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1.
The phenomenon of missing sensor data is very common in wireless sensor networks (WSN). It has a dramatic effect on the usability, stability and efficiency of the WSN-based applications. There exist many methods for the missing sensor data estimation. However, the accurate and efficient consequent estimation of missing sensor data remains a challenging problem. To solve this problem, we propose a new method named consecutive sensor data deep neural network (CSDNN). In this method, firstly, we analyze the correlation coefficients among different types of sensor data and choose a certain number of nearest neighbors of the target sensor nodes. Secondly, to estimate a certain type of sensor data from a target sensor node, we utilize the different types of sensor data that are from the same target sensor node and have strong correlation with the missing ones, and the same type of sensor data from the aforementioned nearest neighbors. We treat these data as the input of the deep neural networks (DNN). Thirdly, we construct the DNN model, discuss the optimized DNN structure for the missing data problem, and test the accuracy of CSDNN for different types of environmental sensor data. The results show that the CSDNN method allows to accurately estimate the consecutively missing sensor data. 相似文献
2.
传统的基于WebVR的激光传感器数据多维可视化方法,基于几何模型的激光传感器数据多维可视化方法与基于三维GIS空间的激光传感器数据多维可视化方法均存在数据处理速度慢的问题,为此设计一种基于虚拟现实技术的激光传感器数据多维可视化方法。采集激光传感器数据,对数据预处理,利用八叉树方法对数据空间进行划分,并定义传递函数,目的是为了获得三维数据场的数据属性,建立三维对象渲染模型,根据虚拟现实技术中的点、线、面等构建模型,以此完成激光传感器数据多维可视化处理。实验对比结果表明此次设计的基于虚拟现实技术的激光传感器数据多维可视化方法比传统的三种方法处理速度快,能够快速地传递激光传感器数据信息。 相似文献
3.
Visualization of dynamic fault tolerance rerouting for data traffic in wireless sensor network
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In wireless sensor network environments, a phenomenon of data concentration may occur in one or certain sensor nodes in the process of transmitting sensing data from a source sensor node to a sink node. In this case, the overhead that occurs in the sensor node affects the performance of the entire sensor network. In addition, in the sensor network, excessive sensing data traffic or data loss may occur depending on the variability of the topology of the sensor network. In this paper, visualization for dynamic rerouting is designed and implemented, which visibly provides packet movement routes between sensor nodes and transmitted packet traffic transmission capacity to Geography Markup Language‐based maps having GPS coordinate information. A mechanism for the visualization for dynamic rerouting to detect sensing data overheads and sensor node faults occurring in sensor networks and dynamically rerouting of data is proposed. In addition, information on rerouting route paths from source sensors to sink nodes is visually provided. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
4.
《Digital Communications & Networks》2016,2(3):122-129
As the massive sensor data generated by large-scale Wireless Sensor Networks (WSNs) recently become an indispensable part of ‘Big Data’, the collection, storage, transmission and analysis of the big sensor data attract considerable attention from researchers. Targeting the privacy requirements of large-scale WSNs and focusing on the energy-efficient collection of big sensor data, a Scalable Privacy-preserving Big Data Aggregation (Sca-PBDA) method is proposed in this paper. Firstly, according to the pre-established gradient topology structure, sensor nodes in the network are divided into clusters. Secondly, sensor data is modified by each node according to the privacy-preserving configuration message received from the sink. Subsequently, intra- and inter-cluster data aggregation is employed during the big sensor data reporting phase to reduce energy consumption. Lastly, aggregated results are recovered by the sink to complete the privacy-preserving big data aggregation. Simulation results validate the efficacy and scalability of Sca-PBDA and show that the big sensor data generated by large-scale WSNs is efficiently aggregated to reduce network resource consumption and the sensor data privacy is effectively protected to meet the ever-growing application requirements. 相似文献
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在传感器网络中,隐私保护和入侵检测是一对矛盾关系,调和两者的矛盾非常重要。在传感器网络中传感数据融合是一个基本操作,研究隐私保护和入侵检测在传感数据融合中的关系并提出一个框架,可以探测错误数据融合,但不需要知道实际的传感数据内容,因而得以保证传感数据的隐蔽性。实验结果显示,实际的原始数据和聚合传感数据可以得到很好隐蔽的同时能够检测到大部分错误数据融合。 相似文献
6.
