| 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. |
| 关键词: 传感器网络 近似聚集 Bernoulli抽样 |
| DOI： |
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| 基金项目:Supported by the National Natural Science Foundation of China under Grant Nos.60533110, 60703012 (国家自然科学基金); the National Basic Research Program of China under Grant No.2006CB303000 (国家重点基础研究发展计划(973)); the Program for New Century Excellent Talents in University of China under Grant No.NCET-05-0333 (新世纪优秀人才支持计划); the NSFC/RGC Joint Research Scheme under Grant No.60831160525 (NSFC/RGC联合资助项目) |
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| (ε,δ)-Approximate Aggregation Algorithm in Wireless Sensor Networks |
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CHENG Si-Yao,LI Jian-Zhong
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| Abstract: |
| This paper proposes an approximate aggregation algorithm 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. |
| Key words: wireless sensor network approximate aggregation Bernoulli sampling |
