Open Systems Laboratory at Illinois

Performance evaluation of sensor networks by statistical modeling and euclidean model checking

By YoungMin Kwon and Gul Agha. TOSN, 9(4):39:1–39:38, 2013.

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Modeling and evaluating the performance of large-scale wireless sensor networks (WSNs) is a challenging problem. The traditional method for representing the global state of a system as a cross product of the states of individual nodes in the system results in a state space whose size is exponential in the number of nodes. We propose an alternative way of representing the global state of a system: namely, as a probability mass function (pmf) which represents the fraction of nodes in different states. A pmf corresponds to a point in a Euclidean space of possible pmf values, and the evolution of the state of a system is represented by trajectories in this Euclidean space. We propose a novel performance evaluation method that examines all pmf trajectories in a dense Euclidean space by exploring only finite relevant portions of the space. We call our method Euclidean model checking. Euclidean model checking is useful both in the design phase--where it can help determine system parameters based on a specification--and in the evaluation phase--where it can help verify performance properties of a system. We illustrate the utility of Euclidean model checking by using it to design a time difference of arrival (TDoA) distance measurement protocol and to evaluate the protocol's implementation on a 90-node WSN. To facilitate such performance evaluations, we provide a Markov model estimation method based on applying a standard statistical estimation technique to samples resulting from the execution of a system.


    author = "Kwon, YoungMin and Agha, Gul",
    title = "Performance evaluation of sensor networks by statistical
             modeling and euclidean model checking",
    biburl = "",
    doi = "10.1145/2489253.2489256",
    journal = "{TOSN}",
    number = "4",
    pages = "39:1--39:38",
    timestamp = "Tue, 06 Nov 2018 00:00:00 +0100",
    url = "",
    volume = "9",
    year = "2013",