Sensor data compression based on MapReduce简 总被引:1,自引:0,他引:1
A compression algorithm is proposed in this paper for reducing the size of sensor data. By using a dictionary-based lossless compression algorithm, sensor data can be compressed efficiently and interpreted without decompressing. The correlation between redundancy of sensor data and compression ratio is explored. Further, a parallel compression algorithm based on MapReduce [1] is proposed. Meanwhile, data partitioner which plays an important role in performance of MapReduce application is discussed along with performance evaluation criteria proposed in this paper. Experiments demonstrate that random sampler is suitable for highly redundant sensor data and the proposed compression algorithms can compress those highly redundant sensor data efficiently. 相似文献
7.
无线传感器网络数据收集问题综述 总被引:1,自引:0,他引:1
数据收集问题研究外界用户如何通过无线传感器网络从监控区域收集感知数据。传感器节点通过自组织方式构成网络,数据收集问题就是寻找高效可靠的方式将感知数据通过多跳的方式传输给用户进行分析和处理。近几年对数据收集问题的研究非常广泛,主要包含减少数据收集过程中的数据传输量、数据收集协议和大规模网络数据收集调度等问题。从以上几方面对数据收集问题进行综述。 相似文献
8.
《Digital Communications & Networks》2020,6(1):101-107
Recently, the application of Wireless Sensor Networks (WSNs) has been increasing rapidly. It requires privacy preserving data aggregation protocols to secure the data from compromises. Preserving privacy of the sensor data is a challenging task. This paper presents a non-linear regression-based data aggregation protocol for preserving privacy of the sensor data. The proposed protocol uses non-linear regression functions to represent the sensor data collected from the sensor nodes. Instead of sending the complete data to the cluster head, the sensor nodes only send the coefficients of the non-linear function. This will reduce the communication overhead of the network. The data aggregation is performed on the masked coefficients and the sink node is able to retrieve the approximated results over the aggregated data. The analysis of experiment results shows that the proposed protocol is able to minimize communication overhead, enhance data aggregation accuracy, and preserve data privacy. 相似文献
9.
Optimizing Lifetime for Continuous Data Aggregation With Precision Guarantees in Wireless Sensor Networks 总被引:1,自引:0,他引:1
《Networking, IEEE/ACM Transactions on》2008,16(4):904-917
10.
《Signal Processing Magazine, IEEE》2004,21(3):14-19
This article describes issues and challenges for secure sensor information management. In particular, we discuss data management for sensor information systems including stream data management, distributed data management for sensor data, sensor information management including mining sensor data, security for sensor databases, and dependable sensor information management such as tradeoffs between security, real-time processing, and fault tolerance. Finally we discuss object-based infrastructures for sensor systems as well as directions for sensor information management. 相似文献
11.
