Effective fault detection and routing scheme for wireless sensor networks

In a wireless sensor network (WSN), random occurrences of faulty nodes degrade the quality of service of the network. In this paper, we propose an efficient fault detection and routing (EFDR) scheme to manage a large size WSN. The faulty nodes are detected by neighbour node’s temporal and spatial correlation of sensing information and heart beat message passed by the cluster head. In EFDR scheme, three linear cellular automata (CA) are used to manage transmitter circuit/ battery condition/microcontroller fault, receiver circuit fault and sensor circuit fault representation. On the other hand, L-system rules based data routing scheme is proposed to determine optimal routing path between cluster head and base station. The proposed EFDR technique is capable of detecting and managing the faulty nodes in an efficient manner. The simulation results show 86% improvement in the rate of energy loss compared to an existing algorithm.     

基于苯环结构的WSNs单向链路故障检测算法

在无线传感器网络（ WSNs）中提出的许多路由算法因其真实应用场景下存在大量单向链路而使其性能大幅降低,甚至无法正常工作。对此如何在WSNs中实现准确、高效能单向链路故障检测成为一个重要的研究课题。针对这种情况提出了一种基于Hello报文的单向链路故障检测（ ALFD-H）算法,该算法充分利用WSNs组成的苯环网络模型,由苯环中心节点发起周期检测信号来完成单向链路故障检测。通过苯环中心节点处理故障单向链路来控制报文数量降低网络资源的消耗,并且提高了网络的连通性和可扩展性。通过NS2仿真实验结果表明：ALFD-H相较传统检测算法采用了苯环网络模型,减少了用于故障检测的能量消耗,从而大大延长了节点的工作时间和网络的生命周期。     

无线传感器网络分簇路由节能研究

在大规模传感和环境监测中,节约能源延长传感器节点生命已成为无线传感器网络最重要的研究课题之一。提供合理的能源消耗和改善无线网络生命周期的传感器网络系统,必须设计一种新的有效的节能方案和节能路由体系。方案采用一种聚类算法减少无线传感器网络的能量消耗,创建一种cluster-tree分簇路由结构的传感器网络。该方案主要目标是做一个理想的分簇分配,减少传感器节点之间的数据传输距离,降低传感器节点能源消耗,延长寿命。实验结果表明,该方案有效地降低了能源消耗从而延长无线传感器网络生命。     

Probabilistic fault detector for Wireless Sensor Network

This paper proposed a novel centralized hardware fault detection approach for a structured Wireless Sensor Network (WSN) based on Naïve Bayes framework. For most WSNs, power supply is the main constraint of the network because most applications are in severe situation and the sensors are equipped with battery only. In other words, the battery’s life is the network’s life. To maximize the network’s life, the proposed method, Centralized Naïve Bayes Detector (CNBD) analyzes the end-to-end transmission time collected at the sink. Thus all the computation will not be performed in individual sensor node that poses no additional power burden to the battery of each sensor node. We have conducted thorough performance evaluation. The obtained results showed better performance can be obtained under a network size of 100-node WSN simulations at various network traffic conditions and different number of faulty nodes.     

无线传感器网络中基于非端到端的区分队列服务

在无线传感器网络中,通信的一方是汇聚节点,通信的另一方不是某一个传感器节点而是一群传感器节点。适用于端到端通信的服务质量方法不再适用于无线传感器网络。为此,提出了一套新的非端到端的事件服务质量参数,并基于此提出了一种基于区分队列服务算法的、为网络中不同的事件提供不同服务质量的方法。通过这一策略,汇聚节点可以及时可靠地检测到待处理的紧急事件。仿真实验结果验证了该方法的可靠性。     

基于梯度的无线传感器网络能耗分析及能量空洞避免机制

在基于"梯度汇聚"模型的无线传感器网络 (Wireless sensor networks, WSNs)中, 因节点间能量消耗不平衡而引发的能量空洞一直是影响网络生存周期的重要原因. 本文分别分析了无通信干扰的自由空间环境和瑞利衰落环境下网络中节点的能量消耗,提出了一种基于节点能量非均匀分布的能量空洞避免机制,即根据节点的能耗水平为每个节点储备不同的初始能量.并结合通信干扰、休眠机制等因素,研究了基于"梯度汇聚"模型的无线传感器网络生存周期的上界和下界. 模拟结果表明,该机制提高了能量的利用效率,延长了网络的生存周期.     

