Study on active sleeping node detection method in sensor network based on multi-dimensional sliding window

Q4 Decision Sciences
Jing Qiu, Feng Gao
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引用次数: 0

Abstract

To overcome the problems of low coverage and detection accuracy in traditional detection methods, a multidimensional sliding window based active sleep node detection method for sensor networks is proposed. Firstly, we set up an active sleep node simulator and controller in the sensor network space to determine the active sleep range. Secondly, we design a multidimensional sliding window algorithm to determine anomalies in the transmission link by calculating the standard deviation of sensing information in the sliding window. Finally, the total length of data transmission is dimensionally transformed to achieve reliable detection of active sleep nodes. The experimental results show that the coverage rate of the detection results of this method is closer to 1, and its detection accuracy remains between 94.84% -97.32%, and the detection process time remains between 1.72 s-232 s. It has the advantages of strong reliability and high efficiency in applications.
基于多维滑动窗口的传感器网络主动睡眠节点检测方法研究
针对传统检测方法覆盖率低、检测精度低等问题,提出了一种基于多维滑动窗口的传感器网络主动睡眠节点检测方法。首先,我们在传感器网络空间中设置主动睡眠节点模拟器和控制器来确定主动睡眠范围。其次,设计了一种多维滑动窗口算法,通过计算滑动窗口中传感信息的标准差来判断传输链路中的异常;最后,对数据传输的总长度进行维数变换,实现对活动睡眠节点的可靠检测。实验结果表明,该方法检测结果的覆盖率更接近于1,检测准确率保持在94.84% ~ 97.32%之间,检测过程时间保持在1.72 s ~ 232 s之间。在实际应用中具有可靠性强、效率高等优点。
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来源期刊
International Journal of Networking and Virtual Organisations
International Journal of Networking and Virtual Organisations Decision Sciences-Information Systems and Management
CiteScore
1.40
自引率
0.00%
发文量
25
期刊介绍: IJNVO is a forum aimed at providing an authoritative refereed source of information in the field of Networking and Virtual Organisations.
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