The Trend Toward Common Architectures Peter Swan Director - - PDF document

IT2EC 2020 The Trend Toward Common Architectures Architecture & Interoperability

The Trend Toward Common Architectures

Peter Swan Director International Sales, Cambridge MA, USA

Abstract — Defense forces around the world are starting to realize the benefits of a common distributed simulation architecture for collective training, whether in the land or air domain. Leaders are frustrated by having to pay for terrains and models multiple times, spending time and effort attempting to federate incompatible training systems, and being unable to guarantee a fair fight between these systems. This paper will describe the different architectural approaches taken to resolve these issues and to deliver collective training on two current programs that MAK is involved in.

1 Introduction

The benefits of distributed simulation have been well known, even since the early days, epitomized by the Defense Advanced Research Projects Agency (DARPA), SIMNET (SIMulation NETworking) Program [1]. Those early systems struggled with high latencies and a lack of

• bandwidth. It was not feasible to transmit large quantities
• f data around – just the bare minimum needed for

distributed simulations to interoperate. However, the advent of fiber networks providing 200+ Mbs into our homes, and the availability

• f

pervasive cloud environments, is making simulation-based training available at the point of need, as well as enabling distributed, collective training. This presentation will describe two specific programs and how they are leveraging modern networking and cloud environments to deliver training.

2 The US Army Synthetic Training Environment

2.1 STE Overview The US Army initiated the Synthetic Training Environment effort in 2016 with the mission of providing a cognitive, collective, multi-echelon training and mission rehearsal capability for the Operational, Institutional and Self-Development training domains; of converging the virtual, constructive and gaming training environments into a single Synthetic Training Environment (STE) for Active and Reserve Components as well as civilians; and to provide training services to ground, dismounted and aerial platforms and command post (CP) points-of-need (PoN) [2]. After evaluating initial prototypes, VT MAK was selected to deliver the Training Simulation Software (TSS) and Training Management Tool (TMT) components

• f the STE Common Synthetic Environment (CSE).

2.2 STE CSE System Architecture The STE vision is to develop and deliver a Common Synthetic Environment and common One World Terrain underpinning the virtual simulators, semi-automated forces and rendering engines across all future US Army collective trainers. This next generation collective training software has the following attributes:



A Computer Generated Forces (CGF) application and a multi-role virtual simulator application, built on a common unified simulation engine running in the cloud and on edge computing systems



A multi-role virtual simulator, Image Generator (IG), scenario authoring tool, Instructor Operator Station (IOS), and After-Action Review (AAR) suite, built on a common unified visualization engine that renders 3D scenes in realistic detail



A common unified terrain engine embedded in all of the components above, allowing them to natively operate on whole-earth WGS-84 terrains



A whole-earth terrain server that can host global terrains at the required fidelity, and serve terrain information through open industry standards to the various STE components



An open systems architecture with a suite of documented APIs, SDKs, and editors to allow users to customize, extend, and adapt any elements of these systems, and to directly integrate new simulation models into both the CGF and the virtual simulators



A truly modular architecture that supports scalability by combining multiple instances of the simulation engine to share the simulation load and communicate with each other through a common, network-protocol-independent interface



A hardware-independent interface that supports a variety of input and output devices, including virtual reality (VR) and augmented

IT2EC 2020 The Trend Toward Common Architectures Architecture & Interoperability reality (AR) head-mounted displays (HMDs), multi-projector domes, motion platforms, and immersive cabins and cockpits. 2.3 Hybrid Cloud Model The system architecture is based on a hybrid cloud model, with the flexibility to enable training wherever it is needed, whether at the point of need, at homestation, in a training center, or distributed across many sites. The architecture must support the processing where it is needed for optimal performance. For example:  rendering is done locally on edge computers for Mixed Reality applications using headsets, to avoid delays and jitter caused by the network, but can be done remotely in a cloud for desktop training applications.  Simulation is conducted locally for small local exercises when connectivity is missing, but can run entirely in the cloud for large constructive simulations. A holistic Training Management Tool (TMT) will handle the planning, preparation, execution, and assessment of these exercises whether local or distributed, on a LAN or in the cloud. It will use an Intelligent Tutoring/AI system to take the training developer through the process of developing the complete required Training Support Packages; scheduling and allocating resources; initializing and monitoring the system; executing the exercise; and performing assessment of individuals, teams and the training itself. 2.1 Scalability At Initial Operating Capability (IOC) the architecture will support up to 80,000 entities for a Brigade level exercise, with the capacity to support millions of entities representing a city’s population. This will be achieved by utilizing multiple simulation engines running in parallel and taking advantage of:  Spatial Organization – responsibility for simulating entities is shared across multiple simulation engines, each covering a specific geographic area.  Ownership transfer - ownership is transferred from one simulation engine to another as the entity moves from one region to another.  Load balancing - the size of the region covered by a simulation engine is automatically adjusted based on the density of entities in the region.  Interest Management – the simulation clients register interest in entities based on certain criteria, typically only those that they might interact with. Within a High Level Architecture (HLA) federation, the simulation engine will support on the order of 50,000 complete and intelligent semi-automated entities, constrained largely by the fact that HLA transmits data separately for each entity. For larger entity counts, MAK is developing a scalability architecture we are calling Legion. A centralized Entity Server maintains a mirror of each Sim Engine’s Data

