Research and development of accounting system in grid environment

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.The Grid has been recognised as the next-generation distributed computing paradigm by seamlessly integrating heterogeneous resources across administrative domains as a single virtual system. There are an increasing number of scientific and business projects that employ Grid computing technologies for large-scale resource sharing and collaborations. Early adoptions of Grid computing technologies have custom middleware implemented to bridge gaps between heterogeneous computing backbones. These custom solutions form the basis to the emerging Open Grid Service Architecture (OGSA), which aims at addressing common concerns of Grid systems by defining a set of interoperable and reusable Grid services. One of common concerns as defined in OGSA is the Grid accounting service. The main objective of the Grid accounting service is to ensure resources to be shared within a Grid environment in an accountable manner by metering and logging accurate resource usage information. This thesis discusses the origins and fundamentals of Grid computing and accounting service in the context of OGSA profile. A prototype was developed and evaluated based on OGSA accounting-related standards enabling sharing accounting data in a multi-Grid environment, the World-wide Large Hadron Collider Grid (WLCG). Based on this prototype and lessons learned, a generic middleware solution was also implemented as a toolkit that eases migration of existing accounting system to be standard compatible.Engineering and Physical Sciences Research Council (EPSRC), Stanford Universit

E-infrastructures fostering multi-centre collaborative research into the intensive care management of patients with brain injury

Clinical research is becoming ever more collaborative with multi-centre trials now a common practice. With this in mind, never has it been more important to have secure access to data and, in so doing, tackle the challenges of inter-organisational data access and usage. This is especially the case for research conducted within the brain injury domain due to the complicated multi-trauma nature of the disease with its associated complex collation of time-series data of varying resolution and quality. It is now widely accepted that advances in treatment within this group of patients will only be delivered if the technical infrastructures underpinning the collection and validation of multi-centre research data for clinical trials is improved. In recognition of this need, IT-based multi-centre e-Infrastructures such as the Brain Monitoring with Information Technology group (BrainIT - www.brainit.org) and Cooperative Study on Brain Injury Depolarisations (COSBID - www.cosbid.de) have been formed. A serious impediment to the effective implementation of these networks is access to the know-how and experience needed to install, deploy and manage security-oriented middleware systems that provide secure access to distributed hospital based datasets and especially the linkage of these data sets across sites. The recently funded EU framework VII ICT project Advanced Arterial Hypotension Adverse Event prediction through a Novel Bayesian Neural Network (AVERT-IT) is focused upon tackling these challenges. This chapter describes the problems inherent to data collection within the brain injury medical domain, the current IT-based solutions designed to address these problems and how they perform in practice. We outline how the authors have collaborated towards developing Grid solutions to address the major technical issues. Towards this end we describe a prototype solution which ultimately formed the basis for the AVERT-IT project. We describe the design of the underlying Grid infrastructure for AVERT-IT and how it will be used to produce novel approaches to data collection, data validation and clinical trial design is also presented

Research and development of accounting system in grid environment

The Grid has been recognised as the next-generation distributed computing paradigm by seamlessly integrating heterogeneous resources across administrative domains as a single virtual system. There are an increasing number of scientific and business projects that employ Grid computing technologies for large-scale resource sharing and collaborations. Early adoptions of Grid computing technologies have custom middleware implemented to bridge gaps between heterogeneous computing backbones. These custom solutions form the basis to the emerging Open Grid Service Architecture (OGSA), which aims at addressing common concerns of Grid systems by defining a set of interoperable and reusable Grid services. One of common concerns as defined in OGSA is the Grid accounting service. The main objective of the Grid accounting service is to ensure resources to be shared within a Grid environment in an accountable manner by metering and logging accurate resource usage information. This thesis discusses the origins and fundamentals of Grid computing and accounting service in the context of OGSA profile. A prototype was developed and evaluated based on OGSA accounting-related standards enabling sharing accounting data in a multi-Grid environment, the World-wide Large Hadron Collider Grid (WLCG). Based on this prototype and lessons learned, a generic middleware solution was also implemented as a toolkit that eases migration of existing accounting system to be standard compatible.EThOS - Electronic Theses Online ServiceEngineering and Physical Sciences Research Council (EPSRC)Stanford UniversityGBUnited Kingdo

