无线传感器网络中一种基于虚拟MIMO多播的多跳传输策略

虚拟MIMO技术能够有效减少信道衰落对无线链路的影响,节省无线传输时的能耗.结合MIMO多播和LEACH协议,提出新的虚拟MIMO多跳传输策略(VMMM),由于该策略避免了多跳数据转发时的簇内广播过程,从而提高整个网络的能量有效性.为优化该传输策略的性能,本文对VMMM策略的能耗进行建模分析,并在此基础上通过联合优化以确定满足最小能耗时的网络参数.仿真结果表明,与已有的虚拟MIMO多跳传输策略—vMISO协议相比,VMMM策略能够显著提高网络的能量有效性,有效延长网络生存时间达50%以上.     

虚拟MIMO无线传感器网络的传输模式

无线传感器网络(wirelesssensor networks,WSN)是由大量低成本、低功耗、具备感知能力、计算能力和无线通信能力的微型传感器节点通过自组织方式构成的网络。多入多出(Multiple-Input Multiple-Output,MIMO)技术是指在发送端和接收端采用多天线,MIMO技术可在不增加频谱资源和天线发送功率的情况下,成倍地提高信道容量,是新一代移动通信系统采用的关键技术。将虚拟MIMO技术引入无线传感器网络,可以利用MIMO技术带来的分集增益,增加接收端信号的信号强度,通过分集来克服信道衰落的影响;也可以利用MIMO技术提供的复用增益,提高信息速率,大大改善网络的能耗特性。本文介绍了虚拟MIMO技术在无线传感器网络中的应用,针对中小规模传感器网络,设计了一种基于分簇的能量高效协作式虚拟MIMO传输模式。并对虚拟MIMO无线传感器网络的能效性进行了分析,最后总结了研究的关键问题以及未来的发展趋势和研究方向。     

无线传感器网络中一种基于分簇的能量高效虚拟MIMO传输策略

协作式MIMO技术被认为是传感器网络中有效的节能解决方案之一.针对中小规模传感器网络设计了一种基于分簇的能量高效的协作式虚拟MIMO传输策略(ECCM).在考虑了分布式STBC编码信道训练开销的情况下,分析了该传输策略的系统总体能耗.基于该能耗模型,建立了一种基于端到端的全网能耗最优化模型,并用该模型来求解最优的虚拟MIMO域(分簇)个数、协作节点(虚拟天线)个数以及传输速率等网络通信参数.仿真结果表明,通过选取最优协议参数,即使考虑到电路能耗和信道训练开销,ECCM策略也能显著降低节点传输能耗,延长网络寿命.     

无线传感器网络虚MIMO技术研究

在无线传感器网络(WSNs)中,由于节点资源受限,一般不具备多天线,为了充分利用多人多出(MIMO)技术的优点,组成虚MIMO结构成为现实可行的技术.分析了MIMO技术特点,在给出的虚MI-MO结构的基础上,提出了WSNs虚MIMO技术要解决的主要问题,并给出了解决方案.     

虚拟MIMO传感器网络中一种联合网络效用和生存时间优化的分布式算法

虚拟(协作式)MIMO技术被认为是传感器网络中有效的节能解决方案之一,然而,现有虚拟MIMO传输策略的设计大多只关注如何有效降低网络能耗,而很少关注反映网络性能的其他指标,例如网络效用(Network Utility),该指标反映了网络数据采集和传输量的多少.为了联合优化网络效用和网络生存时间这两个网络性能参数.本文首先分析虚拟MIMO传输能耗特点,然后基于网络效用最大化(Network Utility Maximization)思想对虚拟MIMO传感器网络进行联合网络生存时间和网络效用的优化建模.在该模型的求解过程中,通过使用对偶分解技术将原需要集中计算的优化问题分解为可以在不同节点上进行计算的子优化问题,并得出一种联合优化网络效用和生存时间的分布式优化算法.该算法的仿真结果显示,网络中的虚拟MIMO节点仅需要交互邻居节点信息,通过有限次的迭代计算,就能收敛到全局最优的发送速率以及功率值.从而使系统总的效用和网络生存时间之间能够达到帕累托(Pareto)最优平衡.     