• Store. Data stays in the same contiguous layout all the

way from the Sim Engine’s Data Store, to the network, to the Entity Server’s Data Store. This eliminates expensive marshalling and copying. Network API abstraction allows various network protocol choices. The default TCP implementation ensures reliability (even over WANs), and allows the efficiency of sending large packets that include many entities’ state. When there are too many Sim Engine instances for one Entity Server to handle, the load is shared across multiple Entity Servers. The Entity Server filters the data against interest criteria, builds a large message of just the data required by a particular client, and sends the message directly to the network.

3 UK DOTC(AIR)

In May 2019, the UK RAF awarded Boeing Defence UK the contract to deliver the Defence Operational Capability (Air) Core System and Services (DCS&S). The DCS&S contract will create a capability, known as Gladiator, that will support multiple complex training scenarios, simultaneously and independently of each other. The system will allow personnel at different sites to train together in their own high-fidelity simulators, linked by a secure network to a new hub at RAF Waddington. The system will securely manage training events across locations and classification levels, allowing RAF crews to experience the same battle environment and threats, including in joint training with their counterparts in the United States. So, rather than a clean sheet, new architecture as envisioned for STE, DCS&S will link together existing and new training centers developed by different suppliers such as BAE Systems, Boeing, CAE and Thales. It will need to resolve the correlation and ‘fair fight’ issues created when different simulations are linked together. The DOTC(Air) network will be implemented using the High Level Architecture (HLA) standards specified in the NATO Education and Training Network (NETN) federation agreement document. It will provide centralized services for instructor control, threat modelling, pattern of life, terrain, weather, communications and visualization. DCS&S will provide the common Computer Generated Forces application, Image Generator, and Role Player Stations for UK RAF distributed training exercises based

• n MAK’s COTS products, extended to support Tactical

IT2EC 2020 The Trend Toward Common Architectures Architecture & Interoperability Data Links and high fidelity flight and electronic warfare models. Boeing will deliver Generic Exercise Management Systems (GEMS) at the central hub and at each main

• perating base. The GEMS will be reconfigurable for

scenario generation, After Action Review and as an Instructor Operator or Role Player Station. Terrain – imagery, elevation, and features including roads, buildings and trees - will be stored centrally in standard GIS formats and streamed to the local federates using Open Geospatial Consortium (OGC) protocols TMS and WMS-C. Whole-Earth terrains will be procedurally generated from GIS data streamed from the terrain server, with the addition of cut-in high-resolution site models. A weather server will provide centralized environment services to the federation.

4 Conclusion

Two major simulation-based training programs have chosen significantly different approaches to meeting their distributed simulation requirements:  The US Army is developing an entirely new architecture and common simulation software for the Synthetic Training Environment; and  The UK Royal Air Force has developed the concept of an HLA based federation linking together and providing centralized services for existing and new training centers for the DOTC(Air) Program. Future programs, such as the Australian Army’s LS Core 2.0, can perhaps learn from these programs how best to implement their own architectures based on their specific requirements.

References

[1] D.C. Miller, SIMNET and Beyond: A History of the Development of Distributed Simulation, I/ITSEC (2015) [2] PEO STRI Website: https://www.peostri.army.mil/synthetic-training- environment-ste-

Author/Speaker Biography

Peter Swan is Director of International Sales at VT MAK, a company that develops software to link, simulate, and visualize the virtual world. Mr. Swan has more than 37 years of experience in the modeling and simulation industry in various technical and managerial roles. He has specialized in the development, sales, and product management of modeling and simulation, networking, and synthetic environment software products, in the UK, Canada, and the US.