无线传感网离群点检测技术研究综述

无线传感器网络(wireless sensor network,WSN)受电池能量、计算能力、通信能力和内存空间及传感数据多维特征的限制,传统的离群点检测技术不能直接应用于WSN,因此出现了一系列针对WSN的离群点检测技术.对已有的WSN离群点检测技术进行了概述,根据各离群点检测技术的特征进行了分类和分析,并结合现有技术的缺陷和需求,展望了WSN离群点检测技术的未来研究方向和目标.     

In-network outlier detection in wireless sensor networks

To address the problem of unsupervised outlier detection in wireless sensor networks, we develop an approach that (1) is flexible with respect to the outlier definition, (2) computes the result in-network to reduce both bandwidth and energy consumption, (3) uses only single-hop communication, thus permitting very simple node failure detection and message reliability assurance mechanisms (e.g., carrier-sense), and (4) seamlessly accommodates dynamic updates to data. We examine performance by simulation, using real sensor data streams. Our results demonstrate that our approach is accurate and imposes reasonable communication and power consumption demands.     

基于椭球模型的无线传感器网络的局部离群点检测

针对现有的无线传感器网络(WSNs)的局部离群点检测算法由于存在未考虑监测环境的异质性而造成邻域划分不准确、检测精度低的问题,提出适用于异质监测环境的基于椭球模型的无线传感器网络的局部离群点检测算法.算法用椭球模型刻画数据分布,节点间只传输模型参数,用椭球参数式方程计算椭球间的相异度;将数据分布的不一致性引入到邻域划分的过程中,最终利用传感数据的时空关联性来确定局部离群点.实验结果表明,提出的算法具有通信量低、检测精度高和误检率低的优点.     

Deployment techniques in wireless sensor networks: a survey,classification, challenges,and future research issues

The Journal of Supercomputing - Wireless sensor networks (WSNs) have been considered as one of the fine research areas in recent years because of vital role in numerous applications. To process the...     

室内环境下无线传感网络路径衰减特性

在室内环境中,墙壁的阻碍和反射会严重的影响无线传感网络中的信号传输特性.针对室内环境中传感节点的部署和应用的环境的特性,研究了无线信号在遇到墙壁反射时的传播特性,推导出了其对应的路径衰减.并基于视距传输和墙壁反射,提出了一种新的室内路径衰减模型.为了验证提出的路径衰减模型,针对室内房间和走廊环境,基于2.4 GHz载波频率,对无线传感节点的路径衰减和遮蔽效应进行了大量的实测实验.实验结果表明:提出的路径衰减模型可以很好地反映无线信号在室内的衰减特性.     

A survey on routing techniques in underwater wireless sensor networks

Underwater Wireless Sensor Networks (UWSNs) are finding different applications for offshore exploration and ocean monitoring. In most of these applications, the network consists of significant number of sensor nodes deployed at different depths throughout the area of interest. The sensor nodes located at the sea bed cannot communicate directly with the nodes near the surface level; they require multi-hop communication assisted by appropriate routing scheme. However, this appropriateness depends not only on network resources and application requirements but also on environmental constraints. All these factors provide a platform where a resource-aware routing strategy plays a vital role to fulfill the different application requirements with dynamic environmental conditions. Realizing the fact, significant attention has been given to construct a reliable scheme, and many routing protocols have been proposed in order to provide an efficient route discovery between the sources and the sink. In this paper, we present a review and comparison of different algorithms, proposed recently in order to fulfill this requirement. The main purpose of this study is to address the issues like data forwarding, deployment and localization in UWSNs under different conditions. Later on, all of these are classified into different groups according to their characteristics and functionalities.     

Topology management techniques for tolerating node failures in wireless sensor networks: A survey

In wireless sensor networks (WSNs) nodes often operate unattended in a collaborative manner to perform some tasks. In many applications, the network is deployed in harsh environments such as battlefield where the nodes are susceptible to damage. In addition, nodes may fail due to energy depletion and breakdown in the onboard electronics. The failure of nodes may leave some areas uncovered and degrade the fidelity of the collected data. However, the most serious consequence is when the network gets partitioned into disjoint segments. Losing network connectivity has a very negative effect on the applications since it prevents data exchange and hinders coordination among some nodes. Therefore, restoring the overall network connectivity is very crucial. Given the resource-constrained setup, the recovery should impose the least overhead and performance impact. This paper focuses on network topology management techniques for tolerating/handling node failures in WSNs. Two broad categories based on reactive and proactive methods have been identified for classifying the existing techniques. Considering these categories, a thorough analysis and comparison of all the recent works have been provided. Finally, the paper is concluded by outlining open issues that warrant additional research.     

