SoS Architecture

Formal System Architecture Model

Overview

FireForce VI is not just a collection of components—it’s a carefully architected system-of-systems where satellites, drones, AI, ground stations, and human commanders work in orchestrated harmony. The SoS Architecture work package creates the authoritative formal model of this complex system using the Ontological Modeling Language (OML), capturing everything from stakeholder needs to component behaviors, from mission scenarios to interface specifications. This model serves as the single source of truth, enabling automated analysis, code generation, verification, and traceability across the entire FireForce VI ecosystem. It is developed in the Modeling Environment and validated through SoS Integration.

The Challenge

Architecting a system-of-systems like FireForce VI requires:

• Comprehensive Modeling: Capturing stakeholders, requirements, capabilities, and behaviors
• Multiple Perspectives: Concept of operations, functional, logical, and physical views
• Formal Specification: Machine-readable, analyzable, and verifiable models
• Autonomous Behavior: Modeling complex AI-driven decision-making and coordination
• Requirements Traceability: Linking needs to capabilities to implementations
• Separation of Concerns: Clear boundaries between system and subsystem responsibilities
• Simulation Integration: Generating code for digital twin validation
• Continuous Verification: Automated checking of architectural consistency

Traditional document-based systems engineering cannot provide the rigor, automation, and analysis capabilities needed for safety-critical autonomous systems at this scale.

Core Capabilities

1. Comprehensive Modeling Vocabulary (OML)

Stakeholder & Needs Modeling

• Stakeholder identification and roles
• Stakeholder needs and concerns
• Value propositions and benefits
• Constraints and limitations
• Success criteria definitions
• Acceptance criteria

Mission & Scenario Modeling

• Operational concepts
• Use case specifications
• Mission scenarios and sequences
• Operational modes
• Environmental conditions
• Edge cases and contingencies

Capability Modeling

• System capabilities and features
• Performance parameters
• Quality attributes
• Service definitions
• Capability dependencies
• Capability evolution

Requirements Modeling

• Functional requirements
• Non-functional requirements
• Interface requirements
• Constraint specifications
• Verification methods
• Traceability relationships

2. Concept of Operations (ConOps)

Mission Context

• Strategic objectives
• Operational environment
• User communities and roles
• Operational scenarios
• Success metrics
• Constraints and assumptions

System Responsibilities

• FireForce VI vs. external systems
• Human vs. autonomous functions
• System boundaries and interfaces
• Authority and control
• Information flows
• Coordination mechanisms

Operational Modes

• Normal operations
• Degraded modes
• Emergency procedures
• Maintenance and support
• Training and simulation
• Evolution and upgrade paths

Stakeholder Descriptions

• Fire commanders and personnel
• Emergency management agencies
• Civil authorities
• Affected communities
• System operators and maintainers
• Regulatory bodies

3. Multi-Level System Architecture

Functional Architecture

• System functions and capabilities
• Functional decomposition hierarchy
• Function allocation to components
• Data and control flows
• Functional interfaces
• Behavioral specifications

Logical Architecture

• Logical components and services
• Component responsibilities
• Interface contracts
• Message flows and protocols
• State machines and behaviors
• Coordination patterns

Physical Architecture

• Hardware platforms (satellites, drones, ground stations)
• Software modules and deployment
• Network topology
• Physical interfaces
• Resource allocation
• Deployment configurations

4. Automated Analysis Viewpoints

Requirements Analysis

• Completeness checking
• Consistency verification
• Traceability validation
• Coverage analysis
• Conflict detection
• Verification status tracking

Interface Analysis

• Interface specification completeness
• Protocol compatibility checking
• Data type consistency
• Message flow validation
• Coupling analysis
• Integration point identification

Behavioral Analysis

• State machine validation
• Deadlock detection
• Liveness properties
• Safety properties
• Timing analysis
• Autonomous behavior verification

Architecture Quality

• Complexity metrics
• Coupling and cohesion
• Modularity assessment
• Reusability analysis
• Maintainability indicators
• Performance predictions

Traceability Reports

• Need-to-requirement traces
• Requirement-to-design traces
• Design-to-implementation traces
• Test-to-requirement coverage
• Change impact analysis
• Gap analysis

5. System Integration & Code Generation

Simulation Framework Integration

• Generate simulation configurations
• Export behavior models
• Create interface stubs
• Produce test harnesses
• Generate documentation
• Synchronize with digital twin

Configuration Management

• Version control integration
• Baseline management
• Change tracking
• Impact analysis
• Release management
• Variant management

CI/CD Pipeline Integration

• Automated model validation
• Continuous consistency checking
• Nightly analysis reports
• Regression detection
• Quality gate enforcement
• Deployment automation

Technical Architecture

Modeling Framework

• Language: Ontological Modeling Language (OML)
• Tool: Custom OML IDE or Eclipse-based environment
• Storage: Git repositories for version control
• Database: Triple store for semantic queries
• Validation: OML consistency checker
• Export: Multiple formats (JSON, XML, RDF)

Analysis Engine

• Query Language: SPARQL for semantic queries
• Reasoning: Ontology reasoner (HermiT, Pellet)
• Analysis Scripts: Python or Jupyter notebooks
• Viewpoints: Markdown with embedded queries
• Visualization: GraphViz, PlantUML, custom
• Reports: Automated HTML/PDF generation

Integration Layer

• Version Control: Git with LFS for large models
• CI/CD: GitHub Actions, GitLab CI, Jenkins
• Simulation Export: Code generation for digital twin
• Requirements Tools: DOORS, Jama integration (optional)
• Documentation: Automated doc generation
• APIs: RESTful API for model queries

