Querying Peak Regions in Wireless Sensor Networks

Abstract

提出了无线传感器网络上的一种查询——极值区域查询(peak region query,简称PRQ),即用户指定查询区域的大小和形状,例如半径为R的圆形区域,然后需要查询传感器网络中的某个区域,使得区域内传感器节点数据的某种聚集值最大.定义了极值区域查询的概念,并提出一种集中式算法以求解查询结果.由于传感器节点的能量有限,为了降低查询处理过程中的能耗,提出了分布式算法EXQ(an algorithm for extreme value query processing).与集中式算法相比,EXQ不但显著降低了能耗,而且使得每个传感器的能耗更加平均,从而延长了网络的使用寿命.EXQ的基本思想是,将整个网络划分为若干相互重叠的子区域,对每个子区域通过本地数据聚集得到一个本地结果,然后对这些结果再进行全局数据聚集从而得到查询结果.从理论和实验两方面分析和比较了集中式算法和EXQ的能耗和节点负载分布.;This paper proposes a query in wireless sensor networks: Peak Region Query (PRQ). Given the shape and size of the query region, i.e., a disk region with radius R, peak region query finds out a region with this shape in the network field, in which the aggregation value of the data of the sensors can be maximized. This paper first gives the definition of PRQ, and then proposes a centralized algorithm for the problem. Because the sensors have limited energy, a distributed approach EXQ (an algorithm for extreme value query processing) is proposed, which not only reduces the energy cost but also balances the workload of the sensors, so as to prolong the lifetime of the network. The basic idea is to divide the network field into overlapped sub-regions, compute a local result for each sub-region and aggregate these results to obtain the query answer. The paper compares the energy efficiency and load balance between EXQ and the centralized approach analytically and experimentally.