Distributed consensus building promises to
improve the robustness and reliability of sensor networks
and thus is an active topic of research. Whereas extensive
study has been done on the theoretical analysis of the
asymptotic behavior of consensus building, one important
issue that is crucial to the practical implementation of
sensor networks was rarely explored, namely, the criteria
to determine whether consensus has been attained. In this
paper, we propose an approach that allows each node in a
network to make the decision by itself, based on the second
derivatives of its own state. The approach does not rely
on the states of other nodes, leads to substantial saving
of communication resources, and is resilient to connection
failure. We perform a systematic analysis of the approach
and, as a consequence, derive the optimal parameters that
minimize the upper bound of the number of required
iterations to reach consensus.
Distributed Consensus Student-t Filter for Sensor Networks With Heavy-Tailed Process and Measurement Noises
