无线传感器网络节点多目标安全优化部署

目前,随着社会经济的快速发展,无线传感器网络节点运行中,优化部署方案中,对网络节点位置移动引起节点间共享密钥破坏安全通信链路等问题考虑的不够周全。此种情况下,本文主要论述了无线传感器网络节点多目标安全优化部署相关问题。     

基于蚁群算法的传感器网络节点部署设计

传感器网络节点的人工部署是一类重要的应用方式,为了解决传感器网络节点部署位置的优化问题,提出了基于蚁群算法的传感器网络节点部署设计算法Easidesign.针对蚁群算法在解决传感器节点部署的扩展性问题,提出了贪婪策略、额外信息素蒸发机制等改进方法.Easidesign算法最大特点是充分考虑到当sink节点处于不同位置时对传感器节点部署设计的影响,并且能保证每个部署的节点与sink的连通性,因此Easidesign具有很大的实用价值.通过大量仿真与实验,不仅证明了算法的有效性,而且给出了如何设计算法中的关键参数等问题.     

多跳无线传感器网络的高效中继节点快速选择算法

针对多跳无线传感器网络数据收集协议中继转发节点选择算法效率不高的问题,提出了一种能量有效的中继节点快速选择 (EERNFS)算法.EERNFS算法利用分时共享信道的方法维护网络同步和更新节点的邻居信息,使节点在每个网络侦听/睡眠周期依赖一定的概率同步激活唤醒,确保了网络节点瞬时连通度的稳定和一致;基于网络节点的地理优先级、节点价值和链路质量的分布式估计,EERNFS算法采用竞争的方法选择中继转发节点, 使用乘性增加时间窗口的方法,分解候选中继节点间的竞争.理论分析和模拟实验结果表明,EERNFS算法在能效、数据传递的平均时延、分组到达率等网络性能指标上显著优于FFS和GeRaF算法,极大地延长了网络的寿命.     

无线传感器网络的中继节点自适应选择休眠机制

针对无线传感器网络节点能量有限的问题,设计一种中继节点自适应休眠方法,对网络节点的工作时间进行优化调度。在路由链路建立中,根据网络中节点的地理位置、剩余能量选择中继节点的方法进行节点休眠调度。网络工作时通过计算下一跳最佳节点位置,选取其附近区域内剩余能量多的节点作为下一跳的转发节点,设计出中继节点自适应选择的节点休眠机制。仿真结果表明,所设计的休眠机制提高了节点能量利用效率、延长了网络工作时间。     

无线传感器网络移动汇聚节点的研究

提出了移动汇聚节点的方法，解决了稀疏WSN网络的组网问题以及瓶颈节点的负载均衡问题．通过OPNET网络仿真，结果表明：采用移动sink节点的方法可以使网络中的各节点的负载趋于平衡，网络的吞吐量大大提高．     

自适应多传感器网络覆盖节点部署技术研究

基于多传感器节点圆形数据采集区域相切形成一系列相似三角形在几何原理上的有效性和可行性,提出了一种基于相似三角形的网络节点协同控制节点部署技术.首先把数据采集区域分割为多个几何相似的三角形,保证对监测区域无缝覆盖的同时聚集最少的传感器节点;其次在簇首节点与分簇区域内的传感器节点之间构建高效拓扑;然后建立一种自适应节点失效重建网络拓扑控制机制.仿真实验表明,该节点部署算法可以对监测区域实现完全无缝覆盖,保持网络整体性能高效以及数据传输的可靠性..     

WiMax Mesh网络中基于最少簇的中继部署算法研究

在多跳中继的WiMax Mesh网络中,当发送功率和信道带宽为定值时,用户接入链路的速率取决于用户到中继的距离,对于接入层中继位置的设计可以提高整个网络的吞吐量和进行无视距通信(Non Line Of Sight,NLOS)具有重要的意义.本文将该问题转化为空间最少簇的问题,算法首先根据用户位置的信息来划分出每个单个簇,然后在每个单个簇中生成符合的覆盖圆,寻找覆盖圆的圆心,得出中继的位置.模拟实验结果表明,与该问题已有算法MIS相比本文算法部署的中继的个数减少了51％,与算法HS相比减少了23％.通过使用较少的中继,本文算法较好地保证了网络的性能、提高了网络用户吞吐量.     