Post-order based routing & transport protocol for wireless sensor networks

In this paper, we propose a lightweight, application independent transport protocol for communication of the nodes belonging to a wireless sensor network (WSN) with the nodes belonging to a local area network. The framework consists of a novel downstream routing scheme and a well-known tree based upstream routing protocol for WSNs. The downstream routing protocol leverages Post-order Numbering (PN) of sensor nodes in the collection tree network formed and maintained by the upstream routing protocol. Through the proposed transport framework, using a technique similar to NATing, we achieve a seamless integration of WSNs and IP networks. The proposed protocol was not only evaluated by extensive simulations, but also implemented on a real test bed to show its practical deployability. We built our test bed around a small Wireless Distribution System (WDS) consisting of two laptop computers and eight Micaz motes attached with MTS300 sensor boards. We connected one of the computers in WDS via Ethernet to the LAN while the other operated as a server with a serial forwarder. A gateway board was attached to the second computer via a USB port which enabled it to function also as a base station for the WSN. A distinct advantage of the proposed framework is that an IP client can directly communicate with a sensor node through its base station.     

Heuristic algorithm for finding boundary cycles in location-free low density wireless sensor networks

Wireless sensor networks (WSNs) comprise a large number of sensor nodes, which are spread out within a region to be monitored and communicate using wireless links. In some WSN applications, recognizing boundary nodes is important for topology discovery, geographic routing, tracking and guiding. In this paper, we study the problem of identifying the boundary nodes of a WSN. In a WSN, close-by nodes can establish direct communications with their neighbors and have the ability to estimate distances to nearby nodes, but not necessarily the true distances. Our objective is to find the boundary nodes by using only the connectivity relation and neighbor distance information without any other knowledge of node locations. Moreover, our main aim is to design a distributed algorithm that works even when the average degree is low. We propose a heuristic algorithm to find the boundary nodes which are connected in a boundary cycle of a location-free, low density (average degree 5–6), randomly deployed WSN. We develop the key ideas of our boundary detection algorithm in the centralized scenario and extend these ideas to the distributed scenario. The distributed implementation is more realistic for real WSNs, especially for sparse networks when all local information cannot be collected very well due to sparse connectivity. In addition, the distributed implementation can tolerate faults by recomputing the boundary locally when a boundary node is faulty. Simulations in ns-2 show that the distributed implementation outperforms the centralized one with higher quality of boundaries.     

一种无线传感器网络节点的故障检测算法

在无线传感器网络(WSN)中,容易因为故障节点存在冗余的故障属性、噪声数据以及数据可靠性等问题,从而产生传输错误数据,这将极大地消耗WSN节点中能量和带宽,向用户形成错误的决策。为此,提出了基于蚁群算法和BP神经网络模型的WSN节点故障检测方法。通过使用蚁群算法,使用户通过寻找优化路径来定位WSN节点的位置,通过这种随机搜索算法以及蚁群算法的搜索策略使用户对WSN故障节点的位置进行总体把握。然后又基于BP神经网络模型对获取的WSN故障节点信息进一步学习,在数据训练过程中,依据WSN故障节点预测误差,并进一步调整网络的权值和阈值,增加了故障诊断的精度。采用的算法对检测WSN故障节点具有较好的性能,使无线传感器网络的服务质量大大提高,增强了系统的稳定性,实验结果验证了算法的可行性和有效性。     

MRNN:一种新的基于改进型递归神经网络的WSN动态建模方法:应用于故障检测

提出了一种适用于无线传感器网络WSN的故障检测方法,该方法运用改进的递归神经网络MRNN为WSN的节点、节点的动态特性以及节点间的关系建立相关模型,对WSN节点进行识别和故障检测。MRNN的输入选择建模节点的先前输出值及其邻居节点的当前及先前输出值,模型基于一种新的改进的反向传播型神经网络,该神经网络的输入以及传感器网络的拓扑结构基于通用的非线性传感器模型。仿真实验将MRNN方法与卡尔曼滤波法进行了全面的比较。实验表明,MRNN在置信因子较小的情况下与卡尔曼滤波方法相比有较高的故障检测精度。     

Editorial

Wireless sensor network(WSN)is characterized by the dense deployment of sensor nodes that continuously observe physical phenomenon.The main advantages of WSN include its low cost,rapid deployment,self-organization,and fault tolerance.WSN has received tremendous interests of various research communities,and significant progresses have been made in various aspects including sensor platform development,wireless communication and networking,signal and information processing,as well as network performance eva...     

