On-demand transmission model using image-based rendering for remote visualization

Interactive distributed visualization is an emerging technology with numerous applications. However, many of the present approaches to interactive distributed visualization have limited performance since they are based on the traditional polygonal processing graphics pipeline. In contrast, image-based rendering uses multiple images of the scene instead of a 3D geometrical representation, and so has the key advantage that the final output is independent of the scene complexity, and depends on the desired final image resolution. These multiple images are referred to as the light field dataset. In this thesis we propose an on-demand solution for efficiently transmitting visualization data to remote users/clients. This is achieved through sending selected parts of the dataset based on the current client viewpoint, and is done instead of downloading a complete replica of the light field dataset to each client, or remotely sending a single rendered view back from a central server to the user each time the user updates their viewing parameters. The on-demand approach shows stable performance as the number of clients increases because the load on the server and the network traffic are reduced. Furthermore, detailed performance studies show that the proposed on-demand scheme outperforms the current local and remote solutions in terms of interactivity measured in frames per second. In addition, a performance study based on a theoretical cost model is presen ted. The model was able to provide realistic estimations of the results for different ranges of dataset sizes. Also, these results indicate that the model can be used as a predictive tool for estimating timings for the visualization process, enabling the improvement of the process and product quality, as well as the further develop ment of models for larger systems and datasets. In further discussing the strengths and weaknesses of each of the models, we see that to be able to run the system for larger dataset resolution involves a trade-off between generality of hardware (the server and network) and dataset resolution. Larger dataset resolution cannot achieve interactive frame rates on current COTS infrastructure. Finally, we conclude that the design of our 3D visualization system, based on image-based rendering coupled with an on-demand transmission model, has made a contribution to the field, and is a good basis for the future development of collaborative, distributed visualization systems

CAVE 3D: Software Extensions for Scientific Visualization of Large-scale Models

AbstractNumerical analysis of large-scale and multidisciplinary problems on high-performance computer systems is one of the main computational challenges of the 21st century. The amount of data processed in complex systems analyses approaches peta- and exascale. The technical possibility for real-time visualization, post-processing and analysis of large-scale models is extremely important for carrying out comprehensive numerical studies. Powerful visualization is going to play an important role in the future of large-scale models. In this paper, we describe several software extensions aimed to improve visualization performance for large-scale models and developed by our team for 3D virtual environment systems such as CAVEs and Powerwalls. These extensions include an algorithm for real-time generation of isosurfaces on large meshes and a visualization system designed for massively parallel computing environment. Besides, we describe an augmented reality system developed by the part of our team in Stuttgart

Analysis domain model for shared virtual environments

The field of shared virtual environments, which also encompasses online games and social 3D environments, has a system landscape consisting of multiple solutions that share great functional overlap. However, there is little system interoperability between the different solutions. A shared virtual environment has an associated problem domain that is highly complex raising difficult challenges to the development process, starting with the architectural design of the underlying system. This paper has two main contributions. The first contribution is a broad domain analysis of shared virtual environments, which enables developers to have a better understanding of the whole rather than the part(s). The second contribution is a reference domain model for discussing and describing solutions - the Analysis Domain Model

Understanding Next-Generation VR: Classifying Commodity Clusters for Immersive Virtual Reality

Commodity clusters offer the ability to deliver higher performance computer graphics at lower prices than traditional graphics supercomputers. Immersive virtual reality systems demand notoriously high computational requirements to deliver adequate real-time graphics, leading to the emergence of commodity clusters for immersive virtual reality. Such clusters deliver the graphics power needed by leveraging the combined power of several computers to meet the demands of real-time interactive immersive computer graphics.However, the field of commodity cluster-based virtual reality is still in early stages of development and the field is currently adhoc in nature and lacks order. There is no accepted means for comparing approaches and implementers are left with instinctual or trial-and-error means for selecting an approach.This paper provides a classification system that facilitates understanding not only of the nature of different clustering systems but also the interrelations between them. The system is built from a new model for generalized computer graphics applications, which is based on the flow of data through a sequence of operations over the entire context of the application. Prior models and classification systems have been too focused in context and application whereas the system described here provides a unified means for comparison of works within the field

A framework for realistic 3D tele-immersion

Meeting, socializing and conversing online with a group of people using teleconferencing systems is still quite differ- ent from the experience of meeting face to face. We are abruptly aware that we are online and that the people we are engaging with are not in close proximity. Analogous to how talking on the telephone does not replicate the experi- ence of talking in person. Several causes for these differences have been identified and we propose inspiring and innova- tive solutions to these hurdles in attempt to provide a more realistic, believable and engaging online conversational expe- rience. We present the distributed and scalable framework REVERIE that provides a balanced mix of these solutions. Applications build on top of the REVERIE framework will be able to provide interactive, immersive, photo-realistic ex- periences to a multitude of users that for them will feel much more similar to having face to face meetings than the expe- rience offered by conventional teleconferencing systems

Mathematical Modelling of Chemical Diffusion through Skin using Grid-based PSEs

A Problem Solving Environment (PSE) with connections to remote distributed Grid processes is developed. The Grid simulation is itself a parallel process and allows steering of individual or multiple runs of the core computation of chemical diffusion through the stratum corneum, the outer layer of the skin. The effectiveness of this Grid-based approach in improving the quality of the simulation is assessed

Methods and design issues for next generation network-aware applications

Networks are becoming an essential component of modern cyberinfrastructure and this work describes methods of designing distributed applications for high-speed networks to improve application scalability, performance and capabilities. As the amount of data generated by scientific applications continues to grow, to be able to handle and process it, applications should be designed to use parallel, distributed resources and high-speed networks. For scalable application design developers should move away from the current component-based approach and implement instead an integrated, non-layered architecture where applications can use specialized low-level interfaces. The main focus of this research is on interactive, collaborative visualization of large datasets. This work describes how a visualization application can be improved through using distributed resources and high-speed network links to interactively visualize tens of gigabytes of data and handle terabyte datasets while maintaining high quality. The application supports interactive frame rates, high resolution, collaborative visualization and sustains remote I/O bandwidths of several Gbps (up to 30 times faster than local I/O). Motivated by the distributed visualization application, this work also researches remote data access systems. Because wide-area networks may have a high latency, the remote I/O system uses an architecture that effectively hides latency. Five remote data access architectures are analyzed and the results show that an architecture that combines bulk and pipeline processing is the best solution for high-throughput remote data access. The resulting system, also supporting high-speed transport protocols and configurable remote operations, is up to 400 times faster than a comparable existing remote data access system. Transport protocols are compared to understand which protocol can best utilize high-speed network connections, concluding that a rate-based protocol is the best solution, being 8 times faster than standard TCP. An HD-based remote teaching application experiment is conducted, illustrating the potential of network-aware applications in a production environment. Future research areas are presented, with emphasis on network-aware optimization, execution and deployment scenarios