邻近信息约束下的随机异构无线传感器网络节点调度算法

针对高密度部署的随机异构传感器网络内部存在的覆盖冗余问题,该文提出一种随机异构无线传感器网络的节点调度算法(NSSH)。在网络原型拓扑的支撑下构建Delaunary三角剖分,规划出节点进行本地化调度的局部工作子集。通过折中与邻近节点的空外接圆半径,完成对感知半径的独立配置;引入几何线、面概念,利用重叠面积和有效约束圆弧完成对灰、黑色节点的分类识别,使得节点仅依赖本地及邻居信息进行半径调整和冗余休眠。仿真结果表明,NSSH能以低复杂度的代价,近似追平贪婪算法的去冗余性能,并表现出了对网络规模、异构跨度和参数配置的低敏感性。     

无线传感器网络自适应目标跟踪节点调度算法

在无线传感器网络中,设计合理的节点调度算法是提高网络感知能力、降低系统能耗的关键。在分析节点能耗模型的基础上,针对移动目标跟踪型网络应用,提出一种高能效的无线传感器网络自适应节点调度算法ANSTT。该算法根据节点对移动目标的感知能力,以及节点的相对剩余能量水平,自动调整节点工作模式。仿真实验表明,ANSTT算法在维持低感知延时、高目标感知率的同时,可有效降低系统能耗,延长网络寿命。     

非均匀分布下无线传感器网络节点调度机制

针对传统依赖精确位置信息的计算复杂和无位置信息部署受限性等弊端,从理论上对节点部署方式进行分析,提出一种非均匀分布下的无线传感器网络节点调度NDNS(non-uniform distribution node scheduling)机制,该机制利用节点与邻居节点的距离信息,对节点覆盖冗余进行判别,适应于任意分布下的网络部署方式。通过实验对机制进行了性能分析和验证,结果表明该方案在保证网络覆盖的前提下,有效地延长了网络生存时间。     

基于能量预测的无线传感器网络节点覆盖调度算法

针对无线传感器网络中存在的热区问题,采用非均匀部署方案,并在此基础上提出基于能量预测的无线传感器网络节点覆盖调度算法。并对算法进行了仿真实验和性能分析。结果表明该算法可以延长的网络生命周期并在较长的时间里保持较高的网络覆盖率,能够达到网络内大多数节点能耗均衡的设计目标。     

无线传感器网络冗余节点休眠调度算法

提出一种冗余节点休眠调度算法来延长网络生命周期。调度过程中重点考虑两方面问题：一是采取策略防止大量节点同时从工作状态转入休眠状态以防止大量盲区同时产生;二是根据邻居表中节点的工作邻居数量,判定节点是否处于网络边界,对边界节点和内部节点采用不同的调度策略,防止边界收缩。仿真结果表明,算法能有效延长无线传感器网络的生命周期。     

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...     

无线传感器网络节点自身定位算法

无线传感器网络(WSN)的许多应用都是基于节点的位置信息.本文从WSN的基于测距的定位算法和无需测距的定位算法对其定位算法进行详细的说明.并分析比较各定位算法的优缺点.最后还指出了WSN的自身定位问题的研究方向.     

无线传感器网络节点自身定位算法

无线传感器网络（WSN）的许多应用都是基于节点的位置信息．本文从WSN的基于测距的定位算法和无需测距的定位算法对其定位算法进行详细的说明．并分析比较各定位算法的优缺点．最后还指出了WSN的自身定位问题的研究方向。     

无线传感器网络节点定位算法研究

研究无线传感器网络节点定位的方法。首先介绍了节点定位的基本原理,在总结节点定位原理的基础上,对节点定位方法的分类依据进行了归纳。在对无线传感器网络节点定位方法的研究中,主要对是否基于测距的节点定位方法进行具体分析,介绍了2种类型的定位方法的基本原理,并对2种类型的定位方法中的典型算法做了具体说明,最后介绍了定位算法的评价标准。     

面向WIA-PA工业无线传感器网络的确定性调度算法

WIA-PA （Wireless Networks for Industrial Automation-Process Automation）是我国自主制定的工业无线传感器网络标准,确定性调度技术是其中一项关键技术.但目前已有的确定性调度算法主要集中在通用传感器网络或WirelessHART,ISA100.11a等遵循国外标准的工业无线传感器网络中,未能针对WIA-PA网络进行优化设计.鉴于此,本文提出了一种适用于WIA-PA网络的基于回溯法的最优确定性调度算法,能够获取调度解的最大成功率;并以此为基础,进一步提出了一种基于最小时间裕度优先的时分多址调度算法（Least Slack First on Time Division Multiple Access,LSF-TDMA）.仿真实验结果表明,所提出的LSF-TDMA算法能够满足WIA-PA网络端到端数据传输的确定性需求,在调度解获取成功率接近于最优的同时,有效降低了算法复杂度.     

