Anomaly detection in wireless sensor networks

Anomaly detection in wireless sensor networks is an important challenge for tasks such as fault diagnosis, intrusion detection, and monitoring applications. The algorithms developed for anomaly detection have to consider the inherent limitations of sensor networks in their design so that the energy consumption in sensor nodes is minimized and the lifetime of the network is maximized. In this survey article we analyze the state of the art in anomaly detection techniques for wireless sensor networks and discuss some open issues for research.     

基于区域的异构无线传感器网络密钥管理

密钥管理是无线传感器网络中极具挑战性的安全问题之一.在随机密钥预分配方案的基础上,提出一种利用节点部署知识和已知区域信息的异构无线传感器网络密钥预分配方案,并分别从网络连通性、节点内存需求和安全性等方面对方案进行性能评价和模拟仿真.结果表明,相比现有密钥管理方案,本方案能提高网络的连通性,减小节点所需存储空间,并增强网络抗攻击能力.     

Energy-balance node-selection algorithm for heterogeneous wireless sensor networks

To solve the problem of unbalanced loads and the short network lifetime of heterogeneous wireless sensor networks, this paper proposes a node-selection algorithm based on energy balance and dynamic adjustment. The spacing and energy of the nodes are calculated according to the proximity to the network nodes and the characteristics of the link structure. The direction factor and the energy-adjustment factor are introduced to optimize the node-selection probability in order to realize the dynamic selection of network nodes. On this basis, the target path is selected by the relevance of the nodes, and nodes with insufficient energy values are excluded in real time by the establishment of the node-selection mechanism, which guarantees the normal operation of the network and a balanced energy consumption. Simulation results show that this algorithm can effectively extend the network lifetime, and it has better stability, higher accuracy, and an enhanced data-receiving rate in sufficient time.     

异构无线传感器网络中簇首的优化部署策略

分簇对用于环境监测的无线传感器网络具有较好的适应性和节能性,由高能力节点担任簇首可以更好地实现节能并改善网络性能.在大规模网络中,高能力簇首部署问题是一类NP-hard问题.同时考虑了影响网络性能的簇半径和簇首的容量限制,把簇首的优化部署问题形式化为一个整数规划问题.针对该问题,提出了启发式的基于K-平均和模拟退火混合算法的KMSA算法,对簇首节点进行有策略的部署.仿真结果表明,在不同的网络规模和簇个数情况下,KMSA可以改善网络性能.     

Multilevel heterogeneous network model for wireless sensor networks

The lifetime of a network can be increased by increasing the network energy. The network energy can be increased either increasing the number of sensors or increasing the initial energy of some sensors without increasing their numbers. Increasing network energy by deploying extra sensors is about ten times costlier than that using some sensors of high energy. Increasing the initial energy of some sensors leads to heterogeneous nodes in the network. In this paper, we propose a multilevel heterogeneous network model that is characterized by two types of parameters: primary parameter and secondary parameters. The primary parameter decides the level of heterogeneity by assuming the values of secondary parameters. This model can describe a network up to nth level of heterogeneity (n is a finite number). We evaluate the network performance by applying the HEED, a clustering protocol, on this model, naming it as MLHEED (Multi Level HEED) protocol. For n level of heterogeneity, this protocol is denoted by MLHEED-n. The numbers of nodes of each type in any level of heterogeneity are determined by the secondary model parameter. The MLHEED protocol (for all level heterogeneity) considers two variables, i.e., residual energy and node density, for deciding the cluster heads. We also consider fuzzy implementation of the MLHEED in which four variables are used to decide the cluster heads: residual energy, node density, average energy, and distance between base station and the sensor nodes. In this work, we illustrate the network model up to seven levels (\(1\le n\le 7\)). Experimentally, as the level of heterogeneity increases, the rate of energy dissipation decreases and hence the nodes stay alive for longer time. The MLHEED-m, \(m=2,3,4,5,6,7\), increase the network lifetime by \(73.05, 143.40, 213.17, 267.90, 348.60, 419.10\,\%\), respectively, by increasing the network energy as \(40, 57, 68.5, 78, 84, 92.5\,\%\) with respect to the original HEED protocol. In case of fuzzy implementation, the MLHEEDFL-m, \(m=2,3,4,5,6,7,\) increases the network lifetime by \(282.7, 378.5, 435.78, 498.50, 582.63, 629.79\,\%\), respectively, corresponding to the same increase in the network energy as that of the MLHEED (all levels) with respect to the original HEED. The fuzzy implementation of the HEED, MLHEEDFL-1, increases the network lifetime by \(176.6\,\%\) with respect to the original HEED with no increase in the network energy.     

