水下传感器网络时间同步技术综述

 时间同步是传感器节点协同工作的基础.水下传感器网络由于采用水声通信方式,具有不同于陆地无线传感器网络的特点,为时间同步算法研究带来了新的挑战.论文首先说明同步问题与同步算法的形式化定义,然后讨论水下传感器网络不同于陆地传感器网络的特点,并指出相关特点对于同步问题的影响;接着综述陆地传感器网络同步算法的研究进展,分析相关算法用于水下环境的不足;进而介绍水下传感器网络同步算法的研究进展,并通过仿真实验完成了相关算法的性能对比;最后总结水下传感器网络时间同步的关键问题,指出进一步的研究方向.     

无线传感器网络中平均跳距修正的DV-Hop定位算法

针对基本无线传感器网络DV-Hop定位算法中,计算平均跳距时产生偏小误差的原因,提出了基于平均跳距修正的DV-Hop算法。改进算法中,引入信标节点个数比例、所有信标节点平均跳距的最大值以及所有信标节点平均跳距的平均值三个因子,并采用它们对平均跳距进行修正。通过Matlab软件对算法进行仿真验证,结果表明,改进后的DV-Hop算法有效降低了未知节点的定位误差,是一种可行的无线传感器网络节点定位解决方案。     

基于无线传感器网络的一种改进Dv-Hop算法

无线传感器网络中的Dv-Hop算法是一种无需测距的节点定位算法,经仿真观察,该算法在信标节点密度较低时节点平均误差较大且稳定性不好.提出了一种改进Dv-Hop算法,即在一个网络区域的边缘设置信标节点.经仿真验证,该算法在和Dv-Hop同等信标节点密度的情况下,在定位精度、节点定位的稳定性以及能源消耗方面都有所改善.     

基于移动模型的水下传感器网络时间同步算法

水下传感器网络具有高时延、移动性的特点。现有时间同步算法在网络移动性方面考虑不足,时间同步参数计算精度不高。针对该问题,首先分析网络移动性对时间同步参数计算的影响,建立节点移动模型,并在此基础上推导出时间同步参数计算方程;进而提出一种能够应用于水下高时延网络的时间同步算法MM-sync。实验结果表明,与现有算法相比,MM-sync能够在通信量较小的基础上达到较高的精确度,适用于高密度快速运动的水下传感器网络。     

基于接收信号强度的WSN概率定位算法

定位对无线传感器网络的应用、操作和管理发挥着至关重要的作用.针对传感器节点的定位,提出了一种基于接收信号强度的概率定位算法.介绍了算法原理及实现过程,讨论了信标节点分布对该算法性能的影响,最后比较了本概率定位算法和最小二乘定位算法在传感器节点定位性能上的优劣.仿真结果表明,信标节点分布对未知节点的定位误差具有较大的影响,本定位算法的性能要优于最小二乘定位算法.     

基于EKF的无线传感器网络移动信标定位算法

针对无线传感器网络节点定位精度较低的问题,提出一种基于扩展卡尔曼滤波的移动信标节点定位算法。该算法采用等距三重优化覆盖思想确定虚拟信标分布,利用蚁群算法获取最优遍历路径,同时引入扩展卡尔曼滤波算法以提高节点定位精度。通过对节点通信半径、虚拟信标数目、路径长度、迭代次数等参数分别进行仿真验证,结果表明本文算法定位精度明显优于普通质心定位算法,同时该算法在提高网络覆盖度、降低网络成本等方面也有较大优势。     

无线传感器网络节点定位算法评判因素

针对无线传感器网络的应用日益广泛,归纳讨论了其应用过程中网络节占、定位算法的相关评判因素：算法的可实施程度、定位精度、节点规模、信标节点密度、节最密度、容错性和自适应性、功耗、代价、安全性等讨论内容体现了无线传感器网络节点定位技术的关键因素。     

DV-Hop节点定位算法研究与改进

在节点随机分布的无线传感器网络中,DV-Hop定位算法存在较大的误差。针对DVHop在智能停车场中定位精度不足的缺点,通过研究信标节点间估计距离和真实距离的误差,提出了改进的算法。改进后的算法修改了网络的平均跳段距离和未知节点坐标的估计范围,并用双曲线法取代了三边定位法,采用Max方法布置信标节点,克服了原算法在智能停车场定位中误差较大的缺点。     

基于DV-Hop的RSSI-Hop算法

在无线传感器网络中,监测到时间之后关心的一个重要问题就是该事件发生的位置。传感器节点能量有限、可靠性差、节点规模大且随机布放、无线模块通信距离有限,对定位算法和定位技术提出了很高的要求。针对随机布放、节点配置低的无线传感器网络,提出一种新的RSSI-Hop定位方法,该方法可以在不增加硬件开销的基础上,有效降低节点能量消耗,较准确地估算未知节点到参考节点之间的距离,减少累积误差,提高定位的准确性。其主要思想是,节点信息根据RSSI强弱,估算各节点到信标节点之间的距离。实验表明,新算法比以前的算法定位更准确。     

