Energy Efficient Sleep Schedule with Service Coverage Guarantee in Wireless Sensor Networks

Service oriented architecture has been proposed to support collaborations among distributed wireless sensor network (WSN) applications in an open dynamic environment. However, WSNs are resource constraint, and have limited computation abilities, limited communication bandwidth and especially limited energy. Fortunately, sensor nodes in WSNs are usually deployed redundantly, which brings the opportunity to adopt a sleep schedule for balanced energy consumption to extend the network lifetime. Due to miniaturization and energy efficiency, one sensor node can integrate several sense units and support a variety of services. Traditional sleep schedule considers only the constraints from the sensor nodes, can be categorized to a one-layer (i.e., node layer) issue. The service oriented WSNs should resolve the energy optimization issue considering the two-layer constraints, i.e., the sensor nodes layer and service layer. Then, the one-layer energy optimization scheme in previous work is not applicable for service oriented WSNs. Hence, in this paper we propose a sleep schedule with a service coverage guarantee in WSNs. Firstly, by considering the redundancy degree on both the service level and the node level, we can get an accurate redundancy degree of one sensor node. Then, we can adopt fuzzy logic to integrate the redundancy degree, reliability and energy to get a sleep factor. Based on the sleep factor, we furthermore propose the sleep mechanism. The case study and simulation evaluations illustrate the capability of our proposed approach.     

基于数据融合的无线传感器网络林火监控算法

针对无线传感器网络在林火监控应用中存在的问题,提出了一种分层聚簇数据融合算法。簇内传感器节点使用加权平均法对原始数据进行数据级融合处理,以消除原始数据中的冗余成分,减少从簇内传感器节点到簇头节点的通信量;簇头节点采用D-S证据理论建立识别框架,通过对本簇成员的反馈信号进行决策级融合处理,提高了火灾事件的识别精度和网络的鲁棒性。实验结果表明,该算法能有效消除无线传感器网络的冗余数据,并能够在失效节点数不超过总节点数40%的情况下正确工作。     

Autonomous fault-diagnosis and decision-making algorithm for determining faulty nodes in distributed wireless networks

In this paper, we address fault-diagnosis agreement (FDA) problems in distributed wireless networks (DWNs) with arbitrary fallible nodes and healthy access points. We propose a new algorithm to reach an agreement among fault-free members about the faulty ones. The algorithm is designed for fully connected DWN and can also be easily adapted to partially connected networks. Our contribution is to reduce the bit complexity of the Byzantine agreement process by detecting the same list of faulty units in all fault-free members. Therefore, the malicious units can be removed from other consensus processes. Also, each healthy unit detects a local list of malicious units, which results in lower packet transmissions in the network. Our proposed algorithm solves FDA problems in 2t+1 rounds of packet transmissions, and the bit complexity in each wireless node is O(n^t+1).     

Fuzzy rule-based faulty node classification and management scheme for large scale wireless sensor networks

In a wireless sensor network (WSNs), probability of node failure rises with increase in number of sensor nodes within the network. The, quality of service (QoS) of WSNs is highly affected by the faulty sensor nodes. If faulty sensor nodes can be detected and reused for network operation, QoS of WSNs can be improved and will be sustainable throughout the monitoring period. The faulty nodes in the deployed WSN are crucial to detect due to its improvisational nature and invisibility of internal running status. Furthermore, most of the traditional fault detection methods in WSNs do not consider the uncertainties that are inherited in the WSN environment during the fault diagnosis period. Resulting traditional fault detection methods suffer from low detection accuracy and poor performance. To address these issues, we propose a fuzzy rule-based faulty node classification and management scheme for WSNs that can detect and reuse faulty sensor nodes according to their fault status. In order to overcome uncertainties that are inherited in the WSN environment, a fuzzy logic based method is utilized. Fuzzy interface engine categorizes different nodes according to the chosen membership function and the defuzzifier generates a non-fuzzy control to retrieve the various types of nodes. In addition, we employed a routing scheme that reuses the retrieved faulty nodes during the data routing process. We performed extensive experiments on the proposed scheme using various network scenarios. The experimental results are compared with the existing algorithms to demonstrate the effectiveness of the proposed algorithm in terms of various important performance metrics.     

