无感知分组丢失下的无线传感器网络链路质量评估模型

针对现有链路质量评估方法没有考虑到不完整分组对链路产生的影响,将无线传感器网络的链路分组丢失分为感知分组丢失和无感知分组丢失,分析了无感知分组丢失产生的原因,在对无感知分组丢失进行度量的基础上,提出一种无感知分组丢失下的链路质量评估模型。该模型采用卡尔曼滤波对获取的CCI进行降噪处理,基于Cubic模型、最小二乘法拟合出CCI与无感知分组丢失率的关系模型。实验结果表明,无感知分组丢失下的链路质量评估模型是合理的,通过该模型求得的无感知分组丢失率与实测值接近。     

无线传感器网络链路通信质量测量研究

首先分析了传统链路测量方法所存在的问题,提出了均值RSSI(接收信号强度显示)、均值LQI(链路质量显示)测量法,通过测量及计算RSSI、LQI的均值,可以较为准确地获得链路通信质量信息;其次构建了发送功率改变、硬件校准改变、周围环境改变和并发干扰等实验案例,分析了均值RSSI、均值LQI在上述案例下的测量性能,定义了链路测量灵敏度,计算了均值RSSI、均值LQI的灵敏度值,对RSSI及LQI用于链路通信质量测量和性能评估做出了全面的权衡。     

Deep belief network-based link quality prediction for wireless sensor network

After analyzing the existing link quality prediction models,a link quality prediction model for wireless sensor network was proposed,which was based on deep belief network.Support vector classification was employed to estimate link quality,so as to get link quality levels.Deep belief network was applied in extracting the features of link quality,and softmax was taken to predict the next time link quality.In different scenarios,compared with the model of link quality prediction based on logistic regression,BP neural network and Bayesian network methods,the experimental results show that the proposed prediction model achieves better precision.     

Link quality estimation for arbitrary packet sizes over wireless links using packet reception events

The packet error rate of wireless links is known to increase with the length of packets. Yet, packet length is rarely taken into account in protocols and algorithms estimating the packet error rate. Still, it is an important factor that higher layer protocols need to be aware of. In this article, we systematically measure the relationship between packet length and packet error rate over a wide range of wireless links and technologies. On the basis of our measurements, we propose a simple empirical model that can capture this behavior. Using this model, multiple methods are proposed that can estimate the packet error rate for any packet length by sampling the link. We consider methods based on hello packets with controlled packet lengths as well as data packets, where the transmitted packet lengths cannot be controlled. We investigate the accuracy of the different estimation methods in various situations and show how they are able to predict the delivery ratio for different packet sizes.     

An energy‐efficient link quality monitoring scheme for wireless networks

Link quality is one of the most important factors that affect the performance of wireless networks. In a densely deployed wireless network, continuous link quality monitoring consumes significant amount of energy and bandwidth at each node. In this paper, we propose a sensitivity model and a spatial correlation model that can be used to derive a set of deputy links to monitor, instead of monitoring all of the links in the network. The proposed scheme can improve energy efficiency of the link quality monitoring process. A greedy algorithm is presented to derive the deputy links set based on three different optimization objective functions. Performance of the proposed method is studied extensively and it is shown that the proposed method can save almost 90% energy in typical simulation scenarios than the method of monitoring all links. We also demonstrate that the energy consumption of the greedy deputy set‐based method is upper‐bounded. Copyright © 2010 John Wiley & Sons, Ltd.     

Study on AdaBoost-based link quality prediction mechanism

The link quality was vulnerable to the complexity environment in wireless sensor network.Obtaining link quality information in advance could reduce energy consumption of nodes.After analyzing the existing link quality prediction methods,AdaBoost-based link quality prediction mechanism was put forward.Link quality samples in deferent scenarios were collected.Density-based unsupervised clustering algorithm was employed to classify training samples into deferent link quality levels.The AdaBoost with SVM-based component classifiers was adopted to build link quality prediction mechanism.Experimental results show that the proposed mechanism has better prediction precision.     

