Sensor networks are expected to be used for spatial cognition in harsh environments. When an event happens, there will be several sensors detect it and send their reports to a sink, but these data are neither integrated nor reliable. Therefore, it is reasonable to make use of data fusion on intermediate nodes to achieve deeper knowledge on an event and cut down the total traffic at the same time. However, a node needs to decide in what order it send packets to its neighbors, which is called traffic scheduling. In sensor networks with data fusion, bad traffic scheduling results in remarkable delay, because an intermediate node must wait for all incoming data to arrive before it can perform data fusion. In order to prolong the network lifetime, we apply traffic scheduling to reduce the energy that consumed by such idle listening.