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中文摘要：
在无线传感器网络环境中，观察者感兴趣的是由传感器网络监测得到的与时间-空间相关的事件，而不是传感器本身或者大量无关的观察数据．观察者会经常提出与事件相关的时-空查询，例如：“网络覆盖的某地理区域R中10：00～11：00发生了哪些事件？”．由于每个传感器节点只有有限的能量，因此，研究能量有效性的时-空查询处理算法成为一个重要的研究课题．给出了一种以数据为中心的时．空查询处理算法．针对3种不同的存储蓑略：以数据为中心的存储、外部存储和节点本地存储，分析比较了节点的能量消耗，系统地研究了在3种不同的数据存储策略下，事件发生的概率，节点密度，事件类型数目，查询数目，时-空查询地理区域的大小以及时-空查询时间窗口的大小对节点能量消耗的影响．理论与实验结果表明，在多数情况下，这种以数据为中心的时-空查询处理算法的能量消耗少于基于外部存储和本地存储的时-空查询处理算法。
英文摘要：
In wireless sensor networks, observers are interested in spatio-temporal information monitored by sensors. Observers are not interested in sensor itself or massive irrelevant readings from sensors. They often issue spatio-temporal queries such as ＂Which events did happen in region R from 10：00 to 12：00？＂. Since battery supply of sensors is limited, energy-efficient spatio-temporal query processing in sensor networks has become an important research problem. This paper presents a spatio-temporal query processing algorithm based on data-centric storage. The energy consumption of sensors in three storage strategies, namely external storage, local storage and data-centric storage, is analyzed and compared in this paper. The pap er also studies the influence of the probability of an event occurring, node density, number of event types, number of queries, temporal window size and spatial area size in spatial-temporal query on energy consumption. Analytical and experimental results show that in most cases the spatio-temporal query processing algorithm proposed in this paper can save more energy than those algorithms based on the external storage and local storage strategies.
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