Area Coverage Optimization in Three-Dimensional Wireless Sensor Network

Wireless Personal Communications - During the development of wireless sensor networks for smart cities, deployment of nodes in three-dimensional space is important factor as data loss in such cases...     

基于容忍覆盖区域的无线传感器网络节点调度算法

节点调度机制是解决无线传感器网络节点能量受限问题的重要方法.传统的位置信息无关的节点调度方案以节点的感知区域覆盖为调度目标,导致处于边界区域的节点由于没有太多机会进入休眠状态而先死亡,进而引起死亡节点向监测中心扩散现象,我们称这种现象为"不均等休眠"问题.针对该问题,从理论上对节点覆盖模型进行分析,提出容忍覆盖区域的概...     

无线传感器网络中移动sink节点的路径规划

在无线传感器网络中,大量感知数据汇集到sink节点的采集方法会导致sink节点附近的节点能量耗尽,造成能量空洞。针对该问题,利用移动的sink节点进行数据收集是一种解决方法,其中移动sink的路径规划成为一个重要的问题。提出了一个移动sink路径规划算法,将无线传感器中随机分布的节点划分为不同的子区域,寻找sink节点移动的最佳转向点,最终得到最优的移动路径,以实现无线传感器网络生命周期最大化。仿真实验表明,与现有方案相比,该算法能显著延长网络的生命周期。     

基于遗传 PSO 的无线传感网络覆盖优化算法研究

针对基于标准粒子群算法的网络覆盖存在收敛速度慢、易早熟等问题,提出一种基于遗传 PSO 的无线传感网络覆盖优化算法.以无线传感器最大覆盖率为目标函数,通过运用加入自适应交叉变异因子的遗传算法搜索解空间,利用 PSO 粒子群强大的全局搜索能力加大搜索范围,使粒子覆盖更有效率,加强算法的寻优能力,提高节点的覆盖率,解决早熟问题.仿真实验表明,与传统遗传算法、新量子遗传算法相比,其覆盖率分别提高了2.28%和0.65%,收敛速度也有所提高,因此该方法能有效地实现无线传感网络覆盖优化.     

无线传感器网络节点机的研制

对无线传感器网络节点进行研究,分析节点的体系结构,设计了节点机的硬件电路.以此为平台,实现各节点间的多跳通信.节点机采用支持IEEE802.15.4的CC2420芯片作为无线通信模块,8位AVR单片机ATmega128L作为处理器,结合外围传感器,对环境进行监测.实验表明:该型节点机具有扩展方便,低功耗,可靠性高的特点.     

多蜜源蜂群算法在无线传感器网络覆盖的优化

基于人工蜂群算法以及无线传感器网络相关技术,提出了一种基于互动策略的多蜜源蜂群算法。该算法采用灵敏度与信息素结合的选择策略代替轮盘赌选择方式以实现跟随蜂的开采过程并引入互动策略实现跟随蜂的邻域搜索。此外,在每次迭代结束时,根据OBL策略产生新蜜源以更新最差蜜源。仿真结果表明,该算法能够使检测区域内传感器节点的分布更加均匀,且通过较少次数的迭代,实现更优的网络覆盖率,这对于延长整个无线传感器网络的生命周期,降低网络的能耗,有着重要的影响。     

基于RSSI的无线传感器网络环境参数分析与修正方案

定位技术是无线传感器网络数据采集的基础服务,而定位精度的高低在很大程度上取决于距离测量的精度。基于RSSI（接收信号强度）测距技术无须添加任何硬件设施、用较少的通信开销和较低的实现复杂度,十分适应于能量受限的无线传感器网络。通过对RSSI测距模型进行分析,并提出一种针对室内环境的参数修正方案。通过自行研发的传感器节点Ubicell上进行验证分析,实验表明,采用环境参数修正方案后,明显提高了测距的精度。     

无线传感器网络路径覆盖问题研究

目标跟踪是无线传感器网络的重要应用之一。在目标跟踪过程中,用户通常更关心目标移动路径的覆盖情况,而不是整个网络部署区域的覆盖情况。学术界对路径1覆盖的问题做了详细的研究,但是并没有给出路径k(k1)覆盖的分析。针对这一问题,该文首先将节点随机布设的2维传感器网络中目标移动路径的覆盖问题转化为1维线段覆盖问题,并通过理论分析给出任意直线路径满足k(k1)覆盖的概率下限。实验表明,在k较小时,该下限可以较好的逼近仿真结果。     

蚁群-遗传算法的无线传感器网络路径优化

为了提高无线传感器网络路径优化效率,快速找到最优路径,提出基于蚁群-遗传算法的传感器路径优化方法.利用遗传算法的快速全局搜索能力和蚁群算法的正反馈机制,实现了两种算法的融合.仿真结果表明,蚁群-遗传算法在时间和性能上都优于单独的蚁群算法和遗传算法,能快速找到无线传感器网络最优路径,有效延长了网络的生命周期.     