传感网中链路干扰优化的拓扑控制综述

拓扑控制是降低传感器网络能耗、为MAC及路由等上层协议提供支持的关键手段。对于广泛采用共享信道的传感器网络来说,并发链路的干扰严重降低了网络的传输效率、浪费了有限的网络资源。因此,降低干扰被认为是拓扑控制的最重要的目标之一。全面分析了面向链路干扰优化的传感器网络拓扑控制技术的研究进展,首先对不同的链路干扰模型进行了分析和比较,然后描述了基于不同模型的拓扑控制算法的执行流程和复杂度,分析了现有工作的特点和不足之处,同时指出了需要进一步研究的问题。     

基于无线传感器网络的车辆检测识别算法研究

针对无线传感器网络(WSNs)的特点,利用车辆发出的声音信号,提出并研究了一种改进的信号检测算法,能够有效地从被噪声严重污染的声音信号中提取出车辆信号。使用小波包变换提取16维信号特征,支持向量机进行目标分类,得到单节点识别结果。提出了基于能量的全局决策融合算法,对多个节点做出的决策进行融合,得到网络的最终识别结果。为了评估算法,使用了来自DARPA SensIT实验中的真实数据,其中包含了履带车和重型卡车的大量声音信号。实验结果表明:该算法用于WSNs中的车辆识别方面是有效的。     

Perimeter detection in wireless sensor networks

For a mobile robotic agent to bridge the gaps between disconnected networks, it is beneficial for the robot to first determine the network coverage boundary. Several techniques have been introduced to determine the boundary nodes of a network, but the correctness of these techniques is often ill-defined. We present a technique for obtaining boundary node ground truth from region adjacency analysis of a model-based image created from a network graph. The resulting ground truth baseline is then used for quantitative comparison of several boundary detection methods including a local application of the image region adjacency analysis and the computation of the local convex hull with the addition of a perturbation value to overcome small boundary concavities in the node location point set. Given our proposed metrics of the techniques evaluated, the perturbed convex hull technique demonstrates a high success rate for boundary node identification, particularly when the convex hull is formed using two-hop neighborhoods. This technique was successfully implemented on a physical 25-node network, and the performance of this network implementation is evaluated.     

Transmission power control techniques for wireless sensor networks

Communication is usually the most energy-consuming event in Wireless Sensor Networks (WSNs). One way to significantly reduce energy consumption is applying transmission power control (TPC) techniques to dynamically adjust the transmission power. This article presents two new TPC techniques for WSNs. The experimental evaluation compares the performance of the TCP techniques with B-MAC, the standard MAC protocol of the Mica 2 platform. These experiments take into account different distances among nodes, concurrent transmissions and node mobility. The new transmission power control techniques decrease energy consumption by up to 57% over B-MAC while maintaining the reliability of the channel. Under a low mobility scenario, the proposed protocols delivered up to 95% of the packets, showing that such methods are able to cope with node movement. We also show that the contention caused by higher transmission levels might be lower than analytical models suggest, due to the action of the capture effect.     

LAD: Localization anomaly detection for wireless sensor networks

In wireless sensor networks (WSNs), sensors’ locations play a critical role in many applications. Having a GPS receiver on every sensor node is costly. In the past, a number of location discovery (localization) schemes have been proposed. Most of these schemes share a common feature: they use some special nodes, called beacon nodes, which are assumed to know their own locations (e.g., through GPS receivers or manual configuration). Other sensors discover their locations based on the reference information provided by these beacon nodes. Most of the beacon-based localization schemes assume a benign environment, where all beacon nodes are supposed to provide correct reference information. However, when the sensor networks are deployed in a hostile environment, where beacon nodes can be compromised, such an assumption does not hold anymore. In this paper, we propose a general scheme to detect localization anomalies that are caused by adversaries. Our scheme is independent from the localization schemes. We formulate the problem as an anomaly intrusion detection problem, and we propose a number of ways to detect localization anomalies. We have conducted simulations to evaluate the performance of our scheme, including the false positive rates, the detection rates, and the resilience to node compromises.     

