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Scalable PeertoPeer Networked Virtual Environment

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Consistency (Topology) Topology is fully connected & consistent enclosing neighbors ... Distributed event/state consistency. Recovery from overlay partition ... – PowerPoint PPT presentation

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Title: Scalable PeertoPeer Networked Virtual Environment


1
Scalable Peer-to-Peer Networked Virtual
Environment
  • Master Thesis Oral Examination
  • Dept. of CSIE, Tamkang Univ.
  • Advisor Dr. Chen Jui-Fa
  • Shun-Yun Hu
  • 2005/01/07

2
Outline
  • Introduction
  • Voronoi-based Overlay Network (VON)
  • Simulation Results
  • Analysis
  • Conclusion

3
What is Networked Virtual Environment (NVE)?
  • Virtual Reality Internet
  • 3D environment with people (avatar), objects,
    terrain, agents
  • Military simulations (80) ?
  • Massively Multiplayer Online Games (mid-90)
  • Trends larger scale, more realistic simulation

4
(No Transcript)
5
NVE A Shared Space
6
Issues for Creating NVE
  • Consistency (events/states)
  • Responsiveness multiplayer
  • Security
  • Scalability
  • Persistency massively multiplayer
  • Reliability (Fault-tolerance)

7
The Scalability Problem
  • Many nodes on a 2D plane ( gt 1,000)
  • Message exchange with those within Area of
    Interest (AOI)
  • How does each node receive the relevant messages?

Area of Interest
8
A simple solution (point-to-point)
Source Funkhouser95
  • N (N-1) connections O(N2) ? Not scalable!

9
A better solution (client-server)
Source Funkhouser95
  • Message filtering at server to reduce traffic
  • N connections O(N) ? server is bottleneck

10
Current solution (server-cluster)
Source Funkhouser95
  • Still limited by servers. Expansive to deploy
    maintain.

11
Scalability Analysis
  • Scalability constrains
  • Computing resource (CPU)
  • Network resource (Bandwidth)
  • Non-scalable system vs. Scalable system

Resource limit
x number of entities y resource consumption at
the limiting system component
12
What Next?
  • Strategies
  • Increase resource ? More servers
  • Decrease consumption ? Message filtering
  • Architectures Scale
  • Point-to-point (LAN) tens 101
  • Client-server hundreds 102
  • Server-cluster thousands 103
  • ? millions 106
  • Peer-to-Peer

13
What is Peer-to-Peer (P2P)?
  • Stoica et al. 2003
  • Distributed systems without any centralized
    control or hierarchical organization
  • Runs software with equivalent functionality
  • Examples
  • File-sharing Napster, Gnutella, eDonkey
  • Distributed computing SETI_at_Home (UC Berkeley)
  • VoIP Skype

14
Peer-to-Peer Overlay
  • A P2P overlay network source Keller Simon
    2003

15
Promise Challenge of P2P
  • Promises
  • Growing resource, decentralized ? Scalable
  • Commodity hardware ? Affordable
  • Challenges
  • Topology maintenance ? dynamic join/leave
  • Efficient content retrieval ? no global knowledge

16
Issues for Creating P2P NVE
  • Consistency (events/states)
  • Responsiveness multiplayer
  • Security
  • Scalability
  • Persistency massively multiplayer
  • Reliability (Fault-tolerance)
  • Consistency (topology) ? P2P NVE

17
Related Works (1) SimMUD
  • Knutsson et al. 2004 (Univ. of Pennsylvania)
  • Pastry Scribe
  • Regions
  • Coordinators
  • (super-nodes)
  • Fixed-size region
  • Relay overhead

18
Related Works (2)
  • Kawahara et al. 2004 (Univ. of Tokyo)
  • Fully-distributed
  • Nearest-neighbors
  • List exchange
  • High transmission
  • Overlay partition

19
Related Works (3) Solipsis
  • Keller Simon 2003 (France Telecomm RD)
  • Links with AOI neighbor
  • Mutual cooperation
  • Inside convex hull
  • Potentially slow discovery
  • Inconsistent topology

20
Outline
  • Introduction
  • Voronoi-based Overlay Network (VON)
  • Simulation Results
  • Analysis
  • Conclusion

21
Design Goals
  • Observation
  • for virtual environment applications, the
    contents we want are messages from AOI neighbors
  • Content discovery is a neighbor discovery problem
  • Solve the Neighbor Discovery Problem in a
    fully-distributed, message-efficient manner.
  • Specific goals
  • Scalable ? Limit minimize message traffics
  • Responsive ? Direct connection with AOI neighbors

22
Voronoi Diagram
  • 2D Plane partitioned into regions by sites, each
    region contains all the points closest to its
    site
  • Can be used to find k-nearest neighbor easily

Neighbors
Region
Site
23
Design Concepts
Use Voronoi to solve the neighbor discovery
problem
  • Identify enclosing and boundary neighbors
  • Each node constructs a Voronoi of its neighbors
  • Enclosing neighbors are minimally maintained
  • Mutual collaboration in neighbor discovery

24
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

Joining node
Acceptors region
25
Procedure (MOVE)
  • 1) Positions sent to all neighbors, mark messages
    to B.N.
  • B.N. checks for overlaps between movers AOI and
    its E.N.
  • 2) Connect to new nodes upon notification by B.N.
  • Disconnect any non-overlapped neighbor

Boundary neighbors
Non-overlapped neighbors
New neighbors
26
Procedure (LEAVE)
  • 1) Simply disconnect
  • 2) Others then update their Voronoi
  • new B.N. is discovered via existing B.N.