A novel knowledge-guided evolutionary scheduling strategy for energy-efficient connected coverage optimization in WSNs

One of the most important challenges in designing wireless sensor network is how to construct full-connected network containing least active sensor nodes with satisfied quality of services, such as the coverage rate and energy consumption. This energy-efficiency full-connected coverage optimization problem is modeled as a single-objective optimization problem with constraint. To solve this problem, a knowledge-guided evolutionary scheduling strategy is proposed. Three highlights of this strategy are: (1) Knowledge is defined as the importance of sensor node, which depends on the distance between sensor node and sink node. (2) The genes of an individual correspond to senor nodes in descending order of their importance. (3) Considering sensor nodes’ importance and redundancy rate, knowledge-guided mutation operator and repair strategy are present. Simulation results show that the proposed method can find the optimal full-connected wireless sensor network containing least sensor nodes and consuming less energy for communication by less computation time. Though the coverage rate of the optimum is larger, it still satisfies the coverage constraint. Moreover, this strategy fits for the problems that the communication radius of sensor node is less than two times of its sensing radius.     

Near-optimal communication-time tradeoff in fault-tolerant computation of aggregate functions

This paper considers the problem of computing general commutative and associative aggregate functions (such as Sum) over distributed inputs held by nodes in a distributed system, while tolerating failures. Specifically, there are N nodes in the system, and the topology among them is modeled as a general undirected graph. Whenever a node sends a message, the message is received by all of its neighbors in the graph. Each node has an input, and the goal is for a special root node (e.g., the base station in wireless sensor networks or the gateway node in wireless ad hoc networks) to learn a certain commutative and associate aggregate of all these inputs. All nodes in the system except the root node may experience crash failures, with the total number of edges incidental to failed nodes being upper bounded by f. The timing model is synchronous where protocols proceed in rounds. Within such a context, we focus on the following question:

Under any given constraint on time complexity, what is the lowest communication complexity, in terms of the number of bits sent (i.e., locally broadcast) by each node, needed for computing general commutative and associate aggregate functions?

This work, for the first time, reduces the gap between the upper bound and the lower bound for the above question from polynomial to polylog. To achieve this reduction, we present significant improvements over both the existing upper bounds and the existing lower bounds on the problem.

     

基于累积和控制图的分布式传感网络故障诊断

由于无线气象传感网具有资源受限及分布式等特点,传感器节点的故障诊断面临着很大挑战。针对现有诊断方法误报率高、计算冗余量大的问题,提出了一种基于累积和控制图（CUSUM）与邻居协作融合的故障诊断方法。首先,通过累积和控制图分析传感器节点上的历史数据,提高对节点故障判断的灵敏度并且定位出异常时间点;然后,结合网络内邻居节点间的数据交换,通过判断节点的状态诊断出故障节点。实验结果表明,即使在整个网络中在节点故障率高达35%时,算法检测精度仍然高于97.7%,而误报率不超过2%。由此可见,在节点故障概率很高的情况下,此所提法也能得到很高的检测精度和较低的误报率,受节点故障率的影响明显减小。     

基于传感器网络节点配置优化仿真研究

研究无线传感网络节点配置覆盖优化问题。由于无线传感网络存在着热区问题,对网络的覆盖性能造成严重的影响,同时影响网络配置优化。为了有效的提高无线传感网络的覆盖率,提出了一种改进的粒子群算法优化无线网络节点覆盖。针对粒子群算法存在易陷入局部极值和早熟的缺陷,引入遗传算法中的交叉算子和变异算子,优化传感网络节点的混合粒子群算法,在严格确保无线传感器网络连通性的条件下,传感器节点配置数目达到要求的覆盖度,并进行仿真。仿真结果表明混合粒子群算法能快速收敛到更精确的解,使网络节点配置达到覆盖的优化要求。     

基于时空特性的无线传感器网络节点故障诊断方法

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。对于网络中存在的节点瞬时故障,通过时间冗余的检测方法,降低故障诊断的虚警率。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。     

无冲突的无线传感器网络广播算法

无线传感器网络的节点众多,各种资源严重受限,广播引起的冗余转播加剧了资源的消耗,因而慎重选择转播节点非常关键.提出了一种无冲突的广播策略,该策略利用邻节点能量和度等信息构建最小连通树,减少了转播节点的数量,同时对最小连通树中的节点的转播进行调度,避免冲突的发生.该策略减少网络中节点的能量消费、延长了网络寿命,同时确保了广播的可达性.仿真结果表明该算法提高了广播的效率.     