Success Metrics

Metric	Target	Measurement Method
Vocabulary Coverage	100% of concerns	Stakeholder review
Model Completeness	No critical gaps	Automated checking
Traceability	100% requirements traced	Traceability analysis
Analysis Automation	Daily CI/CD runs	Pipeline monitoring
Code Generation	Simulation framework sync	Integration testing
Consistency	Zero critical violations	Validation reports

Technical Challenges

1. Modeling System Autonomous Behavior

• Challenge: Formally specifying complex AI-driven decision-making, multi-agent coordination, and emergent behaviors in a way that’s analyzable and verifiable
• Approach: Hierarchical state machines, goal-based specifications, behavior trees, temporal logic constraints, probabilistic modeling
• Skills Required: Formal methods, autonomous systems, AI architectures, behavioral modeling

2. Capturing Verifiable Requirements

• Challenge: Writing requirements that are unambiguous, testable, and formally linked to both stakeholder needs and architectural elements
• Approach: Structured natural language, formal requirement patterns, verification method specification, automated completeness checking
• Skills Required: Requirements engineering, formal specification, verification methods, test design

3. Separation of System and Subsystem Concerns

• Challenge: Maintaining clear architectural boundaries between FireForce VI as a whole and its constituent systems (satellites, drones, etc.) while managing their interactions
• Approach: Interface-based design, contract specifications, responsibility allocation matrices, architectural views, encapsulation principles
• Skills Required: Systems architecture, interface design, modular design, systems thinking

4. Interfacing with Simulation Framework

• Challenge: Automatically generating simulation code, configurations, and interfaces from the architectural model while maintaining consistency
• Approach: Model-driven engineering, code generation templates, bidirectional synchronization, transformation rules, validation hooks
• Skills Required: Model-driven development, code generation, simulation frameworks, toolchain integration

Team Structure

Required Roles

• Systems Engineering Specialist
• Requirements Engineer
• Model-Based Design Expert
• Verification & Validation Engineer

Optional: Tooling Engineer

• CI/CD pipeline setup
• Code generation development
• Analysis automation
• Tool integration
• Custom extensions

Deliverables

1. OML Vocabulary - Comprehensive modeling language for FireForce VI
2. ConOps Model - Formal concept of operations specification
3. System Architecture Model - Functional, logical, and physical views
4. Requirements Model - Complete requirements specification with traceability
5. Analysis Viewpoints - Automated analysis reports (Markdown + queries)
6. Code Generators - Simulation framework integration
7. CI/CD Pipeline - Automated validation and reporting
8. Documentation - Generated architecture documentation

Technology Stack Recommendations

• Modeling: OML (Ontological Modeling Language)
• IDE: VS Code with OML extension, or Eclipse-based
• Storage: Git, GitHub/GitLab
• Ontology DB: Apache Jena, Blazegraph, or GraphDB
• Query: SPARQL
• Analysis: Python, Jupyter notebooks
• Visualization: Graphviz, PlantUML, Mermaid
• CI/CD: GitHub Actions, Jenkins
• Documentation: Markdown, Sphinx, Hugo

Integration Points

• System Modeling Environment - Tool for creating and editing models
• Digital Twin - Target for code generation
• Testing Platform - Requirements verification
• Project Management - Requirements tracking
• All SoS Work Packages - Architecture specifications

Architecture Views

System Context View

• External systems and actors
• System boundaries
• Key interfaces
• Information flows
• Authority relationships

Functional View

• Capability decomposition
• Function allocation
• Data flows
• Control flows
• Behavioral specifications

Logical View

• Component organization
• Service interfaces
• Message protocols
• State machines
• Coordination patterns

Physical View

• Hardware platforms
• Software deployment
• Network topology
• Resource allocation
• Physical constraints

Behavioral View

• Operational scenarios
• State transitions
• Timing sequences
• Failure modes
• Recovery procedures

Learning Outcomes

Participants will gain expertise in:

• Model-based systems engineering (MBSE)
• Ontological modeling
• Requirements engineering
• System architecture design
• Formal verification methods
• Model-driven engineering
• Automated analysis techniques
• Systems thinking and design

Industry Relevance: SoS Architecture applies MBSE techniques used in aerospace (Boeing 787, F-35), defense systems (US DoD Architecture Framework), automotive (ISO 26262), and space programs (NASA Mars missions), creating expertise in formal systems engineering and architecture methods.

Architecture Principles

Modularity

• Clear component boundaries
• Well-defined interfaces
• Loose coupling, high cohesion
• Encapsulation of complexity

Openness

• Published interface specifications
• Standard protocols and formats
• Modular Open Systems Approach (MOSA)
• Technology insertion flexibility

Scalability

• Graceful scaling of capabilities
• Resource-elastic design
• Performance predictability
• Growth accommodation

Resilience

• Fault tolerance
• Graceful degradation
• Self-healing mechanisms
• Redundancy where critical

Validation Approach

Model Validation

• Stakeholder review sessions
• Completeness checking
• Consistency verification
• Traceability validation

Architecture Validation

• Interface compatibility checking
• Behavioral simulation
• Performance analysis
• Trade-off studies

Requirements Validation

• Verification method review
• Testability assessment
• Coverage analysis
• Acceptance criteria validation

Integration Validation

• Simulation code generation
• Digital twin synchronization
• Interface testing
• End-to-end traceability

Foundational Role: The SoS Architecture is the blueprint that transforms FireForce VI from concept to reality. It provides the formal specification that guides all development, enables automated verification, ensures consistency across teams, and creates the traceable evidence needed for certification and deployment of this safety-critical autonomous system.