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文章基本信息

  • 标题:Two Case Studies on Data Sensitivity of Wireless Sensor Network Algorithms and our Proposal on Scalable, Synthetic Data Generation
  • 本地全文:下载
  • 作者:Yan Yu ; Deborah Estrin ; Ramesh Govindan
  • 期刊名称:International Journal of Distributed Sensor Networks
  • 印刷版ISSN:1550-1329
  • 电子版ISSN:1550-1477
  • 出版年度:2006
  • 卷号:2
  • DOI:10.1080/15501320600719086
  • 出版社:Hindawi Publishing Corporation
  • 摘要:Sensor network research is still in its infancy. There is a large volume of exploratory research. From lack of experimental data and sophisticated models derived from such data, many sensor network publications continue to use data generated from simple models in their algorithm evaluation. It is commonly agreed that data processing algorithms in sensor networks are sensitive to input data. However, no previous efforts have been devoted to quantitatively characterize the range of the algorithm performance when evaluated using different data input.
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