  The problem of decentralized sequential change detection is considered, where
an abrupt change occurs in an area monitored by a number of sensors; the
sensors transmit their data to a fusion center, subject to bandwidth and energy
constraints, and the fusion center is responsible for detecting the change as
soon as possible. A novel sequential detection rule is proposed that requires
communication from the sensors at random times and transmission of only low-bit
messages, on which the fusion center runs in parallel a CUSUM test. The
second-order asymptotic optimality of the proposed scheme is established both
in discrete and in continuous time. Specifically, it is shown that the
inflicted performance loss (with respect to the optimal detection rule that
uses the complete sensor observations) is asymptotically bounded as the rate of
false alarms goes to 0, for any fixed rate of communication. When the rate of
communication from the sensors is asymptotically low, the proposed scheme
remains first-order asymptotically optimal. Finally, simulation experiments
illustrate its efficiency and its superiority over a decentralized detection
rule that relies on communication at deterministic times.
