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    李贵林 李建中. 传感器网络中节点个数约束查询处理算法[J]. 计算机研究与发展, 2008, 45(1): 90-96.
    引用本文: 李贵林 李建中. 传感器网络中节点个数约束查询处理算法[J]. 计算机研究与发展, 2008, 45(1): 90-96.
    Li Guilin and Li Jianzhong. A Node Number Constraint Query Processing Algorithm for Sensor Networks[J]. Journal of Computer Research and Development, 2008, 45(1): 90-96.
    Citation: Li Guilin and Li Jianzhong. A Node Number Constraint Query Processing Algorithm for Sensor Networks[J]. Journal of Computer Research and Development, 2008, 45(1): 90-96.

    传感器网络中节点个数约束查询处理算法

    A Node Number Constraint Query Processing Algorithm for Sensor Networks

    • 摘要: 针对传感器网络中一类新查询——节点个数约束查询,提出能量有效的查询处理算法.算法主要由查询下发和结果回收两部分构成.查询下发算法首先根据节点个数约束查询的特点提出相关节点选择以及基于Steiner树的查询下发算法.然后对该下发算法以及一种基于洪泛的能量有效查询下发算法的能量消耗进行分析,并对比两种算法的能量消耗从中选择适当的下发算法.结果回收算法提出直接和间接两种结果回收方式,并给出两种方式在进行结果回收时能够节省能量的条件.仿真实验表明,提出的能量有效节点个数约束查询处理算法能够在满足用户查询精度的同时,使其能量消耗低于其他查询处理算法.

       

      Abstract: An energy efficient query processing algorithm is proposed to process a new kind of query named node number constraint query for wireless sensor networks. The algorithm is mainly composed of two parts: query dissemination algorithm and result collection algorithm. The function of the query dissemination algorithm is to select an energy efficient way to disseminate the user's query into sensor networks. First a relevant node selection algorithm is proposed to select partial number of nodes from the network and a Steiner tree based algorithm is designed to disseminate queries to these relevant nodes. Then two energy cost models are built for the Steiner tree based query dissemination algorithm and an energy efficient flooding based query dissemination algorithm respectively. By comparing two energy consumption models, a suitable dissemination algorithm can be selected to send query to sensor networks. The energy efficient result collection algorithm presents two kinds of result collection strategy, which are direct and indirect collection strategy, and then the collection algorithm gives the condition, in which each strategy is suitable to collect results. By combining all the above mentioned algorithms, an energy efficient query processing algorithm for node number constraint query is proposed and the simulation results show that the algorithm proposed in this paper can not only guarantee the precision of the result but also save much more energy than other algorithms.

       

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