Systematic Evaluation of Sandboxed Software Deployment for Real-time Software on the Example of a Self-Driving Heavy Vehicle

TL;DR

This study systematically evaluates sandboxed software deployment in a self-driving heavy vehicle, demonstrating that sandboxing does not significantly impact performance, thus supporting modern software engineering practices in cyber-physical systems.

Contribution

It provides empirical evidence that sandboxed deployment in real-time automotive systems maintains performance, enabling safer and more flexible software updates.

Findings

No significant performance difference with sandboxing

Sandboxing does not add notable overhead

Supports microservices approach in cyber-physical systems

Abstract

Companies developing and maintaining software-only products like web shops aim for establishing persistent links to their software running in the field. Monitoring data from real usage scenarios allows for a number of improvements in the software life-cycle, such as quick identification and solution of issues, and elicitation of requirements from previously unexpected usage. While the processes of continuous integration, continuous deployment, and continuous experimentation using sandboxing technologies are becoming well established in said software-only products, adopting similar practices for the automotive domain is more complex mainly due to real-time and safety constraints. In this paper, we systematically evaluate sandboxed software deployment in the context of a self-driving heavy vehicle that participated in the 2016 Grand Cooperative Driving Challenge (GCDC) in The Netherlands. We measured the system's scheduling precision after deploying applications in four different execution environments. Our results indicate that there is no significant difference in performance and overhead when sandboxed environments are used compared to natively deployed software. Thus, recent trends in software architecting, packaging, and maintenance using microservices encapsulated in sandboxes will help to realize similar software and system engineering for cyber-physical systems.