1 By Vanessa Newey. 2 Introduction Background Scalability in Distributed Simulation Traditional Aggregation Techniques Problems with Traditional Methods.

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By Vanessa Newey

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Introduction

Background Scalability in Distributed Simulation Traditional Aggregation Techniques Problems with Traditional Methods Projection Aggregation Future Directions Summary

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Distributed Interactive Simulation Systems Include:

Multiplayer Video Games, Collaborative EngineeringMilitary and Industrial training

Systems are Growing Can be hundreds of thousands of dynamic

entities

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Scalability in Distributed Simulation Number of entities that may simultaneously

participate in the system. Entity = participating object that is separately

modeled. Scalability depends on

Network Capacity Processor capabilities Rendering speeds Speed of throughput of shared servers

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Limits to Scalability

Host has to:Receive updatesModel and render scene Other tasks, including collision detection

So…as the number of entities increases Increased Load on Network Resources. Increased Computational Load

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Limits to Scalability cont.

Even with dead-reckoning on a large simulation >125,000 packets/second

Approaching limit of interrupts for a general-purpose processor

Rapidly increasing Computational Load due to: Increasing number of entities Increasing detail of entity models More fine-grained graphical representations

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Aggregation

Used to reduce network and computational load.

“An aggregations is a simulation entity that represents a group of other entities.”

Previously used aggregation techniques are organisational and grid location

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Organisational Aggregation Groups entities by their organisational structure.

e.g. armies, brigades, battalions etc Easy to construct An organisation’s members may be dispersed

throughout regions of the VR world In military simulations up to half the entities are

destroyed Each host has to receive information from all

organisation represented within that region Does not sufficiently reduce network traffic or the

computational load

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Grid Aggregation Groups entities by their location within the virtual

world. Virtual world divided into regions, each is

associated with an aggregation that transmits information about entities in that region

Masks organisational structure For a host to send summary information about a

battalion of tanks, then it must subscribe to information from all regions that could potentially contain one of those tanks.

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Grid Aggregation cont. Does not allow remote hosts to receive different

fidelity information for different entity types. Does not allow hosts to access entities by their

organisation or type, so limited value for reducing network traffic or computational load.

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Projection Aggregation Unifies the organisational and grid

aggregation strategies. Each projection aggregation includes

entities from a single organisation located within a single grid of the virtual world.

Oraganisation is “projected” onto the virtual world.

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Projection Aggregation cont. Each periodically transmits summary information

about its members across the network. Hosts use projections to represent groups of

remote entities that do not merit local modeling at high detail because far from viewer or

Useful abstraction for describing all entities in a simulation

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Projection Aggregation Summary Protocol Each periodically summarises its member entities Transmits summary packets over an associated

multicast address. Enough information in packets for remote hosts

to generate a low fidelity model of those member entities.

Transmitted relatively infrequently (2-3 seconds) Regular entities transmit every second Errors not noticeable

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Projection Aggregation Summary Packets Contain

count of entities represented a single position point (average position) Radius of bounding sphere Distribution information (mean, standard deviation)

On remote host to place each entity the simulation generates a

distribution of locations within the bounding sphere, given the mean and standard deviation.

Projection aggregation’s center point and mean distance can be dead reckoned.

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All entities treated as Projection Aggregation

All entities can be treated as projection aggregations Only the rendering algorithm is different Remote hosts can dynamically change the fidelity of their

local entity model without impacting other hosts Projections are easily integrated into existing

simulations. Provides a natural mechanism for introducing more

detailed entity models into an existing simulation.

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Heirachical Projection Aggregation Projection Aggregations are arranged in a heirachy A projection aggregation is associated with a parent

aggregation (a broader organisation and a larger grid. Each organisation maintains links to all its descendent

entities. Grids maintain links to all projections in that grid Allows top-level filtering, reducing processing Collision detection algorithms can use projection

aggregations to quickly filter unlikely or uninteresting collisions.

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Experience with Projection Aggregations Used in PARADISE distributed simulation to

assess the effectiveness of projections 72% less packets. Host’s multicast subscriptions down by 40% Implemented and managed in roughly 4000 lines

of code

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Conclusion

Projections provide a single abstraction for all simulation entities.

Design allows hosts to view each entity in several ways: Part of an organisation Part of a world Grid Part of a projection aggregation summary

Projection aggregations reduce both network and computational requirements.

A promising technique for network and computational resources

support the evolution of more detailed entity models

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More recently

MASSIVE-3 uses abstraction as well, but more spatially focused

In Singhal’s book he describes a slightly different approach. Where objects subscribe information sets.

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