无线传感器网络的WPCS覆盖策略

延长无线传感器网络生存时间的有效方法是让冗余节点进入休眠状态。而现有研究多是基于传感器感知模型为圆形的假设前提。该文集中讨论传感器感知模型非圆时,覆盖与连通性之间的联系,并提出适用性更广的WPCS(Well-Proportioned Coverage Strategy)覆盖策略。WPCS覆盖策略以最小化重叠面积为准则,其目的是最大化网络生存时间。仿真实验表明,WPCS性能优于CCP(Coverage Configuration Protocol),且具有一般性,并能很好地减少工作传感器数目,延长网络寿命。     

无线传感器网络节点机的研制

分析了无线传感器网络节点的体系结构,设计了节点机的硬件电路.以此为平台,实现各节点间的多跳通信.节点机采用支持IEEE 802.15.4的CC2420芯片作为无线通信模块,8位AVR单片机ATmega128L作为处理器,结合外围传感器,对环境进行监测.实验表明:该型节点机具有扩展方便、低功耗、可靠性高的特点.     

无线传感器网络微型节点的实现

无线传感器网络微型节点通过自组织的方式构成网络,可远程实时感知和采集处理周边环境中的物质现象.本文设计了以8位AVR单片机ATmega128L为核心,结合外围传感器和2.4GHz无线收发模块CC2420构建的无线传感器网络微型节点.     

Network Coverage in Interference Limited Wireless Sensor Networks

Wireless Personal Communications - The performance of a wireless sensor network is limited by the available bandwidth of the shared wireless channel. For the need to share the available bandwidth...     

The Coverage Problem in a Wireless Sensor Network

One of the fundamental issues in sensor networks is the coverage problem, which reflects how well a sensor network is monitored or tracked by sensors. In this paper, we formulate this problem as a decision problem, whose goal is to determine whether every point in the service area of the sensor network is covered by at least k sensors, where k is a given parameter. The sensing ranges of sensors can be unit disks or non-unit disks. We present polynomial-time algorithms, in terms of the number of sensors, that can be easily translated to distributed protocols. The result is a generalization of some earlier results where only k = 1 is assumed. Applications of the result include determining insufficiently covered areas in a sensor network, enhancing fault-tolerant capability in hostile regions, and conserving energies of redundant sensors in a randomly deployed network. Our solutions can be easily translated to distributed protocols to solve the coverage problem.A preliminary version of this paper has appeared in the Workshop on Wireless Sensor Networks and Applications, 2003, San Diego, CA, USA. Chi-Fu Huang received his B.S. and M.S. degrees both in Computer Science and Information Engineering from the Feng-Chia University and the National Central University in 1999 and 2001, respectively. He obtained his Ph.D. in the Department of Computer Science and Information Engineering from the National Chiao-Tung University in September of 2004. He is currently a Research Assistant Professor at the Department of Computer Science and Information Engineering, National Chiao-Tung University, Taiwan. His research interests include wireless communication and mobile computing, especially in ad hoc and sensor networks. Yu-Chee Tseng received his B.S. and M.S. degrees in Computer Science from the National Taiwan University and the National Tsing-Hua University in 1985 and 1987, respectively. He worked for the D-LINK Inc. as an engineer in 1990. He obtained his Ph.D. in Computer and Information Science from the Ohio State University in January of 1994. He was an Associate Professor at the Chung-Hua University (1994–1996) and at the National Central University (1996–1999), and a Full Professor at the National Central University (1999–2000). Since 2000, he has been a Full Professor at the Department of Computer Science and Information Engineering, National Chiao-Tung University, Taiwan. Dr. Tseng served as a Program Chair in the Wireless Networks and Mobile Computing Workshop, 2000 and 2001, as a Vice Program Chair in the Int’l Conf. on Distributed Computing Systems (ICDCS), 2004, as a Vice Program Chair in the IEEE Int’l Conf. on Mobile Ad-hoc and Sensor Systems (MASS), 2004, as an Associate Editor for The Computer Journal, as a Guest Editor for ACM Wireless Networks special issue on “Advances in Mobile and Wireless Systems”, as a Guest Editor for IEEE Transactions on Computers special on “Wireless Internet”, as a Guest Editor for Journal of Internet Technology special issue on “Wireless Internet: Applications and Systems”, as a Guest Editor for Wireless Communications and Mobile Computing special issue on “Research in Ad Hoc Networking, Smart Sensing, and Pervasive Computing”, as an Editor for Journal of Information Science and Engineering, as a Guest Editor for Telecommunication Systems special issue on “Wireless Sensor Networks”, and as a Guest Editor for Journal of Information Science and Engineering special issue on “Mobile Computing”. He is a two-time recipient of the Outstanding Research Award, National Science Council, ROC, in 2001–2002 and 2003–2005, and a recipient of the Best Paper Award in Int’l Conf. on Parallel Processing, 2003. Several of his papers have been chosen as Selected/Distinguished Papers in international conferences. He has guided students to participate in several national programming contests and received several awards. His research interests include mobile computing, wireless communication, network security, and parallel and distributed computing. Dr. Tseng is a member of ACM and a Senior Member of IEEE.This revised version was published online in August 2005 with a corrected cover date.     

