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Post-processing in wireless sensor networks: Benchmarking sensor trace files for in-network data aggregation

机译:无线传感器网络中的后处理:基准化传感器跟踪文件以进行网络内数据聚合

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Wireless sensor network research usually focuses on the reliable and efficient collection of data. In this paper we target on the next step in the lifetime of traces: we aim at investigating and evaluating, by qualitative and quantitative means, data repositories of already collected measurements. Concerning the collected datasets, several important topics arise like the need of exchanging traces between researchers using a common representation of the traces and the need for common classification of the traces based on a commonly agreed set of statistical characteristics for in retrospect utilization. In order to qualitatively address these issues, we propose the use of a novel set of metrics focusing on the in-network data-aggregation problem class. These metrics enable reliable evaluation of algorithms using the same benchmark traces (both in average cases and "stressful" setups) removing the need for running algorithms in a real testbed, at least in the initial development stage. We present the results of our research as a first approach for addressing this problem, and in order to confirm our method, we characterized several traces with the proposed metrics. We validate the metrics by predicting the performance of three data-aggregation schemes using the available traces and checking the results by actually running the algorithms.
机译:无线传感器网络研究通常集中在可靠和高效的数据收集上。在本文中,我们着眼于痕迹寿命的下一步:我们旨在通过定性和定量手段调查和评估已经收集的测量结果的数据库。关于收集的数据集,出现了几个重要的主题,例如需要在研究人员之间使用痕迹的通用表示来交换痕迹,以及需要基于共同同意的统计特征集进行踪迹的通用分类,以进行回溯利用。为了定性地解决这些问题,我们建议使用一套针对网络内数据聚合问题类的新颖度量标准。这些指标可以使用相同的基准测试轨迹(在一般情况下和“压力较大”的设置中)对算法进行可靠的评估,从而至少在初始开发阶段就无需在真实的测试台上运行算法。我们提出研究结果作为解决此问题的第一种方法,并且为了确认我们的方法,我们使用建议的度量标准对数条迹线进行了特征描述。我们通过使用可用迹线预测三种数据聚合方案的性能并通过实际运行算法检查结果来验证指标。

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