Networked VR Ashweeni Beeharee Ashweeni Beeharee VE Course - - - PDF document

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Networked VR

Ashweeni Beeharee

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Content

Networked VR scenarios Architectures

Peer-to-peer

Consistency

Full Partial Predicted

Conclusion

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Helicopter Maintenance

Assembly of a helicopter engine Participant across continents

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The Diamond park

Cycling around the park Multiple users Voice support

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The Oil Platform

Multi-user simulation exercise Use of haptic device + HMD

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Multiplayer Game

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Nature of a Networked Virtual Environment

Multiple user – geographically distributed More types of interactions

Passive navigation Single object/multiple user Multiple objects/multiple users

Voice link between participants Heterogeneous immersion devices

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Concerns for designers

Immersion and embodiment

In-body vs out-body

Presence and shared presence User expectation

Things should look natural

Adaptation

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Demands

Provide up-to-date info to all participants

Users location Support Interactions

Minimal delay update Support multiple message type

Simple state Voice/video

Consistency is Very important

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Architecture

You already know about networking! Peer-to-Peer Client/Server Distributed

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• Total Replicated Database
• Simple Extension to Single Users
• Initial Multi-Participant VE

Simple Peer-to-Peer

DB DB

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Multiple Peer-to-Peer

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Client-Server Architecture

Client Server

• Database on Server with Shadow Copy on Clients
• Current Online Games
• Some VE (MASSIVE,Deva)

DB

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Client-Server Architecture

Server Client Client Client Client

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Distributed Architecture

• Total Replicated or Partial Database
• Most Virtual Environments (DIVE, NPSNET)

DB

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How do these architecture measure up?

Up-to-date information

Synchronisation in peer-to-peer impossible – no

absolute reality!

Interaction

Client/Server provides central locus of control –

constraint resolution

Consistency!

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Consistency : Reality

GOLDEN RULE Information propagation IS NOT instantaneous

It is not possible for It is not possible for EVERY EVERY user to share the user to share the EXACT EXACT same state at same state at EVERY EVERY instance instance

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State Consistency: Case 1 (Total Sync) State Consistency: Case 1 (Total Sync)

T = t Acknowledge every update Propagation delay is 100ms Client A Client B

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State Consistency: Case 1 State Consistency: Case 1

Client A Client B T = t + 50ms

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State Consistency: Case 1 State Consistency: Case 1

Delta T Client A Client B T = t + 50 ms + 100 ms

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State Consistency: Case 1 State Consistency: Case 1

T = t + 50ms + 100ms + 50ms + 100ms T = t + 300ms After 300ms Client A may move again!!! Client A Client B Delta T

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State Consistency: Case 2 (Async) State Consistency: Case 2 (Async)

T = t Local update every 150ms Propagation delay is 100ms Client A Client B

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State Consistency: Case 2 State Consistency: Case 2

T = t + 100ms Client A Client B

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State Consistency: Case 2 State Consistency: Case 2

T = t + 150ms Client A Client B

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State Consistency: Case 2 State Consistency: Case 2

T = t + 250ms Client A Client B Delta T

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State Consistency: Case 2 State Consistency: Case 2

T = t + 300ms Client A Client B

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State Consistency: Case 2 State Consistency: Case 2

T = t + 400ms Inconsistency!!! Client A Client B Delta T Delta T

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State Consistency: Problem State Consistency: Problem

Network propagation > 100ms Network is congested -> retransmission Players >> 2

Consistency Update Frequency

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State Consistency: Total Consistency State Consistency: Total Consistency

Provided by Client/Server Architecture

Server controls total consistency of

database

Communication is reliable Each Client reads from Server Client sends updates to Server (dirty

cache)

Events are totally ordered

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State Consistency: Total Consistency State Consistency: Total Consistency

Pros

Guaranteed ordered event processing Implicit ownership

Cons

Latency penalty: 2 Round Trip Time Reliability not always compatible with real-time (msg +

ack)

Poor scalability Server is bottleneck Server is single point of failure

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State Consistency: Eventual Consistency State Consistency: Eventual Consistency

Clients just send periodic updates Discrepancy is tolerated if:

Does not exceed a given time threshold Does not dramatically a perceptual error threshold

Clients do not need acknowledgements A client is unawares of other clients Inconsistency inversely proportional update

frequency

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State Consistency: Eventual Consistency State Consistency: Eventual Consistency

Pros:

Minimum latency No infrastructure -> reduced processing overhead Simple to upgrade a single user system to multi users No bottleneck Fault tolerant (no packets -> remove entity)

Cons:

Explicit ownership Bandwidth hungry (high frequency for low inconsistency) Better scalability but still poor

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State Consistency: Predicted Consistency State Consistency: Predicted Consistency

Facts:

Users are not aware of other users Total consistency is not a requirement But eventual consistency has problems

Possible solution: Possible solution:

• Dead reckoning

Dead reckoning

• High level behaviours

High level behaviours

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State Consistency: Predicted Consistency State Consistency: Predicted Consistency

Dead reckoning I

Client A Client B Ghost A Ghost B Movement Model: P(t) = P(t0) + v*t P(t) = P(t0) + v*t + 0.5 * a * t2

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State Consistency: Predicted Consistency State Consistency: Predicted Consistency

Dead reckoning II

Client A Simulation If new pos does not exceed error threshold then do nothing If new pos does exceed error threshold then send new position

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State Consistency: Predicted Consistency State Consistency: Predicted Consistency

Dead reckoning III - convergence

T = t

OR

T = t T = t+1 T = t+2

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State Consistency: Predicted Consistency State Consistency: Predicted Consistency

High level behaviours (Games)

Position A Position B

• At each game interval send current position packet
• If path takes 30 seconds and game tick is 10 per second
• You have 300 packets being sent

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State Consistency: Predicted Consistency State Consistency: Predicted Consistency

High level behaviours (Games)

Position A Position B

• Just send Destination Position B
• Use path finding to compute best path
• Not all users will see same path
• But all will see final result
• Send 1 packet only with parameters

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Twines

Derive function which represents complex

path

Send the function over in a single message

Twine

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Interaction

Passive navigation

Consistency requirement minimal Delays

User/User – gesture Point and Shoot Collaboration

Single object/multiple user Multiple objects/multiple users

What is the impact of network problems on these?

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Constraint resolution

Collaborative manipulation

Where is the resolver? – local/remote Impact of Round-trip time Object ownership

But how about finite lag?

Minimising decoupling by using spring paradigm

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Summary

Networked VR

allows new possibilities for interaction Poses new challenges to VR designers

Three types of architectures exist and their

suitability depends on the target application

Consistency is at the heart of networked VR Perfect system not always possible

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The ultimate application?