State Space Exploration of RT Systems in the Cloud

TL;DR

This paper compares distributed and cloud-based approaches to state-space exploration of real-time systems, demonstrating the advantages of cloud frameworks through benchmarking on Petri Nets.

Contribution

It introduces and evaluates two novel cloud and distributed methods for symbolic state-space exploration, adapting existing algorithms for enhanced scalability.

Findings

Cloud approach shows better scalability and efficiency.

Both methods effectively handle real-time Petri Nets.

Benchmark results validate the advantages of cloud-based exploration.

Abstract

The growing availability of distributed and cloud computing frameworks make it possible to face complex computational problems in a more effective and convenient way. A notable example is state-space exploration of discrete-event systems specified in a formal way. The exponential complexity of this task is a major limitation to the usage of consolidated analysis techniques and tools. We present and compare two different approaches to state-space explosion, relying on distributed and cloud frameworks, respectively. These approaches were designed and implemented following the same computational schema, a sort of map & fold. They are applied on symbolic state-space exploration of real-time systems specified by (a timed extension of) Petri Nets, by readapting a sequential algorithm implemented as a command-line Java tool. The outcome of several tests performed on a benchmarking specification are presented, thus showing the convenience of cloud approaches.