The Trend Toward Common Architectures Pete Swan, Director - - PowerPoint PPT Presentation

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The Trend Toward Common Architectures Pete Swan, Director - - PowerPoint PPT Presentation

Jul 27, 2023 371 likes •723 views

The Trend Toward Common Architectures Pete Swan, Director International Sales The Vision These efforts are focused on creating a synthetic environment that will support thousands of entities spread across many sites and provide dynamic

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SLIDE 1

The Trend Toward Common Architectures

Pete Swan, Director International Sales

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SLIDE 2

The Vision

“These efforts are focused on creating a synthetic environment that will support thousands of entities spread across many sites and provide dynamic terrain, weather, phenomena, simulated command forces, and more complex terrain. The architecture must:

  • Scale from a few simulations on a LAN through a large simulation with 100,000 entities from 50

sites.

  • Provide a real-time system.
  • Support Live, Constructive, and Virtual simulations.
  • Support environmental phenomena.
  • Support changing network technology and network topologies.
  • Reach small sites (possibly mobile) linked over low bandwidth lines.”
  • 11th DIS Workshop 1994

AGENTS: An Architectural Construct to Support Distributed Simulation James O. Calvin, MIT Lincoln Laboratory Daniel J. Van Hook, MIT Lincoln Laboratory

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SLIDE 3

Synthetic Training Environment

Common Synthetic Environment

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SLIDE 4

What is STE?

US Army’s next-generation vision for a common Synthetic Training Environment for all collective training applications:

  • STE is a collective training environment that optimizes human performance

within a multi-echelon mixed-reality environment.

  • It provides immersive and intuitive capabilities to keep pace with a

changing operational environment and enable Army training on joint combined arms operations

  • The STE moves the Army away from facility-based training, and instead,

allows the Army to train at the point of need — whether at home-station, combat training centers or at deployed locations.

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SLIDE 5

Current State of STE

Currently consists of 3 separate elements

  • Software: Common Synthetic Environment (CSE) – VT MAK
  • Hardware: Reconfigurable Virtual Collective Trainers (RVCT) – Cole Engineering Services
  • Content: One World Terrain (OWT) – Vricon

MAK was awarded the STE CSE contract on June 14, 2019 The STE CSE will be based on VR-Forces, VR-Engage, VR-Vantage, VR-TheWorld Server, and other MAK products! Other limited prototype developments are also being funded

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SLIDE 6

User Assessment 1 – November 2019

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SLIDE 7

Project/Domain-Specific Content Project/Domain-Specific Behaviors Project/Domain-Specific Features

The STE Vision

A Common Synthetic Environment and common One World Terrain underpinning the virtual simulators, IG, SAFs across all Collective Trainers

Project/Domain-Specific Content Project/Domain-Specific Behaviors Project/Domain-Specific Features IG Host Simulation SAF …

Terrain Terrain Terrain Terrain

Project/Domain-Specific Content Project/Domain-Specific Behaviors Project/Domain-Specific Features

RVCT Ground RVCT Air RVCT Soldier

IG Host Simulation SAF …

Terrain Terrain Terrain Terrain

IG Host Simulation SAF …

Terrain Terrain Terrain Terrain

OWT OWT OWT

Common Synthetic Environment

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SLIDE 8

Common Synthetic Environment Characteristics

  • Virtual simulators, CGF, and IG built on unified engine
  • Solider, ground, air simulators built on unified engine
  • Support for whole-earth geo-specific, geo-centric terrain –

and ability to load source data

  • Modular architecture / open APIs for user extension
  • Cloud and Point-of-Need deployment
  • Potential for constructive simulation on same engine
  • Innovative and agile development process
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SLIDE 9

STE Live S/SVT

Soldier / Squad Virtual Trainer

RVCT

Reconfigurable Virtual Collective Trainers

Mission Command Information Systems (MCIS) Interface to Legacy Systems (LVC-IA) Authoritative Data Sources

(e.g. Army Training Information System)

IVAS

Integrated Visual Augmentation System

OWT

One World Terrain

TSS

Training Simulation Software

TMT

Training Management Tool

CSE

Common Synthetic Environment

STE Common Synthetic Environment

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SLIDE 10

CSE Architecture

Slide content awaiting release approval.

