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无线传感器网络中(ε,δ)-近似聚集算法 被引量：2

(ε,δ)-Approximate Aggregation Algorithm in Wireless Sensor Networks
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摘要 提出了一种基于Bernoulli抽样的近似聚集算法,以满足无线传感器网络(简称WSN)中用户给定的任意精度需求.同时,还提出了两种样本数据的自适应算法,分别用于处理用户的精确度需求以及网络中的感知数据发生变化的情况.理论分析及实验结果表明,所提出的算法在近似结果的精确度、能量开销等方面均优于已有的近似聚集算法. This paper proposes an approximate aggregation algoriihm based on Bernoulli sampling to satisfy the requirement of arbitrary precision in wireless sensor networks （WSN）. Besides, two sample data adaptive algorithms are also provided. One is to adapt the sample to the varying precision requirement. The other is to adapt the sample to the varying sensed data in networks. Theoretical analysis and experimental results show that the proposed algorithms have good performance in terms of accuracy and energy cost.
作者 程思瑶 李建中
机构地区 哈尔滨工业大学计算机科学与技术学院
出处 《软件学报》 EI CSCD 北大核心 2010年第8期1936-1953,共18页 Journal of Software
基金 国家自然科学基金Nos.60533110 60703012 国家重点基础研究发展计划(973)No.2006CB303000 新世纪优秀人才支持计划No.NCET-05-0333 NSFC/RGC联合资助项目No.60831160525~~
关键词 传感器网络 近似聚集 Bernoulli抽样 wireless sensor network approximate aggregation Bernoulli sampling
分类号 TP393 [自动化与计算机技术—计算机应用技术]
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参考文献23

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  • 2Zhao J,Govindan R,Estrin D.Computing aggregates for monitoring wireless sensor networks.In:Kindberg T,ed.Proc.of the 1st IEEE Int'l Workshop on Sensor Network Protocols and Applications.Washington:IEEE Computer Society Press,2003.139-148.
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软件学报
2010年 第8期

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