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

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Presentation transcript:

1 By Vanessa Newey

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

3 Distributed Interactive Simulation Systems Include:  Multiplayer Video Games,  Collaborative Engineering  Military and Industrial training Systems are Growing Can be hundreds of thousands of dynamic entities

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5 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

6 Limits to Scalability Host has to:  Receive updates  Model and render scene  Other tasks, including collision detection So…as the number of entities increases Increased Load on Network Resources. Increased Computational Load

7 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

8 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

9 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

10 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.

11 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.

12 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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14 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

15 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

16 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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18 All entities treated as P rojection 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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21 Heirachical P rojection 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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25 Experience with P rojection 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

26 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

27 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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