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FLoD: A Framework for Peer-to-Peer 3D Streaming IEEE INFOCOM 2008 Shun-Yun Hu*, Ting-Hao Huang, Shao-Chen Chang*, Wei-Lun Sung*, Jehn-Ruey Jiang*, and Bing-Yu Chen National Central University*, National Taiwan University Taiwan, R.O.C.
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Outline Networked Virtual Environments (NVEs) Motivation P2P NVE Neighbor Discovery P2P 3D Streaming Conclusion
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Outline Networked Virtual Environments (NVEs) Motivation P2P NVE Neighbor Discovery P2P 3D Streaming Conclusion
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5 Adaptive Computing and Networking Lab, CSIE, NCU
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NCU ACNLab
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Massively Multiplayer Online Games MMOGs are growing quickly Multi-billion dollar industry 10 million subscribers for World of Warcraft 600,000 concurrent users
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NASA World Wind
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Google Earth
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Zoom in…
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NCU ACNLab To HsinChu..
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and NTHU..
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It is going to be 3D
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NTHU 3D Student Center…
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To the ground
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3-Dimensional Virtual Tourism Google Earth Virtual Earth NASA World Wind X3D Earth NCU ACNLab
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DARPA SIMNET: screenshot From Bruce Sterling's "War is Virtual Hell,“ (1993).
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CALVIN: a distributed collaborative virtual environments for architectural layout designs (1996)
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20 NVE A networked virtual environment (NVE) is a computer-generated virtual world where multiple geographically dispersed users can assume virtual representatives (or avatars) to concurrently interact with each other in real time through networked devices. Also called a distributed virtual environment (DVE)
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21 NVE Examples of NVEs include early DARPA SIMNET and DIS systems early distributed collaborative virtual environments currently booming Massively Multiplayer Online Games (MMOGs) future multi-user 3DVTs future multi-user Web 3D browser
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Outline Networked Virtual Environments (NVEs) Motivation P2P NVE Neighbor Discovery P2P 3D Streaming Conclusion NCU ACNLab
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Motivation Two future trends for NVEs More and more users More worlds with larger and more dynamic contents
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NCU ACNLab Motivation Q: How to support millions of concurrent users? A: Utilizing peer-to-peer schemes to relief the load of servers
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NCU ACNLab Motivation Q: How to support large and dynamic worlds? A: 3D streaming is needed
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Outline Networked Virtual Environments (NVEs) Motivation P2P NVE Neighbor Discovery P2P 3D Streaming Conclusion NCU ACNLab
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27 Model for NVEs Many nodes on a 2D plane An avatar needs to know only those within Area of Interest (AOI) ★ : self ▲ : neighbors Area of Interest (AOI)
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How does each node receive the relevant messages? Completely connected point-to-point Client/Server Client/Server cluster Partially connected point-to-point (peer-to-peer) NCU ACNLab
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29 A simple solution (point-to-point) But…too many irrelevant messages N * (N-1) connections ≈ O(N 2 ) Not scalable! Source: [Funkhouser95]
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30 A better solution (client-server) Message filtering at server to reduce traffic N connections = O(N) server is bottleneck Source: [Funkhouser95]
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31 Current solution (server-cluster) Still limited by servers. Expensive to deploy & maintain. Source: [Funkhouser95]
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The Problem Client-server: resources limited by provisioning Resource limit [Funkhouser95]
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The Solution Peer-to-Peer: resources grow with demand Resource limit [Keller & Simon 2003]
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34 P2P NVE Neighbor Discovery We need to solve the neighbor discovery problem in a fully-distributed, message- efficient manner with specific goals: Consistent Good neighborship consistency Scalable Limit & minimize message traffics Responsive Direct connection with AOI neighbors
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35 Neighborship Consistency (1) Definition # of current AOI neighbors observed # of current AOI neighbors
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36 :is observed neighbor Neighborship Consistency (2) An example Neighborship Consistency = 4 / 5 = 80% :is actual neighbor
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Voronoi-based Overlay Network : VON Use Voronoi diagram to solve the neighbor discovery problem Each node constructs a Voronoi diagram of its neighbors Identify enclosing and boundary neighbors Mutual collaboration in neighbor discovery
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38 Voronoi Diagram 2D Plane partitioned into regions by sites, each region contains all the points closest to its site Site Region
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Voronoi-based Overlay Network : VON ● node i and the big circle is its AOI ■ enclosing neighbors ▲ boundary neighbors ★ both enclosing and boundary neighbors ▼ normal AOI neighbors ◆ irrelevant nodes
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40 Procedure (JOIN) 1)Joining node sends coordinates to any existing node Join request is forwarded to acceptor 2)Acceptor sends back its own neighbor list Joining node connects with other nodes on the list Acceptor’s region Joining node
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41 Procedure (MOVE) 1)Positions sent to all neighbors, mark messages to B.N. B.N. checks for overlaps between mover’s AOI and its E.N. 2)Connect to new nodes upon notification by B.N. Boundary neighbors New neighbors
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42 Procedure (LEAVE) 1)Simply disconnect 2)Others then update their Voronoi diagram new B.N. is discovered via existing B.N. Leaving node (also a B.N.) New boundary neighbor
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Outline Networked Virtual Environments (NVEs) Motivation P2P NVE Neighbor Discovery P2P 3D Streaming Conclusion
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What is 3D streaming? Continuous and real-time delivery of 3D contents over network connections to allow user interactions without a full download. Contents are fragmented, transmitted, reconstructed, and then displayed.