无线传感器网络多汇聚节点分簇算法

为解决大规模无线传感器网络的节点通信效率问题,提出无线传感器网络的一种多汇聚节点分簇算法,针对拥有多个汇聚节点的监控区域,对网络进行层次化管理。算法通过对多种参数的综合考虑后产生簇头,并将传感器节点分配到相应的簇,由此可以有效降低节点的非均匀能耗,减少因能耗较大节点的能量过度衰竭而造成网络可用率下降。仿真结果显示,该算法可以延缓首个死亡节点的发生时间,并能有效延长无线传感器网络的整体可用率。     

Doppler auxiliary time synchronization algorithm for underwater acoustic sensor network

Time synchronization problem in underwater acoustic sensor networks (UWSN) was studied.Due to the propagation of acoustic signals in underwater environment and nodes movement bring some problems to time synchronization.A distributed time synchronization algorithm was proposed based on Doppler method,called NU-Sync.NU-Sync solved the problem of uncertainty propagation delay caused by nodes movement through calculating relative velocity.And autonomous underwater vehicle (AUV) was used as beacon node which can save energy consumption in the process of calculation clock skew.Simulation resulted show NU-Sync achieves high level time synchronization precision.     

E2DTS: An energy efficiency distributed time synchronization algorithm for underwater acoustic mobile sensor networks

Time synchronization plays an important role in wireless sensor network applications and energy conservation. In this paper, we focus on the need of time synchronization in underwater acoustic mobile sensor networks (UAMSNs). Several time synchronization algorithms have been carried out in this issue. But most of them are proposed for RF-based wireless sensor networks, which assume that the propagation delay is negligible. In UAMSNs, the assumption about rapid communication is incorrect because the communication is primarily via acoustic channel, so the propagation speed is much slower than RF. Furthermore, the propagation delay in underwater environment is time-varying due to the nodes’ mobility. We present an energy efficiency distributed time synchronization algorithm (called “E²DTS”) for those underwater acoustic node mobility networks. In E²DTS, both clock skew and offset are estimated. We investigate the relationship between time-varying propagation delay and nodes mobility, and then estimate the clock skew. At last skew-corrected nodes send local timestamp to beacon node to estimate its clock offset. Through analysis and simulation, we show that it achieves high level time synchronization precision with minimal energy cost.     

三维水下传感器网络覆盖优化算法

针对三维水下传感器网络模型,对水下传感器网络的覆盖优化问题进行了描述,提出利用虚拟势场算法CAT（coverage-enhancing algorithm for three-dimensional sensor networks）调整水下传感器节点与浮标节点间缆绳的距离,逐渐消除网络中的感知重叠区域和覆盖盲区,进而实现整个水下传感器网络覆盖增强.在仿真实验中,通过CAT算法与ETG算法的比较,验证了CAT算法的有效性.     

信标节点漂移情况下的无线传感器网络节点定位机制

针对信标节点漂移情况下的节点定位问题,提出了一种分布式的信标节点漂移检测方法,采用节点自评分和协商机制,自动寻找可能发生了漂移的信标节点,同时针对大量信标节点发生漂移后的定位覆盖率下降问题,构建普通节点的定位可信度模型,并在定位盲区内使用一些较为可靠的普通节点作为临时信标节点进行定位。仿真实验表明,该算法在误检测、定位误差方面性能优于传统算法,具有较低的通信开销、较高的实用性和灵活性。     

Weighted centroid localization based on compressive sensing

To solve the problem of estimating the locations of sensor nodes in wireless sensor networks where most nodes are without an effective positioning device, a novel range-free localization algorithm—weighted centroid localization based on compressive sensing (WCLCS) is proposed. WCLCS makes use of compressive sensing to get decomposition coefficients between each nonbeacon node and beacon nodes. According to these coefficients, WCLCS algorithm decides the weighted value of each beacon node for Centroid and estimates the locations of nonbeacon nodes. The simulation results show that WCLCS has better localization performance than LSVM.     