基于MOEA/P的无线传感器网络节点部署研究

在无线传感器网络节点部署中,提高网络覆盖性、连通性,降低网络成本,满足过度覆盖约束等是优化无线传感器网络的多个目标,提高无线传感器网络的服务质量的问题成为一个多目标优化问题。研究围绕在二维的平面区域进行传感器节点的部署。在保证连通性的基础上,采用基于投影面的MOEA/P算法实现最大化覆盖区域,最小化节点部署成本。实验结果表明,采用MOEA/P算法进行节点部署优化比采用MOEA/D算法在IGD指标上降低了18.5%。     

基于图论的光传感器节点部署优化研究

图论在合理部署光传感器节点领域取得一定成果,优化部署光传感器节点是延长传感网络使用寿命的有效途径,为此,对光传感器节点进行部署优化。基于图论构建光传感器网络节点模型,将光传感器网络划分成多个网格,每个网格配置一个活动节点、多个冗余节点,计算光传感器节点负载情况;考虑节点负载量,基于萤火虫算法(GSO)部署光传感器节点,将传感器节点等同于萤火虫,覆盖信号强度为荧光素浓度,计算网格内光传感器节点移动概率、判断节点移动方向,实现光传感器节点的优化部署。光传感器仿真部署结果如下:该方法部署的光传感器节点覆盖率广、节点移动距离和较短,有效延长光传感器网络寿命。     

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。     

无线传感器网络节点的自身定位

无线传感器网络的自身节点的定位对网络来说是非常重要的，传感器节点是随机分布在网络中的，这关系到网络最终的定位精度；节点自身定位的方法从节点的个数主要有单点定位和两个节点的定位，这里提出另一种定位方法，运用三个节点实现传感器网络的节点定位。     

利用移动内点来修复传感器网络空洞的算法

针对目标区域中存在感知空洞问题,提出了一种空洞修复准则。在此基础上,设计了基于移动节点无需地理信息的修复算法SOI,该算法通过计算空洞边缘可移动的最佳内点,使该边缘节点到达新的位置,实现减少目标区域中空洞面积的目的。分析与仿真实验表明,与VHR算法相比,SOI算法在部署密集的传感网络中需要移动的总距离更少。     

Analyzing the redeployment problem of mobile wireless sensor networks via geographic models

Since sensor networks integrate virtual and physical worlds, spatial deployment of sensor nodes may have a significant impact on operation costs and performance. This paper investigates the problem of redeploying mobile sensor networks, in which the objective is to design an efficient algorithm which optimizes the global performance of networks. We take a novel approach in analyzing the problem from a macroscopic perspective, modeling the sensor deployment as a density distribution and the redeployment algorithm as an integral transform of that distribution. Despite lacking the details for individual node, we may still derive insightful results, such as number of moves, stability, and transitional behavior. We also derive the bound of total moving distance difference between an arbitrary one‐move algorithm and the optimum redeployment algorithm, allowing for the estimation of the minimum moving distance from the initial deployment region. In summary, we present an theoretical analysis of the redeployment problem from a macroscopic perspective, and believe the results can serve as a basis for further algorithm development and analysis. Copyright © 2011 John Wiley & Sons, Ltd.     

基于簇结构超宽带无线传感器网络的传输功率优化选择算法

在簇结构超宽带无线传感器网络中,为了在可接受的实现成本范围内解决节能与功率控制问题,提出了一种传输功率优化选择算法,同时满足了预设的数据传输速度和最大限度的节能要求.然后详细地分析了该算法实现的可行性、复杂度和实现成本.仿真结果表明,本算法得出的最优传输功率大大小于传感器节点可获取的最大功率,并可以根据网络背景噪声和最大传输速度的变化而动态调整;该算法可以较为显著地延长传感器节点寿命;另外,仿真结果还表明本算法的实现成本是合理的且可接受的.     