基于 RSSI 的无线传感器网络节点定位算法研究

节点位置信息是无线传感器网络应用的基础。基于RSSI（Receive Signal Strength Indicator）的测距技术因其低成本和低复杂度的优点而被广泛用于无线传感器网络的定位技术中。介绍了RSSI信号传输模型,在介绍无线传感器网络定位基本原理的基础上,分析了影响定位精度的因素。综述了近几年提出的无线传感器网络中基于RSSI的节点定位算法及其改进算法,现有基于RSSI定位算法的改进算法主要从测距精度改进、定位精度改进或误差修正改进等方面进行。最后,指出了基于RSSI的无线传感器网络节点定位算法的不足,并进行展望。     

一种改进的无线传感器网络节点定位技术

无线传感器网络节点自身定位至关重要,在军事和民用领域中有着广泛的应用前景。文中针对传统的网络定位算法。提出的改进算法实验结果表明,算法能够有效地对节点进行定位、减少了误差率。     

IPv6无线传感器网络节点的设计研究

提出了一种IPv6无线传感器网络节点的设计,此系统符合无线传感器网络节点设计原则。硬件系统设计硬件系统充分利用了芯片Atmega128、CC2420和LM60的功能,软件设计通过引入状态机进行系统模式调度,从而实现了系统的独立运行。为了测试系统的正确性,对传感器节点的数据包接收率、平均延迟时间和平均消耗能量进行了测试,测试结果表明,此设计方法安全可行,具有很好的实用性。     

无线传感网死亡节点优化避绕方法研究与仿真

无线传感网络的节点部署随机性很强,每个节点的利用率不同,经常用到的节点可能会能量耗尽死亡,传统的网络协议将传感网络随机分为不同的簇,簇头能量很微弱的节点可能仍被选为簇头,造成了节点死亡,其没有避绕死亡节点的机制,造成通讯稿效率不高.为此提出微粒群优化LEACH的无线传感网络通信优化方法,结合LEACH的优点,簇头选择时使用微粒群的高度智能优化的特点将簇头当前能量与原始能量作为选择因素构造目标函数.通过适应度值避让节点中的死亡节点.实验仿真结果证明,簇头微粒群优化后传感网络能量损耗大大降低,死亡节点通信数目也变小.提高了通讯效率.     

A Malicious Node Identification Strategy with Environmental Parameters Optimization in Wireless Sensor Network

Wireless Personal Communications - In the wireless sensor network (WSN), nodes show a low forwarding rate under a poor-quality links environment and a resource-constrained state. The malicious...     

无线传感器网络节点定位机制研究

传感器网络中的节点定位问题与很多实际应用直接相关,主要有两类算法,即 rang-free和rang-based,这两类定位算法各有其优势和不足.为了研究算法的发展趋势,比较了几种典型的定位算法,指出了各自的优缺点.