  We consider the challenge of efficiently detecting changes within a network
of sensors, where we also need to minimise communication between sensors and
the cloud. We propose an online, communication-efficient method to detect such
changes. The procedure works by performing likelihood ratio tests at each time
point, and two thresholds are chosen to filter unimportant test statistics and
make decisions based on the aggregated test statistics respectively. We provide
asymptotic theory concerning consistency and the asymptotic distribution if
there are no changes. Simulation results suggest that our method can achieve
similar performance to the idealised setting, where we have no constraints on
communication between sensors, but substantially reduce the transmission costs.
