{"title":"Managing evolving shapes in sensor networks","authors":"Besim Avci, Goce Trajcevski, P. Scheuermann","doi":"10.1145/2618243.2618264","DOIUrl":null,"url":null,"abstract":"This work addresses the problem of efficient distributed detection and tracking of mobile and evolving/deformable spatial shapes in Wireless Sensor Networks (WSN). The shapes correspond to contiguous regions bounding the locations of sensors in which the readings of the sensors satisfy a particular threshold-based criterion related to the values of a physical phenomenon that they measure. We formalize the predicates representing the shapes in such settings and present detection algorithms. In addition, we provide a light-weight protocol and aggregation methods for energy-efficient distributed execution of those algorithms. Another contribution of this work is that we developed efficient techniques for detecting a co-occurrence of shapes within a given proximity from each other. Our experiments demonstrate that, when compared to the centralized techniques -- which is, predicates being detected in a dedicated sink -- as well as distributed periodic contours construction, our methodologies yield significant energy/communication savings.","PeriodicalId":74773,"journal":{"name":"Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management","volume":"37 5","pages":"22:1-22:12"},"PeriodicalIF":0.0000,"publicationDate":"2014-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific and statistical database management : International Conference, SSDBM ... : proceedings. International Conference on Scientific and Statistical Database Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2618243.2618264","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10

Abstract

This work addresses the problem of efficient distributed detection and tracking of mobile and evolving/deformable spatial shapes in Wireless Sensor Networks (WSN). The shapes correspond to contiguous regions bounding the locations of sensors in which the readings of the sensors satisfy a particular threshold-based criterion related to the values of a physical phenomenon that they measure. We formalize the predicates representing the shapes in such settings and present detection algorithms. In addition, we provide a light-weight protocol and aggregation methods for energy-efficient distributed execution of those algorithms. Another contribution of this work is that we developed efficient techniques for detecting a co-occurrence of shapes within a given proximity from each other. Our experiments demonstrate that, when compared to the centralized techniques -- which is, predicates being detected in a dedicated sink -- as well as distributed periodic contours construction, our methodologies yield significant energy/communication savings.
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在传感器网络中管理不断变化的形状
这项工作解决了无线传感器网络(WSN)中移动和演化/变形空间形状的高效分布式检测和跟踪问题。形状对应于传感器位置的相邻区域,其中传感器的读数满足与它们测量的物理现象值相关的基于特定阈值的标准。我们形式化了在这种情况下表示形状的谓词,并提出了检测算法。此外,我们还提供了轻量级协议和聚合方法,以实现这些算法的高效分布式执行。这项工作的另一个贡献是我们开发了有效的技术来检测给定距离内形状的共现。我们的实验表明,与集中式技术(即在专用接收器中检测谓词)以及分布式周期性轮廓构建相比,我们的方法可以显著节省能源/通信。
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