无线传感器网络SL-n迭代定位算法

无线传感器网络迭代多边定位算法在迭代定位过程中使用全局最小均方估计(MMSE)方法估计盲节点的位置,导致算法定位误差很大,缺乏稳健性。针对此问题,提出了SL-n估计方法,该方法首先把某盲节点的所有参考节点进行分组,通过三边法或局部MMSE方法求出的每组相应样本值,并用这些样本值估计出此盲节点的位置。仿真实验表明,当部分参考节点的参考误差较大时,该方法优于全局MMSE处理方法,可以有效降低定位误差。     

Optimal placement and routing strategies for resilient two‐tiered sensor networks

In hierarchical sensor networks using relay nodes, sensor nodes are arranged in clusters and higher powered relay nodes can be used as cluster heads. The lifetime of such a network is determined primarily by the lifetime of the relay nodes. In this paper, we propose two new integer linear programs (ILPs) formulations for optimal data gathering, which maximize the lifetime of the upper tier relay node network. Unlike most previous approaches considered in the literature, our formulations can generate optimal solutions under the non‐flow‐splitting model. Experimental results demonstrate that our approach can significantly extend network lifetime, compared to traditional routing schemes, for the non‐flow‐splitting model. The lifetime can be further enhanced by periodic updates of the routing strategy based on the residual energy at each relay node. The proposed rescheduling scheme can be used to handle single or multiple relay node failures. We have also presented a very simple and straightforward algorithm for the placement of relay nodes. The placement algorithm guarantees that all the sensor nodes can communicate with at least one relay node and that the relay node network is at least 2‐connected. This means that failure of a single relay node will not disconnect the network, and data may be routed around the failed node. The worst case performance of the placement algorithm is bounded by a constant with respect to any optimum placement algorithm. Copyright © 2008 John Wiley & Sons, Ltd.     

Optimal power‐aware relay placement for cooperative wireless sensor networks

We study the problem of optimizing the symbol error probability (SEP) performance of cluster‐based cooperative wireless sensor networks. Recent studies in literature show that an efficient relay selection protocol based on simple geographical information of the nodes to execute cooperative diversity can significantly improve the SEP performance at the destination of such networks. As well, similar line of research on optimal power allocation (for the source and relay nodes) can be found in literature. However, to achieve the best SEP performance at the destination of a cooperative wireless sensor network, joint optimization of power allocation and relay placement should be accomplished. To this aim, we reformulate the SEP of a multi‐hop cooperative communication in a general form and optimize transmitted power level and relay placement simultaneously. This analysis is developed for both amplify‐and‐forward and decode‐and‐forward relaying protocols. Simulation results demonstrate that the proposed joint optimization can effectively improve the SEP performance of the network. Copyright © 2013 John Wiley & Sons, Ltd.     

改进遗传算法优化无线传感器网络路由算法

为了有效延长无线传感器网络的生存时间,针对传感器节点能耗不均衡难题,提出一种改进遗传算法优化的无线传感器网络路由算法。首先对LEACH算法不足进行分析,然后构建簇头节点选择的目标函数,并将其作为遗传算法的搜索目标,最后通过遗传算法找到下一时刻簇头的候选节点,并针对遗传算法不足进行相应改进。采用仿真实验对算法的性能进行分析,结果表明,相对于其它无线传感器路由算法,本文算法可以保证无线传感器的节点能量均衡,延长了网络的生存时间。     

