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The highly stochastic nature of wireless environments makes it desirable to monitor link loss rates in wireless sensor networks. This paper studies the loss inference problem in sensor networks with network coding. Unlike traditional transmission protocols, network coding offers reliable communication without using control messages for individual packets. The paper shows, however, that network coding changes the fundamental connection between path and link loss probabilities such that new inference algorithms need to be developed. As end-to-end data are not sufficient to compute link loss rates precisely, the paper proposes inference algorithms based on Bayesian principles to discover the set of highly lossy links in sensor networks.
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