DE-FG02-04ER25606 Identity Federation and Policy Management Guide: Final Report

The goal of this 3-year project was to facilitate a more productive dynamic matching between resource providers and resource consumers in Grid environments by explicitly specifying policies. There were broadly two problems being addressed by this project. First, there was a lack of an Open Grid Services Architecture (OGSA)-compliant mechanism for expressing, storing and retrieving user policies and Virtual Organization (VO) policies. Second, there was a lack of tools to resolve and enforce policies in the Open Services Grid Architecture. To address these problems, our overall approach in this project was to make all policies explicit (e.g., virtual organization policies, resource provider policies, resource consumer policies), thereby facilitating policy matching and policy negotiation. Policies defined on a per-user basis were created, held, and updated in MyPolMan, thereby providing a Grid user to centralize (where appropriate) and manage his/her policies. Organizationally, the corresponding service was VOPolMan, in which the policies of the Virtual Organization are expressed, managed, and dynamically consulted. Overall, we successfully defined, prototyped, and evaluated policy-based resource management and access control for OGSA-based Grids. This DOE project partially supported 17 peer-reviewed publications on a number of different topics: General security for Grids, credential management, Web services/OGSA/OGSI, policy-based grid authorization (for remote execution and for access to information), policy-directed Grid data movement/placement, policies for large-scale virtual organizations, and large-scale policy-aware grid architectures. In addition to supporting the PI, this project partially supported the training of 5 PhD students

Reference installation for the German grid initiative D-Grid

The D-Grid reference installation is a test platform for the German grid initiative. The main task is to create the grid prototype for software and hardware components needed in the D-Grid community. For each grid-related task field different alternative middleware is included. With respect to changing demands from the community, new versions of the reference installation are released every six months

Science 2.0 : sharing scientific data on the Grid

Mestrado em Engenharia de Computadores e TelemáticaA computação assumese cada vez mais como um recurso essencial em ciência, levando ao surgimento do termo eCiência para designar a utilização de tecnologias de computação avançada para suportar a realização de experiências científicas, a preservação e partilha do conhecimento. Uma das áreas de aplicação do conceito de eCiência é o tratamento e análise de imagens médicas. Os processos que lidam com imagem médica, tanto ao nível clínico como de investigação, são exigentes em relação ao suporte computacional, devido aos algoritmos de processamento de imagem que requerem e à elevada capacidade de armazenamento relacionada com volume das imagens geradas. As políticas públicas e os avanços tecnológicos recentes orientados para a eCiência, têm vindo a apoiar o desenvolvimento da computação em Grid, tanto a nível dos middlewares como da instalação de capacidade de produção, como um sistema de computação avançado que permite a partilha de recursos, instrumentos científicos e boas práticas em comunidades virtuais. Este trabalho tem como objectivo desenvolver uma estratégia e um protótipo para o armazenamento de dados médicos na Grid, visando a sua utilização em investigação. Uma preocupação diferenciadora prendese com o objectivo de colocar as potencialidades da Grid ao serviço de utilizadores não técnicos (e.g. médicos, investigadores), que acedem a serviços de processamento e de armazenamento e catalogação de dados de forma transparente, através de um portal Web. O protótipo desenvolvido permite a investigadores na área das neurociências, sem conhecimentos específicos da tecnologia Grid, armazenar imagens e analisálas em Grids de produção existentes, baseadas no middleware gLite. ABSTRACT: Computing has become an essential tool in modern science, leading to the appearance of the term eScience to designate the usage of advanced computing technologies to support the execution of scientific experiments, and the preservation and sharing of knowledge. One of eScience domain areas is the medical imaging analysis. The processes that deal with medical images, both at clinical and investigation level, are very demanding in terms of computational support, due to the analysis algorithms that involve large volumes of generated images, requiring high storage capabilities. The recent public policies and technological advances are eScience oriented, and have been supporting the development of Grid computing, both at the middleware level and at the installation of production capabilities in an advanced computing system, that allows the sharing of resources, scientific instrumentation and good practices among virtual communities. The main objective of this work is to develop a strategy and a prototype to allow the storage of medical data on the Grid, targeting a research environment. The differentiating concern of this work is the ability to provide the nonexperts users (e.g: doctors, researchers) access to the Grid services, like storage and processing, through a friendly Web interface. The developed prototype allows researchers in the field of neuroscience, without any specific knowledge of Grid technology, to store images and analyse them in production Grid infrastructures, based on the gLite middleware