Communication overhead is a major concern in wireless sensor networks because of inherent behavior of resource constrained sensors. To degrade the communication overhead, a technique called data aggregation is employed. The data aggregation results are used to make crucial decisions. Certain applications apply approximate data aggregation in order to reduce communication overhead and energy levels. Specifically, we propose a technique called semantic correlation tree, which divides a sensor network into ring-like structure. Each ring in sensor network is divided into sectors, and each sector consists of collection of sensor nodes. For each sector, there will be a sector head that is aggregator node, the aggregation will be performed at sector head and determines data association on each sector head to approximate data on sink node. We propose a doorway algorithm to approximate the sensor node readings in sector head instead of sending all sensed data. The main idea of doorway algorithm is to reduce the congestion and also the communication cost among sensor nodes and sector head. This novel approach will avoid congestion by controlling the size of the queue and marking packets. Specifically, we propose a local estimation model to generate a new sensor reading from historic data. The sensor node sends each one of its parameter to sector head, instead of raw data. The doorway algorithm is utilized to approximate data with minimum and maximum bound value. This novel approach, aggregate the data approximately and efficiently with limited energy. The results demonstrate accuracy and efficiency improvement in data aggregation. 相似文献
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Data gathering is a major function of many applications in wireless sensor networks. The most important issue in designing
a data gathering algorithm is how to save energy of sensor nodes while meeting the requirements of special applications or
users. Wireless sensor networks are characterized by centralized data gathering, multi-hop communication and many to one traffic
pattern. These three characteristics can lead to severe packet collision, network congestion and packet loss, and even result
in hot-spots of energy consumption thus causing premature death of sensor nodes and entire network. In this paper, we propose
a load balance data gathering algorithm that classifies sensor nodes into different layers according to their distance to
sink node and furthermore, divides the sense zone into several clusters. Routing trees are established between sensor node
and sink depending on the energy metric and communication cost. For saving energy consumption, the target of data aggregation
scheme is adopted as well. Analysis and simulation results show that the algorithm we proposed provides more uniform energy
consumption among sensor nodes and can prolong the lifetime of sensor networks. 相似文献
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Motivated by chaos technology and compressed sensing, we propose a distributed secure data collection scheme via chaotic compressed sensing in wireless sensor networks. The chaotic compressed sensing is applied to the encrypted compression of sensory data for sensor node and the data acquisition for whole sensory in wireless sensor networks. The proposed scheme is suitable for long-term and large scale wireless sensor networks with energy efficiency, network lifetime and security. A sensing matrix generation algorithm and active node matrix algorithm based on chaos sequence are proposed to ensure the secure and efficient transmission of sensor packets. The secret key crack, forgery, hijack jamming and replay attacks on the proposed algorithm are evaluated to show the robustness of this scheme. Simulations and real data examples are also given to show that the proposed scheme can ensure the secure data acquisition in wireless sensor networks efficiently. 相似文献
17.
Wireless Personal Communications - Researchers concentrate on big data. Wireless sensor network is one of the sources of big data. Wireless sensor network has hundreds of sensor nodes with limited... 相似文献
18.
Liqiang Pan Huijun Gao Hong Gao Yong Liu 《International Journal of Wireless Information Networks》2014,21(4):280-289
In wireless sensor networks, the missing of sensor data is inevitable due to the inherent characteristic of wireless sensor networks, and it causes many difficulties in various applications. To solve the problem, the missing data should be estimated as accurately as possible. In this paper, an adaptive missing data estimation algorithm is proposed based on the spatial correlation of sensor data. It adopts multiple regression model to estimate the missing data with the data of multiple neighbor nodes jointly rather than independently, which makes its estimation performance stable and reliable. In addition, for different missing data, it can adjust the estimation equation adaptively to capture the dynamic correlation of sensor data. Thereby, it can estimate the missing data more accurately. Further more, it can also give the confidence interval of each missing data for the given confidence level, which is helpful greatly for users. Experimental results on two real-world datasets show that the proposed algorithm can estimate the missing data accurately. 相似文献
19.
介绍了利用FPGA来采集多路数字位移传感器的数据,同时集成了温度传感器的数据采集功能,并且将两种不同的传感器的采集数据很好的结合在了一起。在后续的数据处理上,灵活的使用采集到的数据,总结出数字位移传感器的特性。该设计显示了FPGA在处理多路多类型传感器方面的能力,为实现复杂传感器系统提供了一种新的可实现的解决方案。 相似文献
20.
WSN(无线传感器网络)是由大量分布式的不同规格和功能的具有感知、计算和通信能力的微型传感器节点通过自组织的方式构成的一个小范围的无线网络。为了解决无线传感器的远距离通信中继问题,能够将网络信息通过中继顺利地传送到远程终端,设计了基于移动螃蟹的传感器网络。它以机器螃蟹作为中继,进行数据的本地化处理和融合,实现分布式数据采集和监控。本系统应用于大规模的无线网络,增加了设备状态数据采集与通信的距离,有效地增强了系统的健壮性。 相似文献