Integrated mutual selection based code dissemination for reprogramming wireless sensor networks

Code dissemination is an important building block of wireless reprogramming. We notice that current code dissemination protocols fails to consider page selection and energy balancing. In this paper, we present an integrated mutual selection based code dissemination protocol (MSD). The key idea of MSD is mutual selection comprising sender selection and page selection. By exploiting link quality information in mutual selection, MSD enhances the propagation. Further, MSD takes energy level information in the sender selection, thus avoiding low power nodes’ over-consumption. We simulate MSD by settings of Mica-Z motes. Simulation results show that MSD can reduce the completion time and average transmission, and help low power nodes avoid unnecessary transmission and energy consumption.     

An indicator kriging method for distributed estimation in wireless sensor networks

The problem of distributed estimation in a wireless sensor network with unknown observation noise distribution is investigated, where each sensor only sends quantized data to a fusion center. The sensing field is modeled as a spatially random field. The objective was to accurately estimate a hidden parameter at the location where no sensor exists, while minimizing the total energy consumption. Driven by the lack of a prior knowledge of the sensing field and the existence of some outliers, an indicator kriging estimator is developed for distributed estimation under imperfect communication channels between the sensors and the fusion center. The tradeoff between estimation performance and energy consumption is formulated as an optimization problem, and a global search algorithm is proposed to approximate the solution. The results show that the proposed indicator kriging estimator achieves better performance than the inverse distance estimator and the simple averaging estimator. Moreover, the proposed search algorithm can schedule the sensors to reach the tradeoff. Copyright © 2012 John Wiley & Sons, Ltd.     

Exploiting classification for fountain data estimation in wireless sensor networks

In order to correct and avoid channel error, fountain codes were the best solution by limiting feedback channels and reducing energy consumption. Multi‐hops transmission is the principal limitation of the deployment and the use of these codes. Indeed, relayed transmission conducts to the generation of useless data, named overflow leading to a waste of energy, the most critical issue, and the big challenge in WSN. In this paper, based on a clustered architecture and estimation, we consider a distributed estimation scheme composing of sensor members and the cluster head. In order to reduce the number of a useless encoded packet generated as well as the impact of the overflow, we determine the optimal minimal number of encoded packets needed for data decoding. Sensor observations are encoded using fountain codes, and then messages are collected at the cluster head where a final estimation is provided within learning method. Then messages are collected at the cluster head where a final estimation is provided with a classification based on Bayes rule. The main goal of this paper is to determine the number of encoded packets by exploiting the classification model for fountain data estimation to minimize the overflow and extend the network lifetime.     

QoS-guaranteed packet scheduling in wireless networks

To guarantee the quality of service (QoS) of a wireless network, a new packet scheduling algorithm using cross-layer design technique is proposed in this article. First, the demand of packet scheduling for multimedia transmission in wireless networks and the deficiency of the existing packet scheduling algorithms are analyzed. Then the model of the QoS-guaranteed packet scheduling (QPS) algorithm of high speed downlink packet access (HSDPA) and the cost function of packet transmission are designed. The calculation method of packet delay time for wireless channels is expounded in detail, and complete steps to realize the QPS algorithm are also given. The simulation results show that the QPS algorithm that provides the scheduling sequence of packets with calculated values can effectively improve the performance of delay and throughput.     

无线Mesh网络中基于链路负载估算的拥塞控制策略

针对无线Mesh网络的网络特性,提出了一种基于链路负载估算的拥塞控制策略LLECC。LLECC算法计算有效链路带宽和链路负载估算确定RED算法中的调整因子,通过调整因子调整RED算法中的参数从而实现动态的对无线网络拥塞控制。详细讨论了LLECC算法的实现过程和相关参数的计算方法,通过仿真分析验证了该算法对无线Mesh网络性能的提高。     

Dual‐mode multiple‐target tracking in wireless sensor networks based on sensor grouping and maximum likelihood estimation

