Keynote 1: Discrete-event modeling and simulation for development of embedded and real-time systems

Abstract

Embedded real-time software construction has usually posed interesting challenges due to the complexity of the tasks these systems have to execute. Most methods for developing these systems are either hard to scale up for large systems, or require a difficult testing effort with no guarantee for bug-free software products. Although formal methods have showed promising results, they are difficult to apply when the complexity of the system under development scales up. Instead, systems engineers have often relied on the use of modeling and simulation (M&S) techniques in order to make system development tasks manageable. Construction of system models and their analysis through simulation reduces both end costs and risks, while enhancing system capabilities and improving the quality of the final products. M&S let users experiment with “virtual’ systems, allowing them to explore changes, and test dynamic conditions in a risk-free environment. This is a useful approach, moreover considering that testing under actual operating conditions may be impractical and in some cases impossible. In this talk, we will present a Modeling and Simulation-based framework to develop embedded systems based on the DEVS (Discrete Event systems Specification) formalism. DEVS provides a formal foundation to M&S that proved to be successful for different complex systems. This approach combines the advantages of a simulationbased approach with the rigor of a formal methodology. We will discuss how to use this framework to incrementally develop embedded applications, and to integrate simulation models with hardware components seamlessly. One of the main aspects of the methodology is that it can be integrated with models of the environment in which the embedded controller will act. We will show how the Cell-DEVS and the QSS methods can be used for this task. We will introduce the main characteristics of the Cell-DEVS and QSS methods, and will show how to model physical systems. We will introduce an integrated environment that deals with these issues, orchestrating a cellular-based simulator (CD++), a GIS (GRASS) and data visualization (Google Earth), to simulate behavior and analyze results supporting the decision making for varied environmental scenarios. Our approach does not impose any order in the deployment of the actual hardware components, providing flexibility to the overall process. The use of DEVS improves reliability (in terms of logical correctness and timing), enables model reuse, and permits reducing development and testing times for the overall process. Consequently, the development cycle is shortened, its cost reduced, and quality and reliability of the final product is improved.