Computing and Information Systems - Research Publications
Permanent URI for this collection
Search Results
1 - 6 of 6
-
ItemThe Virtual Kidney: an eScience interface and Grid portal(ROYAL SOC, 2009-06-13)The Virtual Kidney uses a web interface and distributed computing to provide experimental scientists and analysts with access to computational simulations and knowledge databases hosted in geographically separated laboratories. Users can explore a variety of complex models without requiring the specific programming environment in which applications have been developed. This initiative exploits high-bandwidth communication networks for collaborative research and for shared access to knowledge resources. The Virtual Kidney has been developed within a specialist community of renal scientists but is transferable to other areas of research requiring interaction between published literature and databases, theoretical models and simulations and the formulation of effective experimental designs. A web-based three-dimensional interface provides access to experimental data, a parameter database and mathematical models. A multi-scale kidney reconstruction includes blood vessels and serially sectioned nephrons. Selection of structures provides links to the database, returning parameter values and extracts from the literature. Models are run locally or remotely with a Grid resource broker managing scheduling, monitoring and visualization of simulation results and application, credential and resource allocation. Simulation results are viewed graphically or as scaled colour gradients on the Virtual Kidney structures, allowing visual and quantitative appreciation of the effects of simulated parameter changes.
-
Item
-
ItemA toolkit for modelling and simulating data Grids: an extension to GridSim(WILEY, 2008-09-10)
-
ItemInterGrid:: a case for internetworking islands of Grids(WILEY, 2008-06-10)
-
ItemA grid service broker for scheduling e-Science applications on global data grids(John Wiley & Sons, 2006)The next generation of scientific experiments and studies, popularly called e-Science, is carried out by large collaborations of researchers distributed around the world engaged in the analysis of huge collections of data generated by scientific instruments. Grid computing has emerged as an enabler for e-Science as it permits the creation of virtual organizations that bring together communities with common objectives. Within a community, data collections are stored or replicated on distributed resources to enhance storage capability or the efficiency of access. In such an environment, scientists need to have the ability to carry out their studies by transparently accessing distributed data and computational resources. In this paper, we propose and develop a Grid broker that mediates access to distributed resources by: (a) discovering suitable data and computational resources sources for a given analysis scenario; (b) optimally mapping analysis jobs to resources; (c) deploying and monitoring job execution on selected resources; (d) accessing data from local or remote data sources during job execution; and (e) collating and presenting results. The broker supports a declarative and dynamic parametric programming model for creating Grid applications. We have used this model in Grid-enabling a high-energy physics analysis application (the Belle Analysis Software Framework). The broker has been used in deploying Belle experimental data analysis jobs on a Grid testbed, called the Belle Analysis Data Grid, having resources distributed across Australia interconnected through GrangeNet.
-
ItemNeuroscience instrumentation and distributed analysis of brain activity data: A case for eScience on global Grids(John Wiley & Sons, 2005)The distribution of knowledge (by scientists) and data sources (advanced scientific instruments), and the need for large-scale computational resources for analyzing massive scientific data are two major problems commonly observed in scientific disciplines. Two popular scientific disciplines of this nature are brain science and high-energy physics. The analysis of brain-activity data gathered from the MEG (magnetoencephalography) instrument is an important research topic in medical science since it helps doctors in identifying symptoms of diseases. The data needs to be analyzed exhaustively to efficiently diagnose and analyze brain functions and requires access to large-scale computational resources. The potential platform for solving such resource intensive applications is the Grid. This paper presents the design and development of MEG data analysis system by leveraging Grid technologies, primarily Nimrod-G, Gridbus, and Globus. It describes the composition of the neuroscience (brain-activity analysis) application as parameter-sweep application and its on-demand deployment on global Grids for distributed execution. The results of economic-based scheduling of analysis jobs for three different optimizations scenarios on the world-wide Grid testbed resources are presented along with their graphical visualization.