On-demand diversity wireless relay networks

There has been much recent attention on using wireless relay networks to forward data from mobile nodes to a base station. This network architecture is motivated by performance improvements obtained by leveraging the highest quality links to a base station for data transfer. With the advent of agile radios it is possible to improve the performance of relay networks through intelligent frequency assignments. First, it is beneficial if the links of the relay network are orthogonal with respect to each other so that simultaneous transmission on all links is possible. Second, diversity can be added to hops in the relay network to reduce error rates. In this paper we present algorithms for forming such relay networks dynamically. The formation algorithms support intelligent frequency assignments and diversity setup. Our results show that algorithms that order the sequence in which nodes join a relay network carefully, achieve the highest amount of diversity and hence best performance. This research is supported in part by NSF grant CNS-0508114. JaeSheung Shin received the B.S. and M.S. degree in Computer Science and Engineering from DongGuk University, Korea, in 1991 and 1993, respectively. He is currently working toward the Ph.D. degree in Computer Science and Engineering at the Pennsylvania State University, University Park. He is a research assistant at the Networking and Security Research Center (NSRC). Prior to joining Pennsylvania State University, he was with Electronics and Telecommunications Research Institute (ETRI), Korea, since 1993. He worked on development of 2G and 3G wireless cellular core network elements. His research interests include mobility management and signaling for wireless cellular and routing and resource allocation for multi-radio multi-hop wireless cellular networks. Kyounghwan Lee received the B.S. degree in Electrical and Electronics Engineering from University of Seoul, Seoul, Korea, in 2000, and the M.S. degree in Information and Communication Engineering from Gwangju Institute of Science and Technology, Gwangju, Korea, in 2002. He is currently a Ph.D candidate at the Electrical Engineering department at the Pennsylvania State University and a research assistant at the Wireless Communications and Networking Laboratory (WCAN@PSU). His research interests include wireless communication theory and relay networks. E-mail: kxl251@psu.edu Aylin Yener received the B.S. degrees in Electrical and Electronics Engineering, and in Physics, from Bogazici University, Istanbul, Turkey, in 1991, and the M.S. and Ph.D. degrees in Electrical and Computer Engineering from Rutgers University, NJ, in 1994 and 2000, respectively. During her Ph.D. studies, she was with Wireless Information Network Laboratory (WINLAB) in the Department of Electrical and Computer Engineering at Rutgers University, NJ. Between fall 2000 and fall 2001, she was with the Electrical Engineering and Computer Science Department at Lehigh University, PA, where she was a P.C. Rossin assistant professor. Currently, she is with the Electrical Engineering department at the Pennsylvania State University, University Park, PA, as an assistant professor. Dr. Yener is a recipient of the NSF CAREER award in 2003. She is an associate editor of the IEEE Transactions on Wireless Communications. Dr. Yener’s research interests include performance enhancement of multiuser systems, wireless communication theory and wireless networking. Thomas F. La Porta received his B.S.E.E. and M.S.E.E. degrees from The Cooper Union, New York, NY, and his Ph.D. degree in Electrical Engineering from Columbia University, New York, NY. He joined the Computer Science and Engineering Department at Penn State in 2002 as a Full Professor. He is the Director of the Networking Research Center at Penn State. Prior to joining Penn State, Dr. La Porta was with Bell Laboratories since 1986. He was the Director of the Mobile Networking Research Department in Bell Laboratories, Lucent Technologies. He is an IEEE Fellow and Bell Labs Fellow. Dr. La Porta was the founding Editor-in-Chief of the IEEE Transactions on Mobile Computing. He has published over 50 technical papers and holds 25 patents.     

能量收集多跳D2D无线传感网络中的中继选择算法

针对无线功率传输技术的能量收集效率有限造成信噪比下降进而引发通信中断率增加的问题,在能量收集多跳D2D(Device to Device)无线传感网络中,提出一种基于改进K-means聚类的中继选择方法。首先,推导得到能量收集下的信噪比因子,使其作为K-means聚类特征。然后,利用最小欧氏距离原则得到距离聚类中心最近的实际节点的位置。最后,根据距离重排序得到中继节点,形成从源节点到目的节点的通信链路。仿真实验结果表明,相比最短路径算法和随机中继协作方案,所提出的改进算法链路信噪比更大,能够减小通信中断率,具有更好的中继性能。