基于虚拟力算法的WMSNs覆盖研究

为了提高无线多媒体传感器网络（WMSNs）区域覆盖率,在传感器节点随机部署后,通过调节传感器节点的感知方向,使节点从感知重叠区域向覆盖盲区转动,提高网络覆盖率。针对现有算法中存在覆盖效率和覆盖率不能统一的问题,提出一种改进的虚拟力覆盖算法（VFARCR）,该算法利用传感器节点感知扇形区域质心点间的斥力调节感知方向,且通过传感器节点间的覆盖冗余度的决定方向调整的大小,虚拟力和覆盖冗余度共同控制传感器的转动。仿真实验表明：该算法提高了覆盖效率和覆盖效果,提高了虚拟力覆盖算法的性能。     

<Emphasis Type="Italic">k</Emphasis>-Nearest neighbors tracking in wireless sensor networks with coverage holes

Target tracking is one of the important applications of wireless sensor networks (WSNs). Most of the existing approaches assume that the nodes are dense enough and ignore the coverage holes which are very common in WSNs because of random deployment of the sensor nodes, block of obstacles, etc. Besides, predicting the target’s location of the next time instance is unwise because of the quite a lot random factors. In this paper, we propose a novel target tracking approach without any predicting, called k-nearest neighbors tracking (k-NNT), to tackle the problems of energy efficiency, continuity and coverage holes. In k-NNT, only the k-nearest neighbors keep active and track the target when more than k nodes can sense the target; the k′-nearest neighbors work when there are only k′ nodes (k′ < k) can sense the target. A sophisticated rotation mechanism is designed to improve the continuity of the tracking process. In the worst case, none of the nodes can sense the target, i.e., the target enters into the coverage holes, and then k-NNT recovers by the Round Up mode (RU mode). The nodes on the perimeter of the coverage hole always keep active for a time threshold t and sense the around environment to find the target in time. Once a node finds the target, the RU mode is over and the irrelevant nodes turn into inactive mode. A series of simulation show that k-NNT performs superiorly compared with several existing approaches in terms of tracking accuracy, continuity and energy efficiency.     

一种WSN的非一致性数据故障检测机制

针对无线传感器网络数据传输过程中产生的非一致性问题,提出了一种基于无线传感器网络的非一致性故障检测机制IFDM（Inconsistent Failures Detection Mechanism）。IFDM通过采用节点不相交多重路径,比较数据包内容,判断故障路径,并实施故障节点的定位。仿真实验表明,IFDM能有效的检测出非一致性故障路径及故障节点,具有检测速度快、功耗低、时延小等特性。     

Motion fault detection and isolation in Body Sensor Networks

Significant amount of research and development is being directed on monitoring activities of daily living of senior citizens who live alone as well as those who have certain motion disorders such as Alzheimer’s and Parkinson’s. A combination of sophisticated inertial sensing, wireless communication and signal processing technologies has made such a pervasive and remote monitoring possible. Due to the nature of the sensing and communication mechanisms, these monitoring sensors are susceptible to errors and failures. In this paper, we address the issue of identifying and isolating faulty sensors in a Body Sensor Network that is used for remote monitoring of daily living activities. We identify three different types of faults in a Body Sensor Network and propose fault isolation strategies using history-based and non-history based approaches. The contributions of this paper are: (i) faulty sensor node identification in a small number of deployed body sensors (accelerometers); and (ii) identification of a faulty sensor node using a statically or dynamically bound group of sensor nodes that is sharing similar sensor signal patterns.     

Sustainable life-span of WSN nodes using participatory devices in pervasive environment

Wireless sensor network being a dominant prerequisite in the modern pervasive environment has nodes connected with multi-hop to transmit and reinforce continuous monitoring with real-time updates from the field environment. To achieve pervasiveness integrating wireless and physical devices is unavoidable. Numerous self-organized tiny sensor nodes cooperate with each other to form the clusters and the most prominent node act as cluster head (CH). The cluster head pioneered based on its battery forte whose failure affects rest of the communications. In this paper, we discuss on the essential of idle resource sharing using participatory devices as relay nodes along with node failure rate and node density to achieve reliable communication. The earlier performances are observed and results are revealed. Hence we concentrate on minimizing the task of CH using relay nodes such as participatory devices and the faulty nodes are identified over Poisson distribution which observes the failure probability without affecting communication and reduced resource consumption.