FISDR:一种新的故障注入无线传感器网络性能评估系统

在无线传感器网络WSN中,可靠性和容错性是评价WSN稳定性的重要指标。在WSN的实际应用中常会发生很多故障(Fault)和干扰,采用故障注入FI技术可以向WSN人为地注入这些故障和干扰,通过观察注入故障后网络的反应来评价网络的可靠性和容错性,从而对网络机制进行改进来提高网络的可靠性和稳定性。本文提出的FISDR是一种采用故障注入的WSN性能评估系统,基于软件故障注入方法,采用一对一的方式通过特殊接口与WSN节点连接,向WSN节点注入故障命令。该系统一是可以有效地向WSN注入各种实际应用时可能遇到的故障和干扰并观察网络运行的状况;二是可以接收包括WSN节点和其它各种设备通过特殊接口发来的数据,并将其存储;三是配有上位机软件对网络拓扑结构进行监控、对传输成功率进行统计并对存储的大量信息进行分析,从而对WSN网络及其可靠性做出评价。本系统在一栋五层办公楼分别用数十个WSN节点和FISDR节点做实验,实验内容包括使用FISDR向WSN注入大规模的故障并统计网络的反应状况,验证FISDR故障注入的效果,从而对FISDR的性能进行测试和分析。实验结果表明,FISDR可以有效地向WSN注入各种故障以评价其可靠性,在测试WSN及其可靠性评价方面有很高的应用价值。     

WSN中故障诊断性能与平均节点度研究

在基于无线传感器网络的结构健康监测中,故障节点产生并传输的错误数据将消耗节点的能量和带宽,同时会形成结构健康监测的错误决策。针对该问题,提出一种节点故障诊断算法,利用节点感知传感数据的空间相似性,通过对邻节点所感知的传感数据进行比较,确定检测节点的状态,将测试状态向网络中其他相邻节点进行扩散,实现网络中全部节点的故障检测。同时介绍在不同平均节点度下改善故障诊断率的方法。实验结果表明,该算法能够获得较好的性能。     

基于模糊信任的无线传感器网络可信路由

由于无线传感器网络（WSNs）经常部署在苛刻环境下,节点易被物理俘获或损坏,无线多跳通信的方式也使得网络容易遭受各种信号干扰和攻击,路由安全显得尤为重要。在分簇路由协议的基础上,引入了节点可信度作为路由选择的度量,提出了基于模糊信任的无线传感器网络可信路由模型。该模型中,每个节点的信任值由剩余能量、包转发率、路由信息篡改以及声明诚实度等4个属性采用变权模糊综合评判算法得到。仿真结果表明：在变权模糊综合评判算法中,通过提高具有过低值的属性的权值,可以突出节点的缺陷,使得具备过低剩余能量或是过低包转发率,路由信息篡改信任,或过低诚实度任意一个缺陷的节点都不能够得到较高的信任值从而被选为簇头节点,避免行为恶意的节点破坏网络路由。     

Random Walk Routing in WSNs with Regular Topologies

Topology is one of the most important characteristics for any type of networks because it represents the network's inherent properties and has great impact on the performance of the network. For wireless sensor networks (WSN), a well-deployed regular topology can help save more energy than what a random topology can do. WSNs with regular topologies can prolong network lifetime as studied in many previous work. However, little work has been done in developing effective routing algorithms for WSNs with regular topologies, except routing along a shortest path with the knowledge of global location information of sensor nodes. In this paper, a new routing protocol based on random walk is proposed. It does not require global location information. It also achieves load balancing property inherently for WSNs which is difficult to achieve by other routing protocols. In the scenarios where the message required to be sent to the base station is in comparatively small size with the inquiry message among neighboring nodes, it is proved that the random walk routing protocol can guarantee high probability of successful transmission from the source to the base station with the same amount of energy consumption as the shortest path routing. Since in many applications of WSNs, sensor nodes often send only beep-like small messages to the base station to report their status, our proposed random walk routing is thus a viable scheme and can work very efficiently especially in these application scenarios. The random walk routing provides load balancing in the WSN as mentioned, however, the nodes near to the base station are inevitably under heavier burden than those far away from the base station. Therefore, a density-aware deployment scheme is further proposed to guarantee that the heavy-load nodes do not affect the network lifetime even if their energy is exhausted. The main idea is deploying sensors with different densities according to their distance to the base station. It will be shown in this paper that incorporating the random walk routing protocol with the density-aware deployment scheme can effectively prolong the network lifetime.     

