Migrating Traditional Automotive Applications to Service-Oriented Architectures Using MATLAB & Simulink

Signal Oriented & Service Oriented Architectures_

This white paper explains how to modernize legacy software with a model-based workflow to move from monolithic to modular, scalable SOA systems.

  • 1036

As the automotive industry shifts toward software-defined vehicles, OEMs and suppliers face a common challenge: how to modernize legacy software for today’s service-oriented architectures (SOAs). 

This white paper explains how to modernize legacy software for today’s SOAs. It lays out a practical, model-based workflow to help engineering teams transition from tightly coupled, monolithic systems to modular, service-based architectures. This transition is driven by the adoption of modern software architecture, which enables greater modularity, scalability, and standardization in automotive systems without starting from scratch. 

Why it matters 

Modern vehicle platforms, especially those using HPCs and zonal controllers, now demand new software strategies. Legacy ECU code, built around signal-based communication and rigid execution patterns, just isn’t designed for SOAs. Meanwhile, rewriting everything to suit them is rarely feasible. 

This white paper offers a roadmap for migrating existing applications by restructuring them into reusable services and enabling message-based communication—all within a simulation-driven development process. 

What you’ll learn 

While the full white paper dishes up all of the details, here are a few takeaways: 

  • How to shift from signals to messages using DDS or AUTOSAR Adaptive; 
  • How to modularize legacy software into independent, testable services; 
  • How to simulate and validate service interactions before deployment; 
  • How tools like Simulink® and System Composer™ fit into the process by enabling engineers to author models and services within a structured, model-based design framework; and 
  • How to generate C++ code ready for service-based architectures. 

The paper is especially relevant if you’re working on embedded applications for HPCs or zonal controllers and need to adapt your software development practices accordingly. 

Model-Based Design makes it possible 

At the heart of the workflow is Model-Based Design. By using models to define, simulate, and generate code, teams can ensure early integration testing, easier reuse across programs, and smoother migration to modern platforms. 

Rather than diving into code refactoring first, the approach emphasizes simulation and architecture modeling, which make the migration more predictable and less risky. 

Decomposition and design: Breaking down legacy applications for SOA 

Migrating traditional automotive applications to service-oriented architectures (SOA) means decomposing monolithic application software into modular SOA applications. This process enables flexible, scalable software architectures essential for software-defined vehicles. 

Using Model-Based Design and System Composer, engineers can decompose legacy applications by identifying services, defining interfaces, and modeling dependencies. This approach supports reuse and simplifies integration across platforms, making it easier to update and maintain application software within evolving SOA frameworks. 

Configuring services for AUTOSAR Adaptive applications 

Configuring services for AUTOSAR Adaptive is a crucial step in building service-oriented architectures for software-defined vehicles. Using Model-Based Design and System Composer, developers define and configure application software as AUTOSAR Adaptive services. This involves mapping service interfaces and ports according to AUTOSAR Adaptive standards to ensure proper communication and integration. 

System Composer’s AUTOSAR editor streamlines the alignment of services with platform requirements, while Simulink enables simulation and validation before deployment. This approach supports modular, reusable software architectures that can be deployed efficiently across high-performance computing platforms in SDVs, enabling scalable and maintainable SOA applications. 

Get the full story 

If your team is navigating the shift to service-oriented architectures, this paper is a must-read. It offers structured guidance grounded in real-world engineering practice, not just theory.  

Download the white paper

Please fill out the form below to gain access to the file.


Featured products

All products mentioned are developed by MathWorks®:

Learn more

  • Blog: Software-Defined Vehicles: The New Era of the Automotive Industry
    SDVs are transforming how cars operate and perform. Unlike traditional vehicles, they rely on advanced software to deliver continuous over-the-air updates, introduce new features, and enhance safety. In this article, we’ll look at their key benefits, technological advancements, and what the future holds for this exciting innovation.
    Read more
  • Beyond the Hype: How OEMs Actually Deliver a Software-Defined Vehicle
    A Software-Defined Vehicle (SDV) uses software to control its key functions instead of relying solely on hardware. This article explains how SDVs work, their main components, and the challenges in developing them.
    Read more
  • On-Demand Webinar: Driving the Future: An On-Demand Webinar on Software-Defined Vehicles
    Explore the strategic and technical foundations of SDVs and explain how modern architectures and tools are enabling faster, more modular, and scalable automotive development.
    Watch here
  • Workshops: Designing Service-Oriented Architectures for SDVs with MathWorks Tools: A Hands-On Approach
    Get actionable insights and a clear technical roadmap to move from outdated designs to scalable, service-based architectures.
    Register here

 

Recommended Events

Recommended Posts

Ai robotics working on a car

AI: Driving the Industry Towards Greater Success

Artificial intelligence (AI) is seen as a promising technology that can help leading OEMs to maintain their position as market leaders. In this post, read about how AI is changing the manufacturing sector, as well as its potential advantages and potential drawbacks.

MATLAB and Simulink for Automotive

MATLAB and Simulink for Automotive

Discover how MATLAB and Simulink drive automotive innovation. Learn how these tools expedite vehicle development and help OEMs meet evolving market demands.