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P2P Network for Very Large Virtual Environment

P2P Network for Very Large Virtual Environment. Proceedings of the ACM symposium on virtual reality software and technology VRST '06. Outline. Introduction Overview System Structure Hierarchical LOD Object Structure Data Exchange Methods Simulation Conclusion. Introduction.

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P2P Network for Very Large Virtual Environment

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  1. P2P Network for Very Large Virtual Environment Proceedings of the ACM symposium on virtual reality software and technology VRST '06

  2. Outline • Introduction • Overview • System Structure • Hierarchical LOD Object Structure • Data Exchange Methods • Simulation • Conclusion Adaptive Computing and Networking Lab

  3. Introduction • A centralized architecture is obviously not a good framework to build a truly scalable Virtual Environment (VE). • P2P network overlays are potentially proper architecture. Adaptive Computing and Networking Lab

  4. Introduction • This paper describes a peer connectivity method for visualizing very vast and complex environments and sharing these environments among many users. Adaptive Computing and Networking Lab

  5. Adaptive Computing and Networking Lab

  6. Key Concept • Neighbor peers in a VE are likely to have a lot of data in common • For example, if two peers have nearly the same viewpoint in a city model, data stored in both peers will be almost the same. Adaptive Computing and Networking Lab

  7. Challenges • Finding and maintaining the appropriate peer connectivity is a very difficult problem in a changing environment where peers viewpoint are allowed to move freely and peers can disconnect or appear at any time. Adaptive Computing and Networking Lab

  8. Adaptive Computing and Networking Lab

  9. Peer Connectivity Method • Self-Adaptation:the ability for a requesting peer to dynamically take into account the serving capacity of neighbor peers Adaptive Computing and Networking Lab

  10. Peer Connectivity Method • Three types of peers： • Memory Peers (MP) • Likened to central servers • Visualization Peers (VP) • End-user peers • Connectivity Peers (CP) • Assigned the task of achieving the connectivity between peers Adaptive Computing and Networking Lab

  11. Peer Connectivity Method • Each CP manages all VPs connected to it and, upon a request of a connected VP, it provides a list of the N VP neighbors, N being a parameter of the request. • The list of VP neighbors is the allocated serving pool (ASP). Adaptive Computing and Networking Lab

  12. Adaptive Computing and Networking Lab

  13. Peer Connectivity Method • Goal:to distribute the data requests of a VP among its neighbor VPs. Adaptive Computing and Networking Lab

  14. Peer Connectivity Method • The selection of the serving VPs is made according to the following characterizes: • Time To Server (TTS). • The estimated available data • The upload limit in bandwidth (BPUPL) assigned to this peer for P2P serving tasks. • The number of peers currently served by the serving peer (NBPCS). Adaptive Computing and Networking Lab

  15. Simulation • Accuracy:ACC = NMISS / NREQ • Accuracy at time t is measured as the number of missing nodes (NMISS) in the level-of-detail (LOD) trees with respect to the number of required nodes (NREQ) to render the current viewpoint. Adaptive Computing and Networking Lab

  16. Simulation Adaptive Computing and Networking Lab

  17. Progressive Building Tree: PBTree Adaptive Computing and Networking Lab

  18. LOD Description Tree Adaptive Computing and Networking Lab

  19. Using LODDT to render different viewpoints Adaptive Computing and Networking Lab

  20. Using LODDT to assess the content of neighbor peer cache Adaptive Computing and Networking Lab

  21. Data Exchange Methods Adaptive Computing and Networking Lab

  22. Data Exchange Methods • Four types data exchange methods： • From the MP only (C/S) • From the peer having the least TTS • From the closest peer • Using self-adaptive distribution method. Adaptive Computing and Networking Lab

  23. Simulation Adaptive Computing and Networking Lab

  24. Simulation Adaptive Computing and Networking Lab

  25. Simulation Adaptive Computing and Networking Lab

  26. Conclusion • This paper proposes a new spatially-organized P2P network overlay with intent to obtain self-scalability for a truly scalable Virtual Environment (VE). • It takes into account peer proximity along with some parameters and state variables that allow to assess the current serving capacity of the neighbor peers. Adaptive Computing and Networking Lab

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