     

基于能耗均衡的无线传感器路由算法

为了延长无线传感器的使用寿命,弥补传统路由算法的不足,提出一种基于能耗均衡的无线传感器路由算法。首先,分析了无线传感器节点能量的消耗过程,建立了源节点到目的节点的路由表;然后,通过单跳消息方式确定每一个传感器节点的相邻节点,并把剩余能量信息传递给其相邻节点;最后,根据蚁群算法中的信息素浓度与局部能量来选择无线传感器传输数据时的下一跳节点。通过具体实验对其性能进行了测试,实验结果表明,该算法能耗低,保证了能耗均衡,最大程度地延长了传感器节点的寿命。     

精准农业应用中WSN能量管理研究

在精准农业应用中,传感器节点需持续工作数月,这对能量受限的传感器网络的能量管理提出了更为严峻的挑战。传感器网络的能量管理是一个涉及硬件、操作系统、应用软件的复杂研究领域,需要协调网络各个层次的操作。主要研究节点层的能量管理机制,介绍了节点能量管理的相关研究和TinyOS下的动态能量管理策略,设计了日光温室应用场景中CPU占空比分析机制CPUSA,为进一步的能量优化提供依据。利用示波器获取CPU状态波形并与CPUSA的结果进行对比分析,验证了CPUSA的准确性。     

A fault tolerant peer-to-peer spatial data structure

In recent years, many layered indexing techniques over distributed hash table (DHT)-based peer-to-peer (P2P) systems have been proposed to realize distributed range search. In this paper, we present a fault tolerant constant degree dynamic Distributed Spatial Data Structure called DSDS that supports orthogonal range search on a set of N d-dimensional points published on n nodes. We describe a total order binary relation algorithm to publish points among supernodes and determine supernode keys. A non-redundant rainbow skip graph is used to coordinate message passing among nodes. The worst case orthogonal range search cost in a d-dimensional DSDS with n nodes is \(O\left (\log n+m+\frac {K}{B}\right )\) messages, where m is the number of nodes intersecting the query, K is the number of points reported in range, and B is the number of points that can fit in one message. A complete backup copy of data points stored in other nodes provides redundancy for our DSDS. This redundancy permits answering a range search query in the case of failure of a single node. For single node failure, the DSDS routing system can be recovered to a fully functional state at a cost of O(log n) messages. Backup sets in DSDS nodes are used to first process a query in the most efficient dimension, and then used to process a query containing the data in a failed node in d-dimensional space. The DSDS search algorithm can process queries in d-dimensional space and still tolerate failure of one node. Search cost in the worst case with a failed node increases to \(O\left (d\log n+dm+\frac {K}{B}\right )\) messages for d dimensions.     

基于矩阵的无线传感器网络密钥预分配

为了提高邻居节点建立共享密钥的概率, 减少无线传感器网络资源的消耗, 从而进一步提高无线传感器网络中的连通性, 提出了一种基于矩阵的无线传感器网络的随机密钥部署方案。该方案在无线传感器的目标划分区域中采用3×3矩阵的方式进行密钥预分配, 使邻居节点共享直接密钥的个数为q, 提高了节点间共享密钥的阈值, 减少了节点存储冗余密钥的数量。数据分析和仿真结果表明, 该方案不但在存储密钥数量和安全性方面有较好的性能, 而且连通率为100%。     

一种基于团体的无线传感器网络服务发现协议

服务发现能力是有效应用无线传感器网络的基本要求.提出基于团体的无线传感器网络服务发现协议GSDP,根据传感器节点的运动特性将网络划分为多个团体,每个团体由一个团体头节点和多个成员节点组成.团体头节点构成一个分布式服务目录,负责处理服务注册信息和服务请求信息,避免在网络范围内产生大量的广播信息.仿真实验表明,在具有团体移动特性的传感器网络中,GSDP在保证服务发现性能的同时,能够有效地减少服务发现过程的消息开销.