无线传感器网络中的定位异常检测

在无线传感器网络中位置信息有着重要应用,但是定位过程容易受到恶意攻击者的攻击或环境因素的干扰。为了增加节点定位的安全性。本文提出一种基于节点部署模型的检测方法用来提高定位的安全性能,该方法独立于节点定位过程,根据节点位置的邻居发现和部署知识的一致性判断节点位置是否异常。在具体的异常判断过程中使用一种由马氏距离定义差异矩阵作为比较工具。最后通过Matlab仿真实验分别从检测率,错误警报率两个方面评估验证了该方法的正确性。     

无线传感器网络分布式单向链路检测算法

针对在存在单向链路的网络中如何检测单向链路和如何利用单向链路的问题,提出了3种分布式算法.这3种算法的基本思想是通过Beacon数据包交换一部分链路信息帮助发现单向链路.实验结果显示,使用提出的分布式链路检测算法可以将路由路径的平均长度减少37.8%～39.24%,路由层平均数据发送成功率提高23.82%.模拟实验表明,提出的分布式单向链路检测算法具有很好的可扩展性.     

Channel-aware distributed detection in wireless sensor networks

This paper reviews the classical decentralized decision theory in the light of new constraints and requirements. The central theme that transcends various aspects of signal processing design is that an integrated channel-aware approach needs to be taken for optimal detection performance given the available resources.     

Optimizing event detection in low duty-cycled sensor networks

Duty cycling is a fundamental approach to conserving energy in sensor networks; however, it brings challenges to event detection in the sense that an event may be undetected or undergo a certain delay before it is detected, in particular when sensors are low duty-cycled. We investigate the fundamental relationship between event detection and energy efficiency. We quantify event detection performance by deriving the closed forms of detection delay and detectability with a relatively simple model. We also characterize the intrinsic tradeoff that exists between detection performance and system lifetime, which helps flexible design decisions for sensor networks. In addition, we propose a fully localized algorithm called CAS to cooperatively determine sensor wakeups. Without relying on location information, the distributed algorithm is easy to implement and scalable to network density and scale. Theoretical bounds of event detection are also studied to facilitate comparative study. Comprehensive experiments are conducted and results demonstrate that the proposed algorithm significantly improves event detection performance in terms of detection latency and detection probability. It reduces as high as 31% of detection delay and increases as much as 25% of detectability compared with the random independent scheme.     

Sensor selection for source extraction in heterogeneous wireless sensor networks

A sensor selection scheme for source extraction in heterogeneous wireless sensor networks is proposed. The proposed scheme selects the sensors corresponding to the reconstructed mixtures with the largest signal‐to‐noise‐ratios to transmit their data to a fusion center. It exploits the heterogeneity of the sensor observations and reduces the amount of transmissions. The results demonstrate that the proposed scheme outperforms the full utilization scheme and the random selection scheme. Copyright © 2009 John Wiley & Sons, Ltd.     

Interference mitigation in wireless sensor networks using dual heterogeneous radios

Scalability is one of the most important features that future wireless sensor networks (WSNs) should provide, and clustering is widely considered as a viable approach for high scalability. In the cluster-based architecture, the cluster heads play a key role in relaying messages between the sensor nodes and the sink. While the cluster heads are involved in both intra-cluster and inter-cluster communication, the latter typically requires transmission over much longer distance than the former. In this paper, we consider a scenario in which each cluster head is equipped with dual radios: IEEE 802.15.4 and IEEE 802.11 for intra-cluster and inter-cluster communication, respectively. IEEE 802.11 links between the cluster heads and the sink provide a high capacity backbone for large-scale WSNs. IEEE 802.15.4 and IEEE 802.11 share a lot of similarities including CSMA/CA MAC. Their operating spectrum also overlaps at the 2.4 GHz ISM band, and this may cause interference. We first experimentally measure how severe the interference can be, when two radios are concurrently used in a WSN. We, then, propose an interference mitigation solution which relies on adaptive aggregation of packets and adaptive transmission scheduling. Through prototyping and experimental evaluation, we show that the proposed scheme significantly reduces the interferences between the two types of radios.     

