Theoretical Computer Science
Probabilistic Verification of Discrete Event Systems Using Acceptance Sampling
CAV '02 Proceedings of the 14th International Conference on Computer Aided Verification
Timing-sync protocol for sensor networks
Proceedings of the 1st international conference on Embedded networked sensor systems
The flooding time synchronization protocol
SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
Numerical vs. statistical probabilistic model checking
International Journal on Software Tools for Technology Transfer (STTT)
Formal Software Analysis Emerging Trends in Software Model Checking
FOSE '07 2007 Future of Software Engineering
Wireless sensor network survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Analysis of a Clock Synchronization Protocol for Wireless Sensor Networks
FM '09 Proceedings of the 2nd World Congress on Formal Methods
Analyzing the robustness of FTSP with timed automata
Proceedings of the Second Asia-Pacific Symposium on Internetware
Time for statistical model checking of real-time systems
CAV'11 Proceedings of the 23rd international conference on Computer aided verification
Statistical abstraction and model-checking of large heterogeneous systems
International Journal on Software Tools for Technology Transfer (STTT)
Poster Abstract: Numerical Analysis of WSN Protocol Using Probabilistic Timed Automata
ICCPS '12 Proceedings of the 2012 IEEE/ACM Third International Conference on Cyber-Physical Systems
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Wireless Sensor Networks (WSNs) are widely used in different kinds of environments. They may encounter lots of stochastic uncertainties and disturbances like message loss and node dynamics. Thus, it is critical to ensure the correctness of low level protocols in WSNs and evaluate their performance under different circumstances. In this paper, we propose a new method to analyze and evaluate WSN protocols based on stochastic timed automata and statistical model checking. For modeling, the work flow of a WSN protocol can be modeled with classical timed automata. Then, to model the uncertainties such as message loss and node dynamics, which are common in realistic circumstances, the timed automata can be extended by stochastic transitions, resulting in the stochastic timed automata. For analysis, the correctness of the protocol can be answered by classical model checking on the timed automata, while the performance of the protocol under realistic environments can be evaluated by statistical model checking on the stochastic model. To illustrate the feasibility and scalability of the modeling and verification method presented in this paper, Timing-sync Protocol for Sensor Networks (TPSN) will be studied completely throughout the paper.