Passive Loss Inference in Wireless Sensor Networks Using EM Algorithm

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Wireless Sensor Networks (WSNs) are mainly deployed for data acquisition, thus, the network performance can be passively measured by exploiting whether application data from various sensor nodes reach the sink. In this paper, therefore, the authors take into account the unique data aggregation communication paradigm of WSNs and model the problem of link loss rates inference as a Maximum-Likelihood Estimation problem. And the authors propose an inference algorithm based on the standard Expectation-Maximization (EM) techniques. Their algorithm is applicable not only to periodic data collection scenarios but to event detection scenarios.