Grid-based semantic integration of heterogeneous data resources: Implementation on a HealthGrid

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel University.The semantic integration of geographically distributed and heterogeneous data resources still remains a key challenge in Grid infrastructures. Today's mainstream Grid technologies hold the promise to meet this challenge in a systematic manner, making data applications more scalable and manageable. The thesis conducts a thorough investigation of the problem, the state of the art, and the related technologies, and proposes an Architecture for Semantic Integration of Data Sources (ASIDS) addressing the semantic heterogeneity issue. It defines a simple mechanism for the interoperability of heterogeneous data sources in order to extract or discover information regardless of their different semantics. The constituent technologies of this architecture include Globus Toolkit (GT4) and OGSA-DAI (Open Grid Service Architecture Data Integration and Access) alongside other web services technologies such as XML (Extensive Markup Language). To show this, the ASIDS architecture was implemented and tested in a realistic setting by building an exemplar application prototype on a HealthGrid (pilot implementation). The study followed an empirical research methodology and was informed by extensive literature surveys and a critical analysis of the relevant technologies and their synergies. The two literature reviews, together with the analysis of the technology background, have provided a good overview of the current Grid and HealthGrid landscape, produced some valuable taxonomies, explored new paths by integrating technologies, and more importantly illuminated the problem and guided the research process towards a promising solution. Yet the primary contribution of this research is an approach that uses contemporary Grid technologies for integrating heterogeneous data resources that have semantically different. data fields (attributes). It has been practically demonstrated (using a prototype HealthGrid) that discovery in semantically integrated distributed data sources can be feasible by using mainstream Grid technologies, which have been shown to have some Significant advantages over non-Grid based approaches

Requirements of the SALTY project

This document is the first external deliverable of the SALTY project (Self-Adaptive very Large disTributed sYstems), funded by the ANR under contract ANR-09-SEGI-012. It is the result of task 1.1 of the Work Package (WP) 1 : Requirements and Architecture. Its objective is to identify and collect requirements from use cases that are going to be developed in WP 4 (Use cases and Validation). Based on the study and classification of the use cases, requirements against the envisaged framework are then determined and organized in features. These features will aim at guide and control the advances in all work packages of the project. As a start, features are classified, briefly described and related scenarios in the defined use cases are pinpointed. In the following tasks and deliverables, these features will facilitate design by assigning priorities to them and defining success criteria at a finer grain as the project progresses. This report, as the first external document, has no dependency to any other external documents and serves as a reference to future external documents. As it has been built from the use cases studies that have been synthesized in two internal documents of the project, extracts from the two documents are made available as appendices (cf. appen- dices B and C)

A survey on cost-effective context-aware distribution of social data streams over energy-efficient data centres

Social media have emerged in the last decade as a viable and ubiquitous means of communication. The ease of user content generation within these platforms, e.g. check-in information, multimedia data, etc., along with the proliferation of Global Positioning System (GPS)-enabled, always-connected capture devices lead to data streams of unprecedented amount and a radical change in information sharing. Social data streams raise a variety of practical challenges, including derivation of real-time meaningful insights from effectively gathered social information, as well as a paradigm shift for content distribution with the leverage of contextual data associated with user preferences, geographical characteristics and devices in general. In this article we present a comprehensive survey that outlines the state-of-the-art situation and organizes challenges concerning social media streams and the infrastructure of the data centres supporting the efficient access to data streams in terms of content distribution, data diffusion, data replication, energy efficiency and network infrastructure. We systematize the existing literature and proceed to identify and analyse the main research points and industrial efforts in the area as far as modelling, simulation and performance evaluation are concerned

Evolving a secure grid-enabled, distributed data warehouse : a standards-based perspective

