Scientific visualization today usually involves scientists from multiple disciplines trying to tackle complex simulation problems or dealing with large datasets. These scientists are likely geographically distributed, so there is a cost in both finance and time, when they are required to collaborate or meet face-to-face. The complex problems and larger datasets require high performance computing facilities which are not always available from these scientists’ desktops. The objective of this research is to address these two issues. We aim to create a novel visualization framework which supports collaborative working amongst different users and utilizes high performance computational resources in a Grid environment. The system is named as NoCoV, short for Notification-service-based Collaborative Visualization system. The system involves a number of visualization notification services which can be jointly provided by different developers and deployed on different Grid networks. A visualization notification service can subscribe to other services and receive notification messages delivered from them. By using this subscription/notification communication pattern, users can link suitable visualization services together through a centralized controller service to create customized visualization pipelines according to their different requirements. Collaborative working is supported in both creating and steering of visualization pipelines. Visualization information is recorded as XML-based descriptions and published as notification topics on a controller service. By subscribing to this controller service, collaboration can be achieved by sharing the visualization information amongst different participants. The NoCoV system accommodates users with different background knowledge and supports collaboration between them. Visualization services are jointly provided by different visualization service developers. Visualization experts can compose pipelines with the services created by service developers using their visualization expertise. Application scientists can use pipelines created by visualization experts and can set steering parameters according to their specialized knowledge. A NoCoV prototype is implemented as proof of concept. The prototype has four visualization services and one controller service which are implemented as WSRF notification services deployed on GT4 containers. The prototype also provides a pipeline editor client GUI for visualization experts to create visualization pipelines and a parameter control client for application scientists to steer these pipelines. The performance of the NoCoV prototype is evaluated by a test involving a pipeline distributed across different Grid networks. The limitations of the NoCoV system and the future work are also discussed at the end of this thesis. The overall vision of the NoCoV system is to produce the next generation of visualization system, which has a worldwide repository of visualization services deployed on different Grid networks and supports collaboration amongst users on a global scale.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:445372 |
| Date | January 2007 |
| Creators | Wang, Haoxiang |
| Contributors | Brodlie, K. W. |
| Publisher | University of Leeds |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://etheses.whiterose.ac.uk/1361/ |
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