To improve the visualization of large 3D landscapes and city models in a network environment, the authors use two different types of hierarchical level-of-detail models for terrain and groups of buildings. They also leverage the models to implement progressive streaming in both client-server and peer-to-peer network architectures.
The ever increasing speed of Internet connections has led to a point where it is actually possible for every end user to seamlessly share data on Internet. Peer-To-Peer (P2P) networks are typical of this evolution. The goal of our paper is to show that server-less P2P networks with self-adaptive assignment techniques can efficiently deal with very large environments such as met in the geovisualization domain. Our method allows adaptative view-dependent visualization thanks to a hierarchical and progressive data structure that describes the environment. In order to assess the global efficiency of this P2P technique, we have implemented a dedicated real time simulator. Experimentation results are presented using a hierarchical LOD model of a very large urban environment.
Peer-to-peer (P2P) architectures have recently become very popular in massively multiplayer games (MMGs). While P2P gaming offers high scalability compared to client/server architectures, it introduces several major issues related to data distribution and game state consistency. In this paper, we report our initial version of VoroGame, a P2P architecture for MMGs that addresses these issues by combining a structured P2P overlay based on a distributed hash table (DHT) for data distribution, with a Voronoi diagram used for virtual game world decomposition and semantic overlay support. The resulting hybrid architecture enables a fully distributed management of data and state information, and ensures efficient dissemination of game state updates to relevant peers.
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