Remote Visualization Based on Distributed Rendering Framework

The progressive increase of Internet bandwidth makes remote visualization possible, which has advantages of remote share, mobility and convenience. A Sort-Last based distributed rendering architecture composed of rendering nodes, blending nodes and task nodes, and the corresponding algorithms including GPU based blending and anti-aliasing, are proposed to address the large-scale data rendering problem. The framework is highly parallel and extensible at each level such as rendering, blending and task balance, that is, arbitrary nodes can be deployed as stack structure according to performance requirement. On that basis, a remote visualization system, namely Waterman, is implemented to provide Internet services of terrain rendering and sewage visualization of sea outfalls. The design methods and techniques of Waterman are introduced in detail, which includes GPU based Raycasting algorithm for fast terrain rendering, land mask based technique to remove water area of aero photo texture for sea surface rendering and visualization, and hybrid rendering method using both polygon model and image based rendering. Finally, extensive experiments are settled to analyze benchmark of the distributed rendering framework, as well as time performance and data traffic throughput of the total remote visualization system. The results indicate that the proposed method is practicable, robust, and can serve as a good study case for similar systems.