The problem of tracking multiple mobile targets, using a wireless sensor network, is investigated in this paper. We propose a new sensor grouping algorithm, based on the maximum sensor separation distances (G‐MSSD), for estimating the location of multiple indistinguishable targets, either jointly or individually, depending on the distances between the generated groups. The joint tracking algorithm is formulated as a maximum likelihood (ML) estimator and solved through a modified version of the well‐known Gauss‐Newton (MGN) iterative method. We propose two candidate initial guesses for MGN based on G‐MSSD in joint tracking mode, while for the individual mode, the information of each group is used to estimate the location of only the corresponding target. The Cramer‐Rao lower bound (CRLB) for the variance of the proposed ML estimator is derived, and the potential conditions for reducing the CRLB are presented. Since tracking efficiency is affected by poor estimates, we present two criteria to evaluate the quality of estimates and detect the poor ones. An approach is also proposed for correcting the poor estimates, based on additional initial guesses. We demonstrate the effectiveness and accuracy of our proposed dual‐mode algorithm via simulation results and compare our results with the Multi‐Resolution search algorithm.     

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.     

Efficient broadcasting protocols for regular wireless sensor networks

The wireless sensor network (WSN) has attracted lots of attention recently. Broadcast is a fundamental operation for all kinds of networks and it has not been addressed seriously in the WSN. Therefore, we propose two types of power and time efficient broadcasting protocols, namely one‐to‐all and all‐to‐all broadcasting protocols, for five different WSN topologies. Our one‐to‐all broadcasting protocols conserve power and time by choosing as few relay nodes as possible to scatter packets to the whole network. Besides, collisions are carefully handled such that our one‐to‐all broadcasting protocols can achieve 100% reachability. By assigning each node a proper channel, our all‐to‐all broadcasting protocols are collision free and efficient. Numerical evaluation results compare the performance of the five topologies and show that our broadcasting protocols are power and time efficient. Copyright © 2005 John Wiley & Sons, Ltd.     

基于RSSI的传感器网络节点安全定位机制

针对RSSI测距存在的脆弱性问题,提出了一种基于完整性编码和不间断占用信道的安全RSSI测距协议,该协议不仅可以抵抗伪造插入、重放/虫洞等常规攻击,而且可以防止信标信号被恶意干扰而削弱,即可抵抗虚增测距的外部攻击。在此基础上,设计了一种基于RSSI的传感器网络节点安全定位机制,该机制采用可校验的多边测量法来过滤虚减测距的外部攻击,实现安全定位,并对测距协议和定位机制的安全性进行了理论分析。     

Coverage hole problem under sensing topology in flat wireless sensor networks

In flat wireless sensor networks, one fundamental issue is region coverage, which usually addresses whether the given region is sufficiently covered by sensing disks of sensor nodes or not. Although numerous research works have been carried out on region coverage, it still lacks in‐depth understanding on the relations between region coverage and sensing topology defined with the intersections of sensing areas of sensor nodes. In this paper, we consider the region coverage problem by using the sensing topology proposed in our previous work. Based on the notion of sensing topology, we prove that the given region can be partitioned into a number of the smallest cells, each of which is defined by sensing links among sensor nodes. Then, we investigate the sufficient and necessary conditions for the existence of coverage holes for the specific polygon graph residing in the partitioned cells. Further, two polynomial time algorithms are presented for dividing the given region covered by the whole network and detecting the coverage holes existing in the interior area of the partitioned cells, respectively. The experiment results show that our proposed algorithms are effective for detecting the coverage holes. Copyright © 2014 John Wiley & Sons, Ltd.     

An adaptive joining mechanism for improving the connection ratio of ZigBee wireless sensor networks

Wireless sensor networks (WSNs) are well suited to many applications, including environment surveillance and target tracking. ZigBee is an IEEE 802.15.4‐based standard that is considered suitable for WSNs. The functional operations of a ZigBee network rely on self‐organized network connections and the proper deployment of sensor devices. However, the devices comprising a ZigBee network may become isolated from the network after the joining phase due to the configuration constraints of the ZigBee standard. This means that some deployed devices cannot join the network even though they can communicate with other joined nodes. These isolated devices reduce the efficiency of network operation and increase deployment costs. This paper proposes a ZigBee‐compatible adaptive joining mechanism with connection shifting schemes to improve the connectivity of ZigBee networks, allowing them to operate at the expected efficiency. Simulation results show that the proposed mechanism significantly improves the join ratio of deployed sensor devices in ZigBee WSNs. Copyright © 2009 John Wiley & Sons, Ltd.     

