“…The last line of Table 1 refers to a simulation where N 2 = N 1 , which results in the most precise estimation, because at each step at least one data (and at most two) for the network state estimate is available. As experimental validation, we have run Algorithm 3.1 on a dataset obtained from a real wireless sensor network composed of Telos T-mote Sky nodes where an object was sometimes shadowing the receiver node, similarly to what discussed in [6]. Part of the dataset was used to estimate the transition probabilities of the Markov chain, and the packet drops probabilities in each state, obtaining p R,U = 10 −3 , p U,U = 1.5 · 10 −3 , p r = 0.10, p u = 0.75.…”