On Performance of Node Placement Approaches for Hierarchical Heterogeneous Sensor Networks

This paper considers a two-tier hierarchical heterogeneous wireless sensor network using the concept of clustering. The network has two type of nodes: regular sensor nodes (litenodes or LN) with limited communications, storage, energy, and computation power; and high-end sophisticated nodes (SNs), or clusterheads, with significantly additional resources. The litenodes communicate their data to the SNs and the SNs forward all collected data to a central gateway node called the base station (BS). Our network architecture allows the LNs to reach a SN via multiple hops through other LNs. We investigate the problem of optimally placing a minimum number of sophisticated nodes to handle the traffic generated by the lite nodes, while ensuring that the SNs form a connected network using their wireless links. This placement problem is formulated and solved as multi-constraint optimization problem using well known approaches: Binary Integer Linear Programming (BILP) approach, Greedy approach (GREEDY) and Genetic Algorithm (GA) approach. It was found through simulations that BILP performed best for regular grid topologies, while GA performed better for random LN deployment. Furthermore, the effects of various parameters on the solution are also presented. The paper also proposes a HYBRID approach that uses the solutions provided by GREEDY and/or BILP as the initial solution to the GA. Using HYBRID, results comparable to original GA could be obtained in only 11.46% of the time required for the original GA. Part of the research was supported by a grant from Air Force Office of Scientific Research (AFOSR) grant No. FA9550-06-1-0103.     

Lightweight Deployment-Aware Scheduling for Wireless Sensor Networks

Wireless sensor networks consist of a large number of tiny sensors that have only limited energy supply. One of the major challenges in constructing such networks is to maintain long network lifetime as well as sufficient sensing areas. To achieve this goal, a broadly-used method is to turn off redundant sensors. In this paper, the problem of estimating redundant sensing areas among neighbouring wireless sensors is analysed. We present simple methods to estimate the degree of redundancy without the knowledge of location or directional information. We also provide tight upper and lower bounds on the probability of complete redundancy and on the average partial redundancy. With random sensor deployment, our analysis shows that partial redundancy is more realistic for real applications, as complete redundancy is expensive, requiring up to 11 neighbouring sensors to provide a 90 percent chance of complete redundancy. Based on the analysis, we propose a scalable Lightweight Deployment-Aware Scheduling (LDAS) algorithm, which turns off redundant sensors without using accurate location information. Simulation study demonstrates that the LDAS algorithm can reduce network energy consumption and provide desired QoS requirement effectively. This research was partially supported by Natural Sciences and Engineering Research Council of Canada. Kui Wu received his Ph.D. in Computing Science from the University of Alberta, Canada, in 2002. He joined the Department of Computer Science at the University of Victoria, Canada in the same year and is currently an Assistant Professor there. His research interests include mobile and wireless networks, network performance evaluation, and network security. Yong Gao received his Master's degree and Ph.D. degree in computer science from University of Alberta, Canada, in 2000 and 2005 respectively. He is currently with the Irving K. Barber School of Arts and Sciences, UBC Okanagan, Canada. His research interests include search algorithms and AI, communication networks, and computational biology. Yang Xiao worked at Micro Linear as an MAC (Medium Access Control) architect involving the IEEE 802.11 standard enhancement work before he joined Department of Computer Science at The University of Memphis in 2002. Dr. Xiao is an IEEE Senior member. He was a voting member of IEEE 802.11 Working Group from 2001 to 2004. He currently serves as Editor-in-Chief for International Journal of Security and Networks (IJSN) and for International Journal of Sensor Networks (IJSNet). He serves as an associate editor or on editorial boards for the following refereed journals: (Wiley) International Journal of Communication Systems, (Wiley) Wireless Communications and Mobile Computing (WCMC), EURASIP Journal on Wireless Communications and Networking, and International Journal of Wireless and Mobile Computing. He serves as five lead/sole guest editor for five journal special issues. He serves as a referee/reviewer for many funding agencies, as well as a panelist for NSF. His research interests are Security/ Reliable Communications, Medium Access Control, Mobility/Location/Paging Managements, Cache Access and Replacement Policies, Quality of Service, Energy Efficiency, and Routing in wireless networks and mobile computing.     

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。     

监测无线传感器网络休眠调度算法

休眠调度设计是无线传感器网络一种重要的通信节能方法。针对监测典型应用,为了实现长时间的监测应用要求,充分利用冗余部署提供的能量资源,提出了一种能量相关的分布式自适应休眠调度算法。算法利用极大独立集构建思想,结合节点层次级别、实时的能量消耗、连通度等信息动态选择连通支配节点集作为网络骨干,使得网络活跃节点数量最小化。仿真试验分析表明,算法能够有效地利用冗余节点提供的能量资源,扩展了网络的生命周期。     

多约束容错性WSN中继节点布局算法的研究

针对目前中继节点布局算法所忽视的中继节点通信容量以及网络整体能耗等问题,本文将通信路径不可逆以及中继节点通信容量等约束条件引入现有中继节点布局模型,并提出了基于最小通信网络距离因子的布局算法评价新标准.解决方法上,采用了基于枚举法与贪婪寻优算法的中继节点布局算法,实现了WSN中继节点的多约束容错性布局.仿真实验表明,本...     

无线传感器网络中非GPS的定位算法

无线传感器网络中节点自定位一直是一个具有挑战性的研究课题。全球定位系统(GPS)是一种传统的定位技术,但是定位的准确性低且网络花费较大。通过分析现有的节点自定位算法,认为六边形节点自定位算法是比较优秀的非GPS算法,该算法基于蜂窝交叠的思想,节点仅使用简单的连接矩阵和信标帧中的定位数据就能自定位,且定位准确性高,最后提出了今后要做的工作。