无线传感器网络数据融合技术研究与应用

数据融合技术是无线传感器网络(WSN)的关键技术,其目的是减少网络通信量,降低网络能耗,提高数据精确度,优化WSN整体性能。文章将WSN数据融合与传统多传感器数据融合进行比较,介绍了WSN数据融合的技术特点,重点分析了其融合模型,并对每种融合模型的能量消耗进行分析和比较,最后介绍了该技术在军事及环境领域的应用。     

无线传感器网络基于分簇路由的数据融合研究

无线传感器网络节点资源有限,所以需要采用有效的路由算法与数据融合机制来节省资源,延长网络寿命,提升数据采集效率。LEACH是经典分簇路由协议,针对其在簇头选择机制、数据融合以及簇头与基站通信的路由