Abstract
One of the applications of Vehicular Ad-hoc NETworks, known as VANETs, is warning message dissemination among vehicles in dangerous situations to prevent more damage. The only communication mechanism for message dissemination is multi-hop broadcast; in which, forwarding a received message has to be regulated using a scheme regarding the selection of forwarding nodes. When analyzing these schemes, simulation-based frameworks fail to provide guaranteed analysis results due to the high level of concurrency in this application. Therefore, there is a need to use model checking approaches for achieving reliable results. In this paper, we have developed a framework called VeriVANca, to provide model checking facilities for the analysis of warning message dissemination schemes in VANETs. To this end, an actor-based modeling language, Rebeca, is used which is equipped with a variety of model checking engines. To illustrate the applicability of VeriVANca, modeling and analysis of two warning message dissemination schemes are presented. Some scenarios for these schemes are presented to show that concurrent behaviors of the system components may cause uncertainty in both behavior and performance which may not be detected by simulation-based techniques. Furthermore, the scalability of VeriVANca is examined by analyzing a middle-sized model.
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Notes
- 1.
Message queue in Rebeca and message bag in Timed Rebeca.
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Acknowledgments
The work on this paper has been supported in part by the project “Self-Adaptive Actors: SEADA” (163205-051) of the Icelandic Research Fund and DPAC Project (Dependable Platforms for Autonomous Systems and Control) at Mälardalen University, Sweden.
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Yousefi, F., Khamespanah, E., Gharib, M., Sirjani, M., Movaghar, A. (2019). VeriVANca: An Actor-Based Framework for Formal Verification of Warning Message Dissemination Schemes in VANETs. In: Biondi, F., Given-Wilson, T., Legay, A. (eds) Model Checking Software. SPIN 2019. Lecture Notes in Computer Science(), vol 11636. Springer, Cham. https://doi.org/10.1007/978-3-030-30923-7_14
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