Secure localization and location verification in wireless sensor networks: a survey

The locations of sensor nodes are very important to many wireless sensor networks (WSNs). When WSNs are deployed in hostile environments, two issues about sensors’ locations need to be considered. First, attackers may attack the localization process to make estimated locations incorrect. Second, since sensor nodes may be compromised, the base station (BS) may not trust the locations reported by sensor nodes. Researchers have proposed two techniques, secure localization and location verification, to solve these two issues, respectively. In this paper, we present a survey of current work on both secure localization and location verification. We first describe the attacks against localization and location verification, and then we classify and describe existing solutions. We also implement typical secure localization algorithms of one popular category and study their performance by simulations.     

Machine learning algorithms for wireless sensor networks: A survey

Wireless sensor network (WSN) is one of the most promising technologies for some real-time applications because of its size, cost-effective and easily deployable nature. Due to some external or internal factors, WSN may change dynamically and therefore it requires depreciating dispensable redesign of the network. The traditional WSN approaches have been explicitly programmed which make the networks hard to respond dynamically. To overcome such scenarios, machine learning (ML) techniques can be applied to react accordingly. ML is the process of self-learning from the experiences and acts without human intervention or re-program. The survey of the ML techniques for WSNs is presented in [1], covering period of 2002–2013. In this survey, we present various ML-based algorithms for WSNs with their advantages, drawbacks, and parameters effecting the network lifetime, covering the period from 2014–March 2018. In addition, we also discuss ML algorithms for synchronization, congestion control, mobile sink scheduling and energy harvesting. Finally, we present a statistical analysis of the survey, the reasons for selection of a particular ML techniques to address an issue in WSNs followed by some discussion on the open issues.     

Time synchronization methods for wireless sensor networks: A survey

Wireless sensor networks consist of many nodes that collect real-world data, process them, and transmit the data by radio. Wireless sensor networks represent a new, rapidly developing direction in the field of organization of computer networks of free configuration. Sensor networks are used for monitoring a parameter field, where it is often required to fix time of an event with high accuracy. High accuracy of local clocks is also necessary for operation of network protocols (for energy-saving purposes, the nodes spend most of the time in the sleeping mode and communicate only occasionally). In the paper, base techniques used in the existing time synchronization schemes are analyzed; models of local clock behavior and models of interaction of the network devices are described; classification of the synchronization problems is presented; and a survey of the existing approaches to synchronization of time in sensor networks is given.     

无线传感器网络中节点故障诊断方法的研究

无线传感器网络中故障节点会产生并传输错误数据,这将消耗节点的能量和带宽,同时会形成错误的决策。利用节点感知数据的空间相似性,提出了节点故障诊断的算法,通过对邻节点所感知的传感数据进行比较,从而确定检测节点的状态,并将测试状态向网络中其他相邻节点进行扩散。该算法对实现故障节点的检测具有较好的性能,实验结果验证了算法的可行性和有效性。     

基于压缩感知的无线传感器网络数据收集研究综述

为了对无线传感器网络的压缩数据收集有一个全面的认识和评估,对到目前为止国内外的相关研究成果作了一个系统的介绍。首先,介绍了压缩数据收集及改进方法的框架的建立;然后,分别根据无线传感器网络的传输模式和压缩感知理论的三要素,对压缩数据收集方法分类进行了阐述;接下来,说明了压缩数据收集的自适应和优化问题,与其他方法的联合应用,及实际应用范例;最后,指出了压缩数据收集存在的问题和未来的发展方向。     

Designing robust network topologies for wireless sensor networks in adversarial environments

In this paper, we address the problem of deploying sink nodes in a wireless sensor network such that the resulting network topology be robust. In order to measure network robustness, we propose a new metric, called persistence, which better captures the notion of robustness than the widely known connectivity based metrics. We study two variants of the sink deployment problem: sink selection and sink placement. We prove that both problems are NP-hard, and show how the problem of sink placement can be traced back to the problem of sink selection using an optimal search space reduction technique, which may be of independent interest. To solve the problem of sink selection, we propose efficient heuristic algorithms. Finally, we provide experimental results on the performance of our proposed algorithms.