicated servers that are used to data storage and data replication. In this paper we present a new mechanism for distributed and big data storage and resource discovery services. Here we proposed an architecture named Dynamic and Scalable Storage Management (DSSM) architecture in grid environments. This allows in grid computing not only sharing the computational cycles, but also share the storage space. The storage can be transparently accessed from any grid machine, allowing easy data sharing among grid users and applications. The concept of virtual ids that, allows the creation of virtual spaces has been introduced and used. The DSSM divides all Grid Oriented Storage devices (nodes) into multiple geographically distributed domains and to facilitate the locality and simplify the intra-domain storage management. Grid service based storage resources are adopted to stack simple modular service piece by piece as demand grows. To this end, we propose four axes that define: DSSM architecture and algorithms description, Storage resources and resource discovery into Grid service, Evaluate purpose prototype system, dynamically, scalability, and bandwidth, and Discuss results. Algorithms at bottom and upper level for standardization dynamic and scalable storage management, along with higher bandwidths have been designed.

Distributed and Big Data Storage Management in Grid Computing

Big data storage management is one of the most challenging issues for Grid computing environments, since large amount of data intensive applications frequently involve a high degree of data access locality. Grid applications typically deal with large amounts of data. In traditional approaches high-performance computing consists dedicated servers that are used to data storage and data replication. In this paper we present a new mechanism for distributed and big data storage and resource discovery services. Here we proposed an architecture named Dynamic and Scalable Storage Management (DSSM) architecture in grid environments. This allows in grid computing not only sharing the computational cycles, but also share the storage space. The storage can be transparently accessed from any grid machine, allowing easy data sharing among grid users and applications. The concept of virtual ids that, allows the creation of virtual spaces has been introduced and used. The DSSM divides all Grid Oriented Storage devices (nodes) into multiple geographically distributed domains and to facilitate the locality and simplify the intra-domain storage management. Grid service based storage resources are adopted to stack simple modular service piece by piece as demand grows. To this end, we propose four axes that define: DSSM architecture and algorithms description, Storage resources and resource discovery into Grid service, Evaluate purpose prototype system, dynamically, scalability, and bandwidth, and Discuss results. Algorithms at bottom and upper level for standardization dynamic and scalable storage management, along with higher bandwidths have been designed.

Gossiping for resource discovering: An analysis based on complex network theory

This paper analyzes the adoption of unstructured P2P overlay networks to build resource discovery services. We consider a simple distributed communication protocol, which is based on gossip and on the local knowledge each node has about resources hold by its neighbors. In particular, upon reception (or generation) of a novel query, a node relays the message to those neighbors that have resources whose profile matches the query. Moreover, the node gossips the query to other remaining neighbors, so that the query can be disseminated through the overlay. A mathematical analysis is provided to estimate the number of nodes receiving the query (and consequently, the portion of query hits), based on the network topology, resource availability and gossip probability. Results show that the use of unstructured networks, coupled with simple dissemination protocols, represent a viable approach to build P2P resource discovery systems.

A Novel P2P Based Grid Resource Discovery Model

Resource discovery is a fundamental problem in grid systems. Original approaches to provide grid resource discovery services are either centralized or hierarchical and proved to be inefficient when the scale of grid systems rapidly increases. A P2P network is a distributed system with the attributes of dynamicity and scalability. P2P systems have the same goal as grid systems: to share and exchange various resources. With their development, P2P systems and grid systems can be combined into a new system which has their attributes. In this paper, a novel hierarchical P2P based grid model based on the existing grid resource discovery models is discussed. In our model, Chord and Gnutella are selected as the typical protocols to form the virtual P2P layer. Through the experiment results, we argue that the 3C-2G model performs better than the other models in resource discovery among grids oriented to the same application field.

Key Issue <br>Discovery services: next generation of searching scholarly information

The new breed of resource discovery services is an evolutionary step forward in providing library users with a ‘one-stop shop’ where they can find information sources for their research. They provide a single search box that can search a library’s online and physical content including articles, books, journals, newspaper articles, e-books, specialist collections and more. These discovery services have built on the concepts of both federated searching and next-generation catalogues (described briefly below).