基于最大时间阈值与自适应步长的时间相关性感知数据去冗余算法
A Temporal Correlation Perceptual Data De-duplication Algorithm based on Maximum Time Threshold and Adaptive Step Size
投稿时间:2019-11-19  修订日期:2019-11-19
DOI:
中文关键词: 感知数据  去冗余算法  最大时间阈值  自适应步长  时间相关性
英文关键词: perceptual data  de-duplication algorithm  maximum time threshold  adaptive step size  temporal correlation
基金项目:国家自然科学基金资助项目(61772562),湖北省自然科学基金杰出青年项目(2017CFA043),国家民委中青年英才培养计划项目(2016).
作者单位E-mail
朱容波 中南民族大学 rbzhu@mail.scuec.edu.cn 
李媛丽 中南民族大学  
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中文摘要:
      针对传感器网络感知数据去冗余方法存在冗余度高的不足,提出了一种基于最大时间阈值及自适应步长的时间相关性感知数据去冗余算法(TDS)。TDS算法充分考虑了在去冗余过程中当数据变动幅度范围大、局部最大值与最小值存在较大误差,用户无法通过部分特征数据准确获取重要的信息,以及在数据波动平稳时,数据相似性阈值对冗余数据限制失效等因素;TDS在保证去冗余率的情况下,通过设置最大时间阈值防止数据相似性阈值失效,保证了数据的时效性;同时TDS采用自适应步长机制降低了计算复杂性,达到减少计算能耗的目的。实验结果表明,在相同的数据准确度的条件下,TDS算法减少了96%的冗余数据与传输能耗;与数据传输协议(DaT)方法相比,传输能耗减少了3%,计算能耗减少了50%。
英文摘要:
      In order to overcome the high redundancy of sensing data in sensor networks, a temporal correlation sensing data de-duplication algorithm (TDS) is proposed based on the maximum time threshold and adaptive step size. TDS algorithm fully considers the following factors in the process of de-duplication: when the range of data variation is large, there is a large error between the local maximum value and the minimum value, and the user can’t accurately obtain important information through some characteristic data, and when the data fluctuation is stable, the data similarity threshold doesn’t work on the limits of redundant data. With considering the ratio of de-duplication, TDS guarantees the timeliness of the sensing data with maximum time threshold to prevent the failure of data similarity threshold. Meanwhile, the adaptive step size mechanism is proposed to reduce the complexity of calculation and the energy consumption. Experimental results show that with the same data accuracy, TDS can reduce redundant data and transmission energy consumption by 96%. Meanwhile, compared with the data transmission protocol (DaT) method, TDS is able to reduce transmission energy consumption by 3% and calculation energy consumption by 50%.
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