We propose a novel algorithm for sensor selflocalization
in cooperative wireless networks where observations
of relative sensor distances are available. The variational message
passing (VMP) algorithm is used to implement a mean field
solution to the estimation of the posterior probabilities of the
sensor positions in an R^2 scenario. Extension to R^3 is straightforward.
Compared to non-parametric methods based on belief
propagation, the VMP algorithm features significantly lower
communication overhead between sensors. This is supported by
performance simulations which show that the estimated mean
localization error of the algorithm stabilizes after approximately
30 iterations.