A FRAMEWORK FOR BIOPROFILE ANALYSIS OVER GRID

An important trend in modern medicine is towards individualisation of healthcare to tailor care to the needs of the individual. This makes it possible, for example, to personalise diagnosis and treatment to improve outcome. However, the benefits of this can only be fully realised if healthcare and ICT resources are exploited (e.g. to provide access to relevant data, analysis algorithms, knowledge and expertise). Potentially, grid can play an important role in this by allowing sharing of resources and expertise to improve the quality of care. The integration of grid and the new concept of bioprofile represents a new topic in the healthgrid for individualisation of healthcare. A bioprofile represents a personal dynamic "fingerprint" that fuses together a person's current and past bio-history, biopatterns and prognosis. It combines not just data, but also analysis and predictions of future or likely susceptibility to disease, such as brain diseases and cancer. The creation and use of bioprofile require the support of a number of healthcare and ICT technologies and techniques, such as medical imaging and electrophysiology and related facilities, analysis tools, data storage and computation clusters. The need to share clinical data, storage and computation resources between different bioprofile centres creates not only local problems, but also global problems. Existing ICT technologies are inappropriate for bioprofiling because of the difficulties in the use and management of heterogeneous IT resources at different bioprofile centres. Grid as an emerging resource sharing concept fulfils the needs of bioprofile in several aspects, including discovery, access, monitoring and allocation of distributed bioprofile databases, computation resoiuces, bioprofile knowledge bases, etc. However, the challenge of how to integrate the grid and bioprofile technologies together in order to offer an advanced distributed bioprofile environment to support individualized healthcare remains. The aim of this project is to develop a framework for one of the key meta-level bioprofile applications: bioprofile analysis over grid to support individualised healthcare. Bioprofile analysis is a critical part of bioprofiling (i.e. the creation, use and update of bioprofiles). Analysis makes it possible, for example, to extract markers from data for diagnosis and to assess individual's health status. The framework provides a basis for a "grid-based" solution to the challenge of "distributed bioprofile analysis" in bioprofiling. The main contributions of the thesis are fourfold: A. An architecture for bioprofile analysis over grid. The design of a suitable aichitecture is fundamental to the development of any ICT systems. The architecture creates a meaiis for categorisation, determination and organisation of core grid components to support the development and use of grid for bioprofile analysis; B. A service model for bioprofile analysis over grid. The service model proposes a service design principle, a service architecture for bioprofile analysis over grid, and a distributed EEG analysis service model. The service design principle addresses the main service design considerations behind the service model, in the aspects of usability, flexibility, extensibility, reusability, etc. The service architecture identifies the main categories of services and outlines an approach in organising services to realise certain functionalities required by distributed bioprofile analysis applications. The EEG analysis service model demonstrates the utilisation and development of services to enable bioprofile analysis over grid; C. Two grid test-beds and a practical implementation of EEG analysis over grid. The two grid test-beds: the BIOPATTERN grid and PlymGRID are built based on existing grid middleware tools. They provide essential experimental platforms for research in bioprofiling over grid. The work here demonstrates how resources, grid middleware and services can be utilised, organised and implemented to support distributed EEG analysis for early detection of dementia. The distributed Electroencephalography (EEG) analysis environment can be used to support a variety of research activities in EEG analysis; D. A scheme for organising multiple (heterogeneous) descriptions of individual grid entities for knowledge representation of grid. The scheme solves the compatibility and adaptability problems in managing heterogeneous descriptions (i.e. descriptions using different languages and schemas/ontologies) for collaborated representation of a grid environment in different scales. It underpins the concept of bioprofile analysis over grid in the aspect of knowledge-based global coordination between components of bioprofile analysis over grid