Wireless sensor networks have emerged as a promising solution for a large number of monitoring applications. Sensor nodes are capable of measuring real world phenomena, storing, processing and transferring these measurements. However, users are interested in event monitored by sensors, but not the sensor itself or the massive irrelevant readings from sensors. Users often issue event queries such as “Where did happen hailstone in sensor network from 3:00 to 5:00?” Since battery supply of sensors is limited, energy-efficient query processing in sensor networks has become an important research problem. This paper presents an improved data-centric storage strategy, called CM-DCS, and also proposes two event query processing algorithms based on CM-DCS and local storage. The energy consumption of sensors for three storage strategies namely external storage, local storage and data-centric storage are analyzed and compared. The paper also studies the influence of the number of sensor nodes and node density on energy consumption. Analytical and experimental results show that in most cases the event query processing algorithm based on CM-DCS can save more energy than those algorithms based on external storage and local storage strategies.