Energy-efficient and fault-tolerant drone-BS placement in heterogeneous wireless sensor networks

Wireless Networks - This paper introduces a distributed and energy-aware algorithm, called Minimum Drone Placement (MDP) algorithm, to determine the minimum number of base stations mounted on...     

无线传感器网络中基于链路质量的路径延时分析

基于链路质量给出了路径满足实时性概率的上界,并证明了计算其上界的时间复杂度为指数级。另外在考虑链路质量的基础上,提出了一种在给定的延迟阈值下最大化端到端数据分组发送成功概率的贪心算法(RROP)。根据给定的延迟阈值和链路质量,RROP算法通过设置每跳链路的最大重传次数来优化端到端数据分组发送成功的概率。证明该算法能够在多项式时间内找到最优解并且通过该最优解获得路径满足实时性概率的一个近似最优的下界。实验结果表明给出的路径延迟分析上界和下界是准确的,并且提出的RROP算法在节省能量和满足实时性上比传统的方法能够获得高出10%以上的性能。     

异构无线网络混合接入与优化机制

在LTE与WSN异构无线网络架构中,有效降低信道接入时的碰撞概率从而提高网络容量吞吐量是影响异构无线网络性能的关键因素。文中建立混合接入模型及超帧结构,完成时分复用结构下的冲突避免,降低了WSN网络的能量消耗。通过时隙优化机制,解决当接入簇首的LTE UE数量变化频繁时竞争时隙配置不合理所导致的网络资源浪费。仿真结果表明,随着LTE UE的数量的增加,协作机制的性能优于传统的随机竞争接入机制,且协作机制的吞吐量性能呈现线性增长。当接入时隙相对充足簇资源利用趋向饱和时,接入概率和网络吞吐量性能均可保持稳定。     

Gravitational outlier detection for wireless sensor networks

Accuracy of sensed data and reliable delivery are the key concerns in addition to several other network‐related issues in wireless sensor networks (WSNs). Early detection of outliers reduces subsequent unwanted transmissions, thus preserving network resources. Recent techniques on outlier detection in WSNs are computationally expensive and based on message exchange. Message exchange‐based techniques incur communication overhead and are less preferred in WSNs. On the other hand, machine learning‐based outlier detection techniques are computationally expensive for resource constraint sensor nodes. The novelty of this paper is that it proposes a simple, non message exchange based, in‐network, real‐time outlier detection algorithm based on Newton's law of gravity. The mechanism is evaluated for its accuracy in detecting outliers, computational cost, and its influence on the network traffic and delay. The outlier detection mechanism resulted in almost 100% detection accuracy. Because the mechanism involves no message exchanges, there is a significant reduction in network traffic, energy consumption and end‐to‐end delay. An extension of the proposed algorithm for transient data sets is proposed, and analytic evaluation justifies that the mechanism is reactive to time series data. Copyright © 2016 John Wiley & Sons, Ltd.     

Energy-efficient event pattern recognition in wireless sensor networks using multilayer spiking neural networks

Wireless Networks - Motivated by the energy-efficient computation of the brain, an energy-efficient wireless sensor network infrastructure is built for solving the pattern recognition task. In this...     

Cooperative fault‐detection mechanism with high accuracy and bounded delay for underwater sensor networks

This paper proposes a cooperative fault‐detection mechanism for detecting cluster‐head failures in cluster‐based UnderWater Sensor Networks (UWSNs). The proposed detection mechanism aims to accurately and fast detect the failure of a cluster head in order to avoid unnecessary energy consumption caused by a mistaken detection. For this purpose, it allows each cluster member to independently detect the fault status of its cluster head and then employs a distributed agreement protocol to reach an agreement on the fault status of the cluster head among multiple cluster members. It runs concurrently with normal network operation by periodically performing a detection process at each cluster member. To reduce energy consumption, it uses a time division multiple access medium access control (TDMA MAC) protocol and makes use of the data periodically sent by a cluster head as the heartbeats for fault detection. A couple of forward and backward time‐division‐multiplexing (TDM) frames are specially structured for enabling multiple cluster members to reach an agreement within two frames in each detection process. Moreover, a schedule generation algorithm is also proposed for a cluster head to generate the transmission schedule in the forward and backward frames. Through simulation results, we show that the proposed detection mechanism can achieve high detection accuracy under high packet loss rates in the harsh underwater environment, and can detect a cluster‐head failure faster than a traditional fault‐detection mechanism within a delay bound of two TDM frames. Copyright © 2008 John Wiley & Sons, Ltd.