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A Cluster-Interval-Based Algorithm for Optimizing Range Query in Wireless Sensor Network

机译:无线传感器网络中基于簇区间的距离查询优化算法

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In wireless sensor network, how to use limited node energy efficiently to process data querying becomes an important research problem. We propose a cluster-based filter algorithm SFOA for range query in wireless sensor network because the data, sampled in cluster nodes, are highly similar to one another in cluster-based WSN. Its basic idea is to provide a filter for each cluster, and three filters for each node which are in the same cluster. This algorithm build cluster interval for each cluster, and inter-cluster interval for each node in the cluster to filter out the impossible clusters and nodes, which can reduce the number of nodes participating in the range query, saving nodes energy. Furthermore, the simulation experimental results indicate that, in most cases, SFOA has energy efficiency, which greatly reduce the data transmissions.
机译:在无线传感器网络中,如何有效利用有限的节点能量来处理数据查询成为一个重要的研究问题。我们提出了一种基于集群的过滤算法SFOA,用于无线传感器网络中的距离查询,因为在集群节点中采样的数据与基于集群的WSN中的数据非常相似。其基本思想是为每个群集提供一个筛选器,并为同一群集中的每个节点提供三个筛选器。该算法为每个集群建立集群间隔,并为集群中的每个节点建立集群间间隔,以过滤掉不可能的集群和节点,从而可以减少参与范围查询的节点数量,从而节省节点能量。此外,仿真实验结果表明,在大多数情况下,SFOA具有能源效率,从而大大减少了数据传输。

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