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Hybrid Cloud Model

Mil Data Sources Training Data TMT - SimGUI TSS – SimEngines RenderEngines PlayerInterface TSS TSS

RVCT SimEngines RenderEngines PlayerInterface

TMT - SimGUI TSS – SimEngines Cache Cache Cache CSE Home Station CSE Cloud OWT Source OWT - TerrainEngine

TerrainDB

OWT - TerrainEngine

TerrainDB

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SLIDE 12

Cloud Characteristics

Takes advantage of NVIDIA GRID technology 3D graphics rendered on server side, with high-resolution video streamed to client machine Client does not need to have a high-end graphics card, and can even be a simple virtual desktop infrastructure (VDI) Supports full HLA federation, using MAK RTI, on virtual subnet on Cloud! Possible to access EXCON GUI and Role Player/Virtual Simulation from a web- browser with no plug-ins or native applications installed However, performance and user experience is better with a native application like NICE DCV (relative mouse, etc.) Mass-market technology continues to advance rapidly, and MAK is continuing to incorporate the latest technologies

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Scalability

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One Million Entities running through MAK’s new Legion scalability framework!

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SLIDE 14

Network Communication Among Sim Engine Instances, and With Virtual Simulators and Other Clients

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Sim Engine needs to efficiently simulate large numbers of entities each frame Simulation code that computes the state of each entity may require knowledge of state of other entities Sim Engine needs to communicate state of entities to Virtual Simulators and other applications For player-controlled entities, the code that computes the state of the entities requires input from Virtual Simulator Interface

Top-level Problem

Entity Entity Entity Entity Entity

Sim Engine

…

Virtual Simulator Interface

…

Virtual Simulator Interface Virtual Simulator Interface

Virtual Simulators

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Sharing the Load

  • Divide responsibility
  • Communicate state locally or over

network

Entity Entity Entity Sim Engine Instance Entity Entity Entity Sim Engine Instance Entity Entity Entity Sim Engine Instance Entity Entity Entity Sim Engine Instance

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Spatial Organization of Entities

  • Each Sim Engine simulates entities in a

specific geographic region

  • Automatic ownership transfer
  • Automatic scaling

Entity Entity Entity Sim Engine Instance Entity Entity Entity Sim Engine Instance Entity Entity Entity Sim Engine Instance Entity Entity Sim Engine Instance Entity Entity Entity Sim Engine Instance Entity

Entity Entity Sim Engine Instance Entity Sim Engine Instance Entity Entity Sim Engine Instance Entity Sim Engine Instance

Entity Entity Entity Sim Engine Instance

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SLIDE 18

Entity Entity Entity Sim Engine Instance Entity Entity Entity Sim Engine Instance Entity Entity Entity Sim Engine Instance Entity Entity Entity Sim Engine Instance Virtual Simulator Interface

Interest Management

Virtual simulators can only handle small subset of entities in scenario

  • Register interest in entities
  • Deliver only entities meeting those criteria
  • Sim Engine instances also register interest
  • nly in entities that they might need to

interact with

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SLIDE 19

Thread #1

Current Task: Compute Entity A

Thread #2

Current Task: Compute Entity B

Thread #3

Current Task: Compute Entity C

Thread #4

Current Task: Compute Entity D

Pos Ori Vel Pos Ori Vel

A P I App Code

Legion Framework Data Store Library

Data-Oriented Implementation / Object-Oriented API

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Now that Sim Engine instances have a well-defined, optimized way of storing the state of objects that it simulates, we need to communicate that data to other applications We also need a way of populating each application’s Data Store with data about entities received from other applications

A P I

Sim Engine Instance

A P I

Sim Engine Instance

A P I

Client Application

Network

Networking

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SLIDE 21

A P I

Sim Engine Instance

Network

Data Store Library

Network Library

A P I

Sim Engine Instance Data Store Library

Legion Network Library is responsible for communicating data from the in-memory Data Store to the network, and from the network for the in-memory Data Store Or could use an existing network standard – DIS, HLA, etc.

