We describe LiveNet, a set of tools and analysis methods for reconstructing the complex behavior of a deployed sensor network. LiveNet is based on the use of multiple passive packet sniffers co-located with the network, which collect packet traces that are merged to form a global picture of the network's operation. The merged trace can be used to reconstruct critical aspects of the network's operation that cannot be observed from a single vantage point or with simple application-level instrumentation. We address several challenges: merging multiple sniffer traces, determining sniffer coverage, and inference of missing information for routing path reconstruction. We perform a detailed validation of LiveNet's accuracy and coverage using a 184-node sensor network testbed, and present results from a real-world deployment involving physiological monitoring of patients during a disaster drill. Our results show that LiveNet is able to accurately reconstruct network topology, determine bandwidth usage and routing paths, identify hot-spot nodes, and disambiguate sources of packet loss observed at the application level. © 2008 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Chen, B. R., Peterson, G., Mainland, G., & Welsh, M. (2008). LiveNet: Using passive monitoring to reconstruct sensor network dynamics. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5067 LNCS, pp. 79–98). https://doi.org/10.1007/978-3-540-69170-9_6
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