169,457 research outputs found
Resource Management Services for a Grid Analysis Environment
Selecting optimal resources for submitting jobs on a computational Grid or
accessing data from a data grid is one of the most important tasks of any Grid
middleware. Most modern Grid software today satisfies this responsibility and
gives a best-effort performance to solve this problem. Almost all decisions
regarding scheduling and data access are made by the software automatically,
giving users little or no control over the entire process. To solve this
problem, a more interactive set of services and middleware is desired that
provides users more information about Grid weather, and gives them more control
over the decision making process. This paper presents a set of services that
have been developed to provide more interactive resource management
capabilities within the Grid Analysis Environment (GAE) being developed
collaboratively by Caltech, NUST and several other institutes. These include a
steering service, a job monitoring service and an estimator service that have
been designed and written using a common Grid-enabled Web Services framework
named Clarens. The paper also presents a performance analysis of the developed
services to show that they have indeed resulted in a more interactive and
powerful system for user-centric Grid-enabled physics analysis.Comment: 8 pages, 7 figures. Workshop on Web and Grid Services for Scientific
Data Analysis at the Int Conf on Parallel Processing (ICPP05). Norway June
200
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
Role-Based Access Control for the Open Grid Services Architecture - Data Access and Integration (OGSA-DAI)
Grid has emerged recently as an integration infrastructure for the sharing and coordinated use of diverse resources in dynamic, distributed virtual organizations (VOs). A Data Grid is an architecture for the access, exchange, and sharing of data in the Grid environment. In this dissertation, role-based access control (RBAC) systems for heterogeneous data resources in Data Grid systems are proposed. The Open Grid Services Architecture - Data Access and Integration (OGSA-DAI) is a widely used framework for the integration of heterogeneous data resources in Grid systems.
However, in the OGSA-DAI system, access control causes substantial administration overhead for resource providers in VOs because each of them has to manage the authorization information for individual Grid users. Its identity-based access control mechanisms are severely inefficient and too complicated to manage because the direct mapping between users and privileges is transitory. To solve this problem, (1) the Community Authorization Service (CAS), provided by the Globus toolkit, and (2) the Shibboleth, an attribute authorization service, are used to support RBAC in the OGSA-DAI system. The Globus Toolkit is widely used software for building Grid systems.
Access control policies need to be specified and managed across multiple VOs. For this purpose, the Core and Hierarchical RBAC profile of the eXtensible Access Control Markup Language (XACML) is used; and for distributed administration of those policies, the Object, Metadata and Artifacts Registry (OMAR) is used. OMAR is based on the e-business eXtensible Markup Language (ebXML) registry specifications developed to achieve interoperable registries and repositories.
The RBAC systems allow quick and easy deployments, privacy protection, and the centralized and distributed management of privileges. They support scalable, interoperable and fine-grain access control services; dynamic delegation of rights; and user-role assignments. They also reduce the administration overheads for resource providers because they need to maintain only the mapping information from VO roles to local database roles. Resource providers maintain the ultimate authority over their resources. Moreover, unnecessary mapping and connections can be avoided by denying invalid requests at the VO level. Performance analysis shows that our RBAC systems add only a small overhead to the existing security infrastructure of OGSA-DAI
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Business Grid Services
Grid services have come to represent the synthesis of web services and grid computing paradigms. Web services provide the means to modularize software, enabling loosely coupled and novel synthesis. Grid computing removes the binding between functional software components and specific hosting hardware, enabling software to be deployed dynamically over a network (e.g. intra-, extra- or inter-net). Applying the constructs of grid computing to the service orientation of enterprise software will allow business service networks to utilize more specialized services. An upper service ontology that enables business grid services to be described and then related to the grid hosting platform is presented. Explicit knowledge is required for enterprise software, hosting servers and the domain that can then be utilized by both SLA and reservation systems. The ontology presented is derived from and validated using a collection of web services taken from leading investment banks
A Taxonomy of Workflow Management Systems for Grid Computing
With the advent of Grid and application technologies, scientists and
engineers are building more and more complex applications to manage and process
large data sets, and execute scientific experiments on distributed resources.
Such application scenarios require means for composing and executing complex
workflows. Therefore, many efforts have been made towards the development of
workflow management systems for Grid computing. In this paper, we propose a
taxonomy that characterizes and classifies various approaches for building and
executing workflows on Grids. We also survey several representative Grid
workflow systems developed by various projects world-wide to demonstrate the
comprehensiveness of the taxonomy. The taxonomy not only highlights the design
and engineering similarities and differences of state-of-the-art in Grid
workflow systems, but also identifies the areas that need further research.Comment: 29 pages, 15 figure
Global Grids and Software Toolkits: A Study of Four Grid Middleware Technologies
Grid is an infrastructure that involves the integrated and collaborative use
of computers, networks, databases and scientific instruments owned and managed
by multiple organizations. Grid applications often involve large amounts of
data and/or computing resources that require secure resource sharing across
organizational boundaries. This makes Grid application management and
deployment a complex undertaking. Grid middlewares provide users with seamless
computing ability and uniform access to resources in the heterogeneous Grid
environment. Several software toolkits and systems have been developed, most of
which are results of academic research projects, all over the world. This
chapter will focus on four of these middlewares--UNICORE, Globus, Legion and
Gridbus. It also presents our implementation of a resource broker for UNICORE
as this functionality was not supported in it. A comparison of these systems on
the basis of the architecture, implementation model and several other features
is included.Comment: 19 pages, 10 figure
Enabling quantitative data analysis through e-infrastructures
This paper discusses how quantitative data analysis in the social sciences can engage with and exploit an e-Infrastructure. We highlight how a number of activities which are central to quantitative data analysis, referred to as ‘data management’, can benefit from e-infrastructure support. We conclude by discussing how these issues are relevant to the DAMES (Data Management through e-Social Science) research Node, an ongoing project that aims to develop e-Infrastructural resources for quantitative data analysis in the social sciences
Two ways to Grid: the contribution of Open Grid Services Architecture (OGSA) mechanisms to service-centric and resource-centric lifecycles
Service Oriented Architectures (SOAs) support service lifecycle tasks, including Development, Deployment, Discovery and Use. We observe that there are two disparate ways to use Grid SOAs such as the Open Grid Services Architecture (OGSA) as exemplified in the Globus Toolkit (GT3/4). One is a traditional enterprise SOA use where end-user services are developed, deployed and resourced behind firewalls, for use by external consumers: a service-centric (or ‘first-order’) approach. The other supports end-user development, deployment, and resourcing of applications across organizations via the use of execution and resource management services: A Resource-centric (or ‘second-order’) approach. We analyze and compare the two approaches using a combination of empirical experiments and an architectural evaluation methodology (scenario, mechanism, and quality attributes) to reveal common and distinct strengths and weaknesses. The impact of potential improvements (which are likely to be manifested by GT4) is estimated, and opportunities for alternative architectures and technologies explored. We conclude by investigating if the two approaches can be converged or combined, and if they are compatible on shared resources
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