As digital data-collection has increased in scale and number, it becomes an important type of resource serving a wide community of researchers. Cross-institutional data-sharing and collaboration introduce a suitable approach to facilitate those research institutions that are suffering the lack of data and related IT infrastructures. Grid computing has become a widely adopted approach to enable cross-institutional resource-sharing and collaboration. It integrates a distributed and heterogeneous collection of locally managed users and resources. This project proposes a distributed data warehouse system, which uses Grid technology to enable data-access and integration, and collaborative operations across multi-distributed institutions in the context of HV/AIDS research. This study is based on wider research into OGSA-based Grid services architecture, comprising a data-analysis system which utilizes a data warehouse, data marts, and near-line operational database that are hosted by distributed institutions. Within this framework, specific patterns for collaboration, interoperability, resource virtualization and security are included. The heterogeneous and dynamic nature of the Grid environment introduces a number of security challenges. This study also concerns a set of particular security aspects, including PKI-based authentication, single sign-on, dynamic delegation, and attribute-based authorization. These mechanisms, as supported by the Globus Toolkit’s Grid Security Infrastructure, are used to enable interoperability and establish trust relationship between various security mechanisms and policies within different institutions; manage credentials; and ensure secure interactions

Grid-based semantic integration of heterogeneous data resources : implementation on a HealthGrid

The semantic integration of geographically distributed and heterogeneous data resources still remains a key challenge in Grid infrastructures. Today's mainstream Grid technologies hold the promise to meet this challenge in a systematic manner, making data applications more scalable and manageable. The thesis conducts a thorough investigation of the problem, the state of the art, and the related technologies, and proposes an Architecture for Semantic Integration of Data Sources (ASIDS) addressing the semantic heterogeneity issue. It defines a simple mechanism for the interoperability of heterogeneous data sources in order to extract or discover information regardless of their different semantics. The constituent technologies of this architecture include Globus Toolkit (GT4) and OGSA-DAI (Open Grid Service Architecture Data Integration and Access) alongside other web services technologies such as XML (Extensive Markup Language). To show this, the ASIDS architecture was implemented and tested in a realistic setting by building an exemplar application prototype on a HealthGrid (pilot implementation). The study followed an empirical research methodology and was informed by extensive literature surveys and a critical analysis of the relevant technologies and their synergies. The two literature reviews, together with the analysis of the technology background, have provided a good overview of the current Grid and HealthGrid landscape, produced some valuable taxonomies, explored new paths by integrating technologies, and more importantly illuminated the problem and guided the research process towards a promising solution. Yet the primary contribution of this research is an approach that uses contemporary Grid technologies for integrating heterogeneous data resources that have semantically different. data fields (attributes). It has been practically demonstrated (using a prototype HealthGrid) that discovery in semantically integrated distributed data sources can be feasible by using mainstream Grid technologies, which have been shown to have some Significant advantages over non-Grid based approaches.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Distributed Management of Grid-based Scientific Workflows

Grids and service-oriented technologies are emerging as dominant approaches for distributed systems. With the evolution of these technologies, scientific workflows have been introduced as a tool for scientists to assemble highly specialized applications, and to exchange large heterogeneous datasets in order to automate and accelerate the accomplishment of complex scientific tasks. Several Scientific Workflow Management Systems (SWfMS) have already been designed to support the specification, execution, and monitoring of scientific workflows. Meanwhile, they still face key challenges from two different perspectives: system usability and system efficiency. From the system usability perspective, current SWfMS are not designed to be simple enough for scientists who have quite limited IT knowledge. What’s more, there is no easy mechanism by which scientists can share and re-use scientific experiments that have already been designed and proved by others. From the perspective of system efficiency, existing SWfMS are coordinating and executing workflows in a centralized fashion using a single scheduler and / or a workflow enactor. This creates a single point of failure, forms a scalability bottleneck, and enforces centralized fault handling. In addition, they don’t consider load balancing while mapping abstract jobs onto several computational nodes. Another important challenge exists due to the common nature of scientific workflow applications, that need to exchange a huge amount of data during the execution process. Some available SWfMS use a mediator-based approach for data transfer where data must be transferred first to a centralized data manager, which is completely inefficient. Other SWfMS apply a peer-to-peer approach via data references. Even this approach is not sufficient for scientific workflows as a single complex scientific activity can produce an extensive amount of data. In this thesis, we introduce SWIMS (Scientific Workflow Integration and Management System) framework. It employs the Web Services technology to originate a distributed management system for data-intensive scientific workflows. The purpose of SWIMS is to overcome the previously mentioned challenges through a set of salient features: i) Support for distributed execution and management of workflows, ii) diminution of communication traffic, iii) support for smart re-run, iv) distributed fault handling and load balancing, v) ease of use, and vi) extensive sharing of scientific workflows. We discuss the motivation, design, and implementation of the SWIMS framework. Then, we evaluate it through the Montage application from the astronomy domain

