Spatio-Temporal Analysis of Concurrent Networks

TL;DR

This paper focuses on modelling spatio-temporal properties and their model-checking and simulation using different analysis tools in combination with the methods and tool extensions proposed here.

Abstract

Many very large-scale systems are networks of cyber-physical systems in which humans and autonomous software agents cooperate. To make the cooperation safe for the humans involved, the systems have to follow protocols with rigid real-time and real-space properties, but they also need to be capable of making competitive and collaborative decisions with varying rewards and penalties. Due to these tough requirements, the construction of system control software is often very difficult. This calls for applying a model-based engineering approach, which allows one to formally express the time and space properties and use them as guidance for the whole engineering process from requirement definition via system design to software development. Moreover, it is beneficial, if one can verify with acceptable effort, that the time and space requirements are preserved throughout the development steps. This paper focuses on modelling spatio-temporal properties and their model-checking and simulation using different analysis tools in combination with the methods and tool extensions proposed here. To this end, we provide an informal overview of CASTeL, our CASTeLogic. CASTeL is stochastic and includes real-time concurrency and real-space distribution.

Figures (4)

• Figure 1: Simple Dead Spot Road Network with a T-intersection.
• Figure 2: Simple scenario for the three cars shown in Fig. \ref{['fig:RoadLayoutSimple']}.
• Figure 3: Coloured Stochastic Petri Net for concurrent car interactions in the simple dead spot network of Fig. \ref{['fig:RoadLayoutSimple']}.
• Figure 4: Scenario with a coverage bubble formed from ad hoc networks between vehicles.