基于无线传感网的虚拟MIMO的能量有效性研究

基于一种无线传感网模型,提出了一种新的虚拟MIMO结构,此结构不需要接收端协同,避免了以往虚拟MIMO结构中接收端协同的复杂性。文章从整个网络生存周期角度出发,分析并推导了在相同条件下虚拟MIMO相比SISO会有更小的能耗,此外,还考虑了基于导频序列信道估计对能耗的影响,仿真结果表明了协同虚拟MIMO比SISO情况下能量节省很多。     

无线传感器网络中基于网络层的能源有效性研究

如何有效地使用有限的能源是无线传感器网络的一个核心问题。以环境监测为背景,基于网络层建立了无线传感器网络生命期的模型,并时其进行分析,指出能源有效路由算法和数据融合是网络层节省能源的重要因素。最后给出了一种基于网络层的能源有效性解决方案,达到延长网络生命期的目的。     

基于虚拟力的无线传感器网络地理位置路由算法*

通过引入虚拟力导向的节点移动方式改进了GAF路由算法,提出了一种新的基于虚拟力的无线传感器网络地理位置路由算法。算法通过计算节点之间以及节点与边界之间的虚拟力,引导移动节点移动到新位置;同时,利用计算得到的节点移动前后的位置信息改进了节点休眠机制,能够在节点移动后适时地唤醒其他节点。仿真实验结果表明,该算法能有效提高网络覆盖率、平衡节点能量消耗,并显著延长网络生命时间。     

无线传感器网络中基于网络层的能源有效性研究*

如何有效地使用有限的能源是无线传感器网络的一个核心问题。以环境监测为背景,基于网络层建立了无线传感器网络生命期的模型,并对其进行分析,指出能源有效路由算法和数据融合是网络层节省能源的重要因素。最后给出了一种基于网络层的能源有效性解决方案,达到延长网络生命期的目的。     

基于无线传感器网络虚拟MIMO系统盲均衡

无线传感器网络（ Wireless Sensor Network,WSN）是近年来人们研究的热点。针对无线传感器网络高密度分布的特点,在无线传感器网络进行分簇处理的基础上,文中构造了一种新的虚拟MIMO系统模型,并且针对传统的盲均衡算法进行改进,提出一种新的适用于无线传感网的TXK_Z盲均衡算法,最后对该虚拟MIMO系统利用文中提出的TXK_Z算法进行盲均衡的仿真实验。实验表明,跟传统的盲均衡算法相比,在低信噪比、短数据的环境下,改进后算法的误码率明显降低,性能显著提高。     

基于一种虚拟骨干网环境下的移动能量补充策略

在无线传感器网络中,骨干网可方便地实现数据聚合,有利于达到能量高效的数据收集,但是其面临着骨干节点能量消耗过快,易出现因节点能量耗尽而导致骨干网连接中断的问题.为了保证网络能够持续高效的运行,一种基于虚拟骨干网的移动能量补充策略VBMERS(Mobile Energy Replenishment Strategy with Virtual Backbone)被提出来解决网络中骨干节点的能耗过快问题,同时也兼顾对非骨干节点的能量补充.VBMERS策略根据待充电传感器节点当前的通信量计算其优先级,始终选择优先级最大的节点作为充电候选节点以尽量给负载大的节点优先充电,从而避免节点快速进入能量饥饿状态.仿真结果显示,VBMERS策略能有效的解决节点的能量饥饿问题,降低了节点的失效率,进而延长了传感器网络的生存周期.     

基于簇的无线传感器网络能量平衡策略

分簇被认为是延长无线传感器网络寿命的最有效的方法之一。本文首先说明根据节点数目以及分布区域特征,确定合理的成簇数目是分簇算法设计的核心;算法EBCO（Energy Balance Cluster Optimize）按照无线传感器网络运行过程中相邻簇簇头能量消耗速度信息来调整簇的大小,并且从能耗大的簇＂驱逐＂一些节点到能耗低的簇,从而平衡簇头之间的能量消耗。仿真结果表明,采用该能量平衡的传输策略时,能有效地平衡簇头间的能量消耗,较好地解决＂热区＂问题,延长网络生存时间。     

