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For a connected network of sensors we consider deriving the linear update weights required by a 1-hop distributed linear averaging algorithm (denoted 1-DLA) such that average-consensus is reached when the sensor nodes simultaneously track, by linear stochastic approximation, a set of distinct Markov chains with time-varying regime. It is found the desired consensus is infeasible for any 1-hop 1-DLA...
Decentralized network estimation of the average initial node value is considered here in a variety of stochastic network settings. Each setting assumes the elements of the network communication graph edge set are modeled as a collection of ergodic Markov chains with slowly switching regime and unknown stationary distribution. In this framework an asymptotic average-consensus is obtained by using a...
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