Integrated System for Control and Monitoring Industrial Wireless Networks for Labour Risk Prevention

The FASyS (Absolutely Safe and Healthy Factory) project, aligned with the European Factories of the Future (FoF) concept, has been set-up to develop a new factory model aimed at minimizing the risks to the worker's health and safety, and guarantee their welfare and comfort in machining, handling and assembly factories. To this aim, ICT (Information and Communication Technologies) and wireless communication technologies in particular may represent very valuable tools to implement distributed and mobile sensing applications capable to continuously sense the working environment and the workers' health and safety conditions. The effective deployment of such applications in critical environments, like the industrial one, require the availability of a platform capable to monitor the operation and performance of the heterogeneous wireless networks that will connect the mobile sensors to remote control centers. This paper presents the platform implemented for this purpose in the context of the FASyS project. In addition to monitoring the status of heterogeneous wireless networks, the implemented platform provides the capability to reconfigure remotely the communication settings of wireless nodes based on possible malfunctioning or QoS degradation notifications. These functionalities will help guaranteeing the reliable and robust wireless communications required in industrial environments to implement innovative labor risk prevention applications exploiting ICT technologie

Towards Efficient and Scalable Data-Intensive Content Delivery: State-of-the-Art, Issues and Challenges

This chapter presents the authors’ work for the Case Study entitled “Delivering Social Media with Scalability” within the framework of High-Performance Modelling and Simulation for Big Data Applications (cHiPSet) COST Action 1406. We identify some core research areas and give an outline of the publications we came up within the framework of the aforementioned action. The ease of user content generation within social media platforms, e.g. check-in information, multimedia data, etc., along with the proliferation of Global Positioning System (GPS)-enabled, always-connected capture devices lead to data streams of unprecedented amount and a radical change in information sharing. Social data streams raise a variety of practical challenges: derivation of real-time meaningful insights from effectively gathered social information, a paradigm shift for content distribution with the leverage of contextual data associated with user preferences, geographical characteristics and devices in general, etc. In this article we present the methodology we followed, the results of our work and the outline of a comprehensive survey, that depicts the state-of-the-art situation and organizes challenges concerning social media streams and the infrastructure of the data centers supporting the efficient access to data streams in terms of content distribution, data diffusion, data replication, energy efficiency and network infrastructure. The challenges of enabling better provisioning of social media data have been identified and they were based on the context of users accessing these resources. The existing literature has been systematized and the main research points and industrial efforts in the area were identified and analyzed. In our works, in the framework of the Action, we came up with potential solutions addressing the problems of the area and described how these fit in the general ecosystem

Uncertainty in service provisioning relationships

Web services encapsulate some well-defined functionality such as data storage, computation or a business process. An organization can delegate responsibility for the provision of a Web service to another organization with the formation of a Service Provisioning Relationship (SPR). Such relationships enable organizations to specialize in the provision of those Web services for which they have a comparative advantage, and to outsource responsibility for any other functionality on which they are dependent to the Web services provided by other organizations. This specialization can lead to significant increases in organizational efficiency. The scale of such increases is determined by the extent to which the presence of uncertainty in the Quality of Service (QoS) can be addressed by the organizations in the SPR. The requester of a Web service can be uncertain of the willingness and ability of the provider to provision a Web service with a certain QoS. The provider of a Web service can be uncertain of his ability to provision a Web service to each requester with a certain QoS. These uncertainties can endanger the economic viability of such relationships, and mitigate any increases in organizational efficiency. This thesis provides a number of key contributions to address these uncertainties in order to retain the economic viability of these relationships for both organizations. The key contributions are: an institutional framework for trust in SPRs, a structured language for the representation of a Service Level Agreement (SLA) as a contingent contract, and a theoretical and practical methodology for the creation of SLAs which are optimal with regard to the objectives of an organization.EThOS - Electronic Theses Online ServiceEPSRCGBUnited Kingdo