A pragmatic approach to area coverage in hybrid wireless sensor networks

Success of Wireless Sensor Networks (WSN) largely depends on whether the deployed network can provide desired area coverage with acceptable network lifetime. This paper seeks to address the problem of determining the current coverage achieved by the non‐deterministic deployment of static sensor nodes and subsequently enhancing the coverage using mobile sensors. We identify three key elements that are critical for ensuring effective area coverage in Hybrid WSN: (i) determining the boundary of the target region and evaluating the area coverage (ii) locating coverage holes and maneuvering mobile nodes to fill these voids, and (iii) maintaining the desired coverage over the entire operational lifetime of the network. We propose a comprehensive solution that addresses all of the aforementioned aspects of the area coverage, called MAPC (mobility assisted probabilistic coverage). MAPC is a distributed protocol that operates in three distinct phases. The first phase identifies the boundary nodes using the geometric right‐hand rule. Next, the static nodes calculate the area coverage and identify coverage holes using a novel probabilistic coverage algorithm (PCA). PCA incorporates realistic sensing coverage model for range‐based sensors. The second phase of MAPC is responsible for navigating the mobile nodes to plug the coverage holes. We propose a set of coverage and energy‐aware variants of the basic virtual force algorithm (VFA). Finally, the third phase addresses the problem of coverage loss due to faulty and energy depleted nodes. We formulate this problem as an Integer Linear Program (ILP) and propose practical heuristic solutions that achieve similar performance as that of the optimal ILP solution. A guiding principle in our design process has been to ensure that the MAPC can be readily implemented in real‐world applications. We implemented the boundary detection and PCA algorithm (i.e., Phase I) of the MAPC protocol on off‐the‐shelf sensor nodes and results show that the MAPC can successfully identify boundary nodes and accurately determine the area coverage in the presence of real radio irregularities observed during the experiments. Extensive simulations were carried out to evaluate the complete MAPC protocol and the results demonstrate that MAPC can enhance and maintain the area coverage, while reducing the total energy consumption by up to 70% as compared with the basic VFA. Copyright © 2010 John Wiley & Sons, Ltd.     

Position‐based adaptive quantization for target location estimation in wireless sensor networks using one‐bit data

The problem of target location estimation in a wireless sensor network is considered, where due to the bandwidth and power constraints, each sensor only transmits one‐bit information to its fusion center. To improve the performance of estimation, a position‐based adaptive quantization scheme for target location estimation in wireless sensor networks is proposed to make a good choice of quantizer' thresholds. By the proposed scheme, each sensor node dynamically adjusts its quantization threshold according to a kind of position‐based information sequences and then sends its one‐bit quantized version of the original observation to a fusion center. The signal intensity received at local sensors is modeled as an isotropic signal intensity attenuation model. The position‐based maximum likelihood estimator as well as its corresponding position‐based Cramér–Rao lower bound are derived. Numerical results show that the position‐based maximum likelihood estimator is more accurate than the classical fixed‐quantization maximum likelihood estimator and the position‐based Cramér–Rao lower bound is less than its fixed‐quantization Cramér‐Rao lower bound. Copyright © 2015 John Wiley & Sons, Ltd.     

Efficient delivery‐guaranteed geographic routing in 3D wireless sensor networks with holes

In many applications, sensor nodes are deployed in a 3D environment with obstacles, in which case a great deal of holes exist in 3D wireless sensor networks constructed. Recently, several geographic routing protocols are proposed for 3D wireless sensor networks. Each of them, however, cannot guarantee packet delivery or demands a long routing path to turn around a hole. In this paper, we first introduce a method of constructing a guide to the navigation on the surface of a hole. Subsequently, a geographic routing protocol termed the Greedy‐Guide_Navigation‐Greedy protocol (GGNG) that can always route a packet to turn around a hole with the help of the guide is proposed. GGNG guarantees packet delivery and can be extended toward a mobile sensor network in a limited 3D space. Simulations show that the path stretch of each routing protocol to GGNG in approximately 90 % of the cases is between 1.02 and 189.24. In addition, the number of messages transmitted by a node surrounding a hole in the guide construction is approximately three. Copyright © 2014 John Wiley & Sons, Ltd.