| 摘要: |
| 在无线传感器网络中,加权聚集操作是用户获取检测对象信息的重要手段,这一操作通过赋予各个节点或感知数据不同的权值来确保聚集结果更加真实地反映监测对象.另一方面,考虑到能量的限制、网络的不稳定性,如果能保证误差在用户容忍的范围内,近似加权聚集更加适用于传感器网络.针对感知数据的近似加权聚集问题,提出了一种基于分组抽样的(ε,δ)-近似算法,理论证明算法可以达到任意的精度要求.同时,提出的算法具有良好的扩展性,可以适用于大规模、动态变化的传感器网络,并且支持查询过程中的精度调整.仿真实验验证了算法的正确性,并且通过和已有算法比较证明了所提出算法的高效性. |
| 关键词: 无线传感器网络 数据聚集 加权计算 抽样算法 近似查询 |
| DOI： |
| 分类号: |
| 基金项目:国家自然科学基金(61033015, 60933001, 61190115) |
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| Approximate Aggregation Algorithm for Weighted Data in Wireless Sensor Networks |
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ZHENG Xu, LI Jian-Zhong
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School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
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| Abstract: |
| In wireless sensor networks, a weighted aggregation is an important method for the users to obtain the information when monitoring the environment. This method enforces the objectivity of the aggregation result by assigning different weights to different nodes or sensed data. On the other hand, the WSNs are both energy constraint and unstable, so it is better to do the approximate data aggregation if one can ensure the error-bound is tolerable for the users. A group-based sampling algorithm for approximate weighted aggregation is proposed. The theoretical analysis demonstrates that the proposed algorithm can reach arbitrary precision. Furthermore, the proposed algorithm is scalable, and it can adapt to large-scale dynamic sensor networks, and support the modification of the precision during the processing of a query. Experimental results show the correctness of the proposed algorithm and demonstrates the high performance of the proposed algorithm by comparing it with previous algorithms. |
| Key words: wireless sensor network data aggregation weighted computation sampling algorithm approximate query |