Radio-Triggered Wake-Up for Wireless Sensor Networks

Power management is an important technique to prolong the lifespan of sensor networks. Many power management protocols employ wake-up/sleep schedules, which are often complicated and inefficient. We present power management schemes that eliminate such wake-up periods unless the node indeed needs to wake up. This type of wake-up capability is enabled by a new radio-triggered hardware component inspired by the observation that the wake-up radio signal contains enough energy to trigger a wake-up process. We evaluate the potential power saving in terms of the lifespan of a sensor network application, using experimental data and SPICE circuit simulations. Comparing the result with always-on and rotation-based power management schemes, we find the radio-triggered scheme saves 98% of the energy used in the always-on scheme, and saves over 70% of the energy used in the rotation-based scheme. Consequently, the lifespan increases from 3.3 days (always-on) or 49.5 days (rotation-based) to 178 days (radio-triggered). Furthermore, a store-energy technique can extend operating distance from 10 feet to 22 feet, or even longer if longer latency is acceptable. Wake-up efficiency is evaluated in NS-2 simulations, which show that radio-triggered wake-up has fewer failures, shorter latency, and consistently larger sensing laxity than rotation based wake-up. We also present amplification and radio-triggered IDs which can further enhance performance.Lin Gu is a Ph.D. student at University of Virginia. His current research area is in wireless sensor networks, focusing on OS kernel services and energy efficient hardware and architecture support. Before joining to UVa, he got M.S. degree from Peking University and B.S. in Computer Science from Fudan University.John A. Stankovic is the BP America Professor in the Computer Science Department at the University of Virginia. He recently served as Chair of the department, completing two terms. He is a Fellow of both the IEEE and the ACM. He also won the IEEE Real-Time Systems Technical Committees Award for Outstanding Technical Contributions and Leadership. Professor Stankovic also serves on the Board of Directors of the Computer Research Association. Before joining the University of Virginia, Professor Stankovic taught at the University of Massachusetts where he won an outstanding scholar award. He has also held visiting positions in the Computer Science Departmentat Carnegie-Mellon University, at INRIA in France, and Scuola Superiore S. Anna in Pisa, Italy. He was the Editor-in-Chief for the IEEE Transactions on Distributed and Parallel Systems and is a co-editor-in-chief for the Real-Time Systems Journal. His research interests are in distributed computing, real-time systems, operating systems, and wireless sensor networks. Prof. Stankovic received his Ph.D. from Brown University.     

基于虚拟力的异构无线传感器网络覆盖优化策略

针对异构无线传感器网络覆盖优化过程中,固定Sink节点的虚拟作用力限制移动节点的位置移动,导致覆盖盲区得不到全局修复的问题,本文结合计算几何理论,提出基于Voronoi多边形形心引力的虚拟力覆盖优化算法（CAVFA）。虚拟力算法能有效指导移动节点的散布过程,形心引力能更好地实现全局的覆盖优化。通过合理设置虚拟力的距离阈值参数和优先级,调整固定节点对移动节点的约束。仿真表明,相比传统VFA算法和CBA算法,本文提出的CAVFA算法能够更有效地提高异构网络的覆盖率,且算法收敛速度更快。     

无线传感器网络安全认证方案综述

安全认证是无线传感器网络中关键安全技术之一,如何确保无线传感器网络中通信双方身份的真实性是无线传感器网络的一个研究重点.论文从基于对称密码体制、非对称密码体制的认证方案、分布式认证方案、单向散列函数的认证方案、零知识证明的认证方案等方面出发,对典型的无线传感器网络认证方案进行了总结归纳,并指出了每类方案优点与不足,最后对无线传感器网络中安全认证方案的研究热点进行了展望.     

Metaheuristic Secure Clustering Scheme for Energy Harvesting Wireless Sensor Networks

Recently, energy harvesting wireless sensor networks (EHWSN) have increased significant attention among research communities. By harvesting energy from the neighboring environment, the sensors in EHWSN resolve the energy constraint problem and offers lengthened network lifetime. Clustering is one of the proficient ways for accomplishing even improved lifetime in EHWSN. The clustering process intends to appropriately elect the cluster heads (CHs) and construct clusters. Though several models are available in the literature, it is still needed to accomplish energy efficiency and security in EHWSN. In this view, this study develops a novel Chaotic Rider Optimization Based Clustering Protocol for Secure Energy Harvesting Wireless Sensor Networks (CROC-SEHWSN) model. The presented CROC-SEHWSN model aims to accomplish energy efficiency by clustering the node in EHWSN. The CROC-SEHWSN model is based on the integration of chaotic concepts with traditional rider optimization (RO) algorithm. Besides, the CROC-SEHWSN model derives a fitness function (FF) involving seven distinct parameters connected to WSN. To accomplish security, trust factor and link quality metrics are considered in the FF. The design of RO algorithm for secure clustering process shows the novelty of the work. In order to demonstrate the enhanced performance of the CROC-SEHWSN approach, a wide range of simulations are carried out and the outcomes are inspected in distinct aspects. The experimental outcome demonstrated the superior performance of the CROC-SEHWSN technique on the recent approaches with maximum network lifetime of 387.40 and 393.30 s under two scenarios.