Fault tolerance in wireless sensor network using hand-off and dynamic power adjustment approach

Wireless Sensor Network (WSN) is deployed to monitor physical conditions in various places such as geographical regions, agriculture lands, office buildings, industrial plants and battlefields. WSNs are prone to different types of failures due to various environmental hazards like interference and internal failures (such as battery failure, processor failure, transceiver failure, etc). In such a situation, the sensed data cannot be transmitted correctly to the data center and the very purpose of deploying WSNs is not effective. Since it is difficult to monitor the network continuously through a manual operator, the nodes in WSN need to be capable of overcoming the failures and transmit the sensed data in proper order to the data center. Sensor network should be designed such that it should be able to identify the faulty nodes, try to rectify the fault and be able to transmit the sensed data to data center under faulty condition of a network and thereby make the network fault-free and thus enhance the fault tolerant capability.In this paper, we propose a novel idea of an Active node based Fault Tolerance using Battery power and Interference model (AFTBI) in WSN to identify the faulty nodes using battery power model and interference model. Fault tolerance against low battery power is designed through hand-off mechanism where in the faulty node selects the neighboring node having highest power and transfers all the services that are to be performed by the faulty node to the selected neighboring node. Fault tolerance against interference is provided by dynamic power level adjustment mechanism by allocating the time slot to all the neighboring nodes. If a particular node wishes to transmit the sensed data, it enters active status and transmits the packet with maximum power; otherwise it enters into sleep status having minimum power that is sufficient to receive hello messages and to maintain the connectivity. The performance evaluation is tested through simulation for packet delivery ratio, control overhead, memory overhead and fault recovery delay. We compared our results with Fault Detection in Wireless Sensor Networks (FDWSNs) for various performance measures and found that AFTBI outperforms compared to the results of FDWSN.     

Satisfying the target network lifetime in wireless sensor networks

Generally, the lifetime of a wireless sensor network (WSN) is defined as the duration until any sensor node dies due to battery exhaustion. If the traffic load is not properly balanced, the batteries of some sensor nodes may be depleted quickly, and the lifetime of the WSN will be shortened. While many energy-efficient routing schemes have been proposed for WSNs, they focus on maximizing the WSN lifetime. In this paper, we propose a scheme that satisfies a given ‘target’ lifetime. Because energy consumption depends on traffic volume, the target lifetime cannot be guaranteed through energy-efficient routing alone. We take an approach that jointly optimizes the sensing rate (i.e., controlling the sensor-traffic generation or duty cycle) and route selection. Satisfying the target lifetime while maximizing the sensing rate is a NP-hard problem. Our scheme is based on a simple Linear Programming (LP) model and clever heuristics are applied to compute a near-optimal result from the LP solution. We prove that the proposed scheme guarantees a 1/2-approximation to the optimal solution in the worst case. The simulation results indicate that the proposed scheme achieves near-optimality in various network configurations.     

Identifying defective nodes in wireless sensor networks

Wireless sensor networks (WSNs) have become ubiquitous, e.g., in logistics, smart manufacturing, smart city infrastructures or vehicular ad-hoc networks. WSNs tend to rely on ad-hoc infrastructures that are prone to a wide range of different defects, e.g., communication failures, faulty sensors or nodes that have been tampered with. Additionally, dealing with defects is challenging, as defects might occur only occasionally. In this paper, we introduce SEDEL, our approach for Sensor nEtwork DEfect Localization. SEDEL helps the WSN operator to pinpoint defective nodes in the routing topology of a WSN. In particular, we let the operator store graph representations of the routing topology, together with information if the WSN has produced errors. Based on this information, SEDEL assigns each WSN node a suspiciousness score that is correlated with the defect probability. Thus, our approach can be used with any kind of defect, and the kind does not have to be known, as long as the operator can decide if a certain processing is correct or not. We have evaluated SEDEL with a real sensor-node deployment. Our evaluation shows that the defective node is assigned a high probability in the vast majority of the experiments.     

基于加权中值的分布式传感器网络故障检测

无线传感器网络中的错误测量数据会导致网络服务质量下降和能量浪费.提出了一种通过融合邻居节点的测量数据来实现故障检测的策略.主要做了以下3项工作:(1) 提出了一种新颖的对邻居节点测量数据进行加权的方法;(2) 提出了一种衡量测量数据之间差距的方法;(3) 提出了基于加权中值的故障诊断策略WMFDS(weighted median fault detection scheme),它同时适用于二进制决策和实数测量值.理论分析及仿真结果表明,即使节点发生故障的概率很高,提出的诊断策略也能得到很高的检测精度和较小的误判率,这表明在无线传感器网络故障检测中应用该方法具有很好的性能.     

基于最优连通功率控制的WSNs跨层路由优化算法

针对非连通区域节点空洞效应和热点区域节点间通信干扰导致的路由服务质量（QoS）下降问题,提出了一种基于最优连通功率控制的无线传感器网络（WSNs）跨层路由优化算法。算法采用自适应最优连通功率控制策略,在避免路由空洞产生和保证网络连通性条件下,降低热点区域节点数据转发竞争干扰;通过位置信息、剩余能量和干扰等级的跨层信息交互,动态选取最优转发节点,提高网络整体性能。仿真实验表明：算法能够提高路由（QoS）、优化网络生命周期和降低热点区域通信干扰。