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3D streaming vs. media streaming Video / audio media streaming is very matured User access patterns are different for 3D content Highly interactive Latency-sensitive Behaviour-dependent Non-sequential
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4 types of 3D streaming Object streaming Scene streaming Visualization streaming Image-based streaming
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47/ Object streaming Hoppe 1996 Progressive Meshes
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48/ Scene streaming Many objects Object selections & transmissions Teler &Lischinski 2001
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P2P-based 3D Streaming Models & assumptions Many 3D objects(position, orientation) User navigations withAOI visibility Objects are fragmented (base & refinement pieces) Data are initially stored at server
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50/ NCU ACNLab Observation Limited & predictable area of interest (AOI) Overlapped visibility = shared content
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FLoD: Flowing Level-of-Details Assume P2P-NVE overlay, such as VON Download 3D content from AOI neighbors Basic design Each object has a unique ID and associated progressive mesh data Scene description records object ID, orientation, and scale World is partitioned into cells
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IEEE INFOCOM 2008
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Steps of FLoD 1. Peers exchange incremental formation of cached 3D data periodically 2. A peer sends requests for downloading scene descriptions 3. A peer sends requests for downloading object data 4. A peer asks the server if none of the peers responds
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Object Prioritization Visual importance
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Peer selection Multi-level request
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Prototype experiment Progressive modeling and rendering of the scene (by NTU) P2P neighbor discovery and 3D streaming (by NCU)
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Partition Cell-based construction Use an actual game scene 100x game scene (514KB -> 51.8MB)
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Fragmentation
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Simulation setup Environment 1000x1000 world, 100ms / step, 3000 steps client: 1 Mbps / 256 Kbps, server: 10 Mbps (both) Objects Random object placement (500 objects) User behavior Random way-point clustering movement (1.5 * ln(n) hotspots)
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Metrics Server's perspective Requests can be redirected (bandwidth usage) User's perspective Visual quality (fill ratio) Interactivity (base latency)
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Server bandwidth usage
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Client bandwidth usage
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Fill ratio
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Base latency
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Outline Networked Virtual Environments (NVEs) Motivation P2P NVE Neighbor Discovery P2P 3D Streaming Conclusion
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NVE neighbor discovery can be solved in a P2P manner with Good neighborship consistency Low message overhead NVE 3D streaming can be solved in a P2P manner with Minimal server resource usage Low control message overhead Short Latency
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Conclusion Future work Multi-user X3D browser Multi-user X3D browser with P2P 3D streaming TOPOS (Greek; common place): Authenticable P2P personal 3D space publication and navigation system H E AVEN (a Hybrid Architecture for massively multi-user Virtual ENvironments): client assisted MMOGs
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Adaptive Computing and Networking Lab. Q & A Thank you! http://acnlab.csie.ncu.edu.tw
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69 Related Work (1): DHT-based: SimMUD [Knutsson et al. 2004] (UPenn) Pastry (DHT mapping) + Scribe (Multicast) Fixed-Sized Regions Coordinators
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70 PASTRY (P2P overlay) SCRIBE (Multicast support) MMOG GAME Related Work (1): DHT-based: SimMUD
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71 Related Work (1): DHT-based: SimMUD
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72 Related Work (2): Neighbor-list Exchange [Kawahara et al. 2004] (Univ. of Tokyo) Fully-distributed Nearest-neighbors List exchange High transmission Overlay partition
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73 Related Work (3): Mutual Notification: Solipsis [Keller & Simon 2003] (France Telecomm R&D) Links with AOI neighbor Mutual cooperation Inside convex hull Potentially slow discovery Inconsistent topology
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74/ Visualization streaming Large volume Time-varying Dedicated servers Olbrich & Pralle 1999
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75/ Image-based streaming Server- rendered Thin clients Less responsive Cohen-Or et. al. 2002
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