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    题名: Efficient and Robust Schemes for Sensor Data Aggregation Based on Linear Counting
    作者: 陳良弼
    Fan,Yao-Chung;Chen,Arbee L.P.
    贡献者: 資科系
    日期: 2010-11
    上传时间: 2014-08-21 15:10:27 (UTC+8)
    摘要: Sensor networks have received considerable attention in recent years, and are often employed in the applications where data are difficult or expensive to collect. In these applications, in addition to individual sensor readings, statistical aggregates such as Min and Count over the readings of a group of sensor nodes are often needed. To conserve resources for sensor nodes, in-network strategies are adopted to process the aggregates. One primitive in-network aggregation strategy is the tree-based aggregation, where the aggregates are computed from leaves to the root of a spanning tree over a sensor network. However, a shortcoming with the tree-based aggregation is that it is not robust against communication failures, which are common in sensor networks. One of the solutions to overcome this shortcoming is to enable multipath routing, by which each node broadcasts its reading or a partial aggregate to multiple neighbors. However, multipath routing-based aggregation typically suffers from the problem of overcounting sensor readings. In this study, we propose two schemes based on the linear counting technique to deal with the overcounting problem. These two schemes process aggregates by statically and dynamically, respectively, allocating space for the use of the linear counting technique. Both schemes provide the same accuracy guarantee but involve different communication costs. Through extensive experiments with real-world and synthetic data, we demonstrate the efficiency and effectiveness of using these two schemes as solutions for processing aggregates in a sensor network. The experiments also show that the scheme that dynamically allocates the space often outperforms the other one in terms of energy conservation since it requires less space to satisfy an accuracy constraint.
    關聯: Parallel and Distributed Systems,21(11),1675-1691
    数据类型: article
    DOI 連結: http://dx.doi.org/10.1109/TPDS.2010.33
    DOI: 10.1109/TPDS.2010.33
    显示于类别:[資訊科學系] 期刊論文

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