基于拨备满足模型的无线传感网节点覆盖算法

针对无线传感网预覆盖过程中存在覆盖盲区以及数据频繁重传而导致的节点覆盖抑制现象,提出了一种基于拨备满足模型的无线传感网网络覆盖算法。设计一种新的无线传感网节点覆盖模型,并构建覆盖指数、覆盖强度、覆盖均衡评估系数等评估维度,快速评估节点覆盖质量。再计算覆盖均衡评估系数,并采用拨备模型优化覆盖质量,确定覆盖性能优越的备用工作节点。随后,基于覆盖相似性原则评估工作节点覆盖性能,设计了节点首次覆盖评估方法,按节点移动路径依次评估覆盖指数统计均值,并根据目标节点进入覆盖区域的先后,逐次激活性能最佳的工作节点进行监测。仿真实验表明：与当前无线传感网常数节点覆盖方案相比,所提方案具有更高的网络覆盖率、更短的覆盖启动时间和更少的工作节点数目。     

网络分层的水下传感器网络覆盖保持路由算法

在以监测为目的的水下传感器网络中,较好的网络覆盖率和连通率是完成监测任务的重要保证.以改善覆盖效果为目标的水下覆盖保持路由算法NCPR算法相对比LEACH-Coverage-U算法有效的延长了网络覆盖时间,但是该算法连通性表现较差,同时存在靠近SINK节点的簇首由于需要转发大量数据而过早死亡的问题.本文提出一种分布式的网络不均匀分层的覆盖保持路由(Network Unevenly Layered Coverage Preserving Routing,NULCPR)算法,由SINK节点开始逐层向下建立网络,同时每层网络节点通信半径也随层号增加而逐渐增大.每层网络独立运行NCPR算法以使该层节点成簇,并通过簇首向上建立连通链路以保证网络连通.仿真结果表明,与NCPR算法相比,NULCPR算法提高了网络连通率以及覆盖率,并且降低了网络能耗,证明了该算法的有效性.     

移动传感器网络非均匀事件区域节点部署优化

针对移动传感器网络中热点事件监测场景,研究传感器节点的快速优化部署策略.首先假定事件随机产生,针对事件优先模型及节点感知误差函数推导基于Voronoi剖分时感知误差最小,然后定义节点有效覆盖权值,证明了当所有节点有效覆盖权值一致时,整个网络覆盖效能将达到最大.结合虚拟力及节点有效覆盖权提出一种分布式优化部署算法SDOA(Sparse Deployment Optimization Algorithm),其在保证覆盖能效最大化时保证网络连通性.最后仿真比较了本文提出部署策略能够快速有效实现对热点区域部署,并保证较高的覆盖效能.     

Coverage‐aware connectivity‐constrained unattended sensor deployment in underwater acoustic sensor networks

Careful deployment of nodes in underwater acoustic sensor networks in a distributed manner with the goal of maximized coverage and guaranteed connectivity is a challenging problem because it is very difficult and costly to access the 3D underwater environment. This paper presents a novel algorithm for self‐deployment of nodes in underwater acoustic sensor networks assuming that the nodes are randomly dropped to the water surface and form a densely populated connected network at the water surface. The idea of the algorithm is based on calculating an optimized depth for each node in the network in such a way that the possible sensing coverage overlaps are minimized and the connectivity of final topology is guaranteed. The algorithm has three main phases. In the first phase, nodes are organized in a tree structure that is rooted at the surface station. In the second phase, the depths for all nodes are computed iteratively at surface station. In the final phase, the calculated depths are distributed to nodes so that the nodes start sinking. The performance of the proposed approach is validated through simulation. We observed that the proposed approach performs at least 10% better in terms of network coverage than contemporary schemes in the literature. Copyright © 2016 John Wiley & Sons, Ltd.     

Random Mobility and Heterogeneity-Aware Hybrid Synchronization for Wireless Sensor Network

Random mobility of a node in wireless sensor networks (WSNs) causes the frequent changes in the network dynamics with increased cost in terms of energy and bandwidth. During data collections and transmission, they need the additional efforts to synchronize and schedule the activities of nodes. A key challenge is to maintain the global clock scale for synchronization of nodes at different levels to minimize the energy consumption and clock skew. It is also difficult to schedule the activities for effective utilization of slots allocated for aggregated data transmission. The paper proposes the Random Mobility and Heterogeneity-aware Hybrid Synchronization Algorithm (MHS) for WSN. The proposed algorithm uses the cluster-tree for efficient synchronization of CH and nodes in the cluster and network, level-by-level. The network consists of three nodes with random mobility and are heterogeneous regarding energy with static sink. All the nodes and CH are synchronized with the notion of the global timescale provided by the sink as a root node. With the random mobility of the node, the network structure frequently changes causing an increase in energy consumption. To mitigate this problem, MHS aggregate data with the notion of a global timescale throughout the network. Also, the hierarchical structure along with pair-wise synchronization reduces the clock skews hence energy consumption. In the second phase of MHS, the aggregated data packets are passed through the scheduled and synchronized slots using TDMA as basic MAC layer protocol to reduce the collision of packets. The results are extended by using the hybrid approach of scheduling and synchronization algorithm on the base protocol. The comparative results show that MHS is energy and bandwidth efficient, with increased throughput and reduced delay as compared with state-of-the-art solutions.