Network Library

DIS/HLA DIS/HLA Legion Legion

Legion Network Library

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Design of MAK’s “Legion” Network Architecture

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SLIDE 23

A P I

Sim Engine Instance

Network

Data Store Library

Network Library

A P I

Sim Engine Instance Data Store Library

Network Library

Entity Server

A B

Data Store Library

A B C

  • Centralized Entity Server maintains a mirror
  • f each Sim Engine’s Data Store
  • Network API abstraction allows various

network protocol choices

A B A B Network System Design

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Entity Server

A P I

Sim Engine Instance

Network

Data Store Library

Network Library

A P I

Sim Engine Instance Data Store Library

Network Library

Entity Server

A B

Data Store Library

A B C

  • When there are too many Sim Engine

instances for one Entity Server to handle, we share the load across multiple Entity Servers

A B A B

Entity Server

Network System Design

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Network

Entity Server

A P I

Client Data Store Library

Network Library

Data Store Library

A B C

Client expresses interest through Network API Network Library Data Store already coarsely organized spatially – by maintaining separate state arrays per Sim Engine instance (remember – each Sim Engine responsible for region) Network Library in Entity Server does the fine filtering against interest criteria Then builds a large message consisting just of data required by the client – using essentially the same data representation as the Data Store (no marshalling)

Network System Design

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Network

Entity Server

A P I

Client Data Store Library

Network Library

Data Store Library

A B C

Network Library Received by client’s Network Library, and placed into the Data Store ready for next frame Client code accesses data about remotely simulated entities through the same abstract Data Store API that it uses to access locally simulated entities Large message sent directly to network

Network System Design

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Review of Key Points

  • Multiple Sim Engines running in parallel
  • Spatial organization of entities among Sim Engines
  • Ownership transfer to maintain spatial coherence of entities on each engine
  • Interest management to limit how many entities are received by each client
  • Separating interface (API) from implementation so that networking specifics can be

tailored for use case and network topology

  • Dynamic link compatibility so upgrades can be plugged into applications
  • Networking and Data Store designed together to reduce marshalling/copying
  • Same compact binary representations of data used throughout the system
  • Data-oriented design to optimize Sim Engine and support multi-threading
  • Extensibility to allow for custom or extended data models
  • Stateful Entity Server reduces load on Sim Engines
  • Large message with bulk data vastly faster than per-entity packets
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DCS&S

Defence Operational Training Capability (Air) Core System and Services

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Operational Model

CENTRAL HUB

Non-Runtime System Runtime System Exercise Management Support Services

TYPHOON

Synthetic Training Equipment Exercise Management Local Client/System

Lightning

Synthetic Training Equipment

E-3D

Synthetic Training Equipment

Future Capabilities

Synthetic Training Equipment

TYPHOON

Synthetic Training Equipment

External Sites

JFST DMOC DMON

Exercise Management Local Client/System Exercise Management Local Client/System Exercise Management Local Client/System Exercise Management Local Client/System

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DOTC(A) Centralized Sim Services

Synthetic Training Platform

  • Flight Model
  • Weapons
  • Sensors
  • Mission Systems

Central Simulation Services

  • Instructor Control
  • Threat Modeling
  • Pattern of Life
  • Terrain
  • Weather
  • Comms
  • Visualization

Interface

  • Open Standards
  • Non-Proprietary
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SLIDE 31

GEMS – Generic Exercise Management System Management System

Runtime Services

Player Controls

Role Players

VR-Vantage Render Engine VR-Engage Player Interface

Simulation

VR-Forces Sim Engine

AAR

VR-Vantage Stealth

IOS

VR-Forces GUI CGF Controls

Non-Runtime Services

Scenario Generation

VR-Forces Sim Engine VR-Forces GUI Streaming Terrain Server

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VR-Forces APIs

VR-Forces Simulation Engine

Env. Comms Terrain Entity Lua Sensors

Weather Server Terrain ServerLink-16

VR-Forces APIs will be used to:

  • Connect to other services
  • Weather
  • Terrain
  • Remote Control
  • Add local content
  • Add ITAR capabilities

Behaviors & Tasks Aerodynamics and EW

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Conclusion

MAK products are being used in 2 different ways on two major programs:

  • As a suite of tools to develop an entirely new architecture and common simulation

software for the US Army’s Synthetic Training Environment

  • As the COTS core components of a large HLA federation for the UK Royal Air Force

DOTC(Air) Program

Future programs, such as the Australian Army’s LS Core 2.0, can learn from these programs how best to implement their own architectures based on their specific requirements.