New boundary neighbor
Leaving node (also a B.N.)
27
Dynamic AOI
  • Crowding within AOI can overload a particular
    node
  • Its better if AOI-radius can be adjusted in real
    time

28
Adjustment Conditions
  • AOI-radius decrease
  • Number of connections gt maximum allowable
    connections
  • AOI-radius increase
  • Maximum connections not exceeded
  • Current AOI-radius lt preferred AOI-radius
  • Delay counter
  • To avoid fluctuations

29
Demonstration
  • Simulation video
  • General movements (20 nodes, 800x600 world)
  • Local vs. global view
  • Dynamic AOI adjustment

30
(No Transcript)
31
Outline
  • Introduction
  • Voronoi-based Overlay Network (VON)
  • Simulation Results
  • Analysis
  • Conclusion

32
Simulation Method
  • C implementation of Voronoi-based algorithm
  • World size 1000 x 1000, AOI 150
  • Trials from 10 250 nodes
  • Connection limit per node 10
  • 1000 time-steps
  • ( 100 simulated seconds, assuming 10
    updates/seconds)
  • Behavior model
  • Random movement random direction
  • Constant velocity 5 units/step
  • Movement duration random (1 25 steps)

33
Consistency Metrics
  • Topology Consistency Kawahara, 2004
  • Number of observed AOI neighbors
  • Number of actual AOI neighbors
  • Drift Distance Diot, 1999
  • Distance between observed position and actual
    position
  • (average over all nodes)

34
Basic ModelTopology Consistency
35
Basic ModelScalability (1)
36
Basic ModelScalability (2)
37
Dynamic AOI Model
38
Dynamic AOIScalability (1)
39
Dynamic AOIScalability (2)
40
Dynamic AOIScalability (3)
41
Dynamic AOITopology Consistency (1)
42
Dynamic AOITopology Consistency (2)
43
Dynamic AOIReliability (1)
44
Dynamic AOIReliability (2)
45
Outline
  • Introduction
  • Voronoi-based Overlay Network (VON)
  • Simulation Results
  • Analysis
  • Conclusion

46
Analysis of Design
  • Consistency (Topology)
  • Topology is fully connected consistent ?
    enclosing neighbors
  • Responsiveness
  • Lowest latency ? direct connection, no relay
  • Scalability
  • Resource-growing decentralized resource
    consumption
  • Reliability
  • Self-organizing for small number of node failures

47
P2P NVE Comparisons
48
Problems of Voronoi Approach
  • Message traffic
  • Circular round-up of nodes
  • Redundant message sending
  • (inherent to fully-distributed design)
  • Incomplete neighbor discovery
  • Can happen with inconsistent / incorrect neighbor
    list
  • Fast moving node

49
Outline
  • Introduction
  • Voronoi-based Overlay Network (VON)
  • Simulation Results
  • Analysis
  • Conclusion

50
Conclusion
  • NVE scalability is achievable with P2P
    architecture and is a neighbor discovery problem
  • A promising solution Voronoi-based P2P Overlay
  • Leverage knowledge of each peer to maintain
    topology
  • Properties
  • Scalable fully-distributed, dynamic AOI
  • Efficient low irrelevant messages, zero relay
  • Robust consistent and self-organizing
    topology

51
Potential Applications
  • Online games
  • Relieve server from position updates in current
    MMOGs
  • Military
  • Enable large-scale, affordable military training
    simulation
  • 3D Web
  • Provide multi-user interactivity to static 3D
    world
  • Scientific simulations
  • Distribute spatial simulation requiring frequent
    synchronization

52
Future Works
  • Short-term
  • Reliability measurements ? latency, packet loss,
    node fail
  • Distributed event/state consistency
  • Recovery from overlay partition
  • Long-term
  • Persistency issue (P2P-based database)
  • Security issue (protection from malicious
    nodes)
  • 3D content distribution (3D streaming on P2P)
  • Massive, persistent 3D environment sharable by
    all!

53
Acknowledgements
  • Dr. Jui-Fa Chen (?????)
  • Dr. Wei-Chuan Lin (?????)
  • Members of the Alpha Lab, TKU CS
  • Guan-Ming Liao (???)
  • Dr. Chin-Kun Hu (?????)
  • LSCP, Institute of Physics, Academia Sinica
  • Joaquin Keller (France Telecomm RD, Solipsis)
  • Bart Whitebook (butterfly.net)
  • Jon Watte (there.com)
  • Dr. Wen-Bing Horng (?????)
  • Dr. Jiung-yao Huang (?????)

54
Inconsistency caused by dAOI
55
Reliability (0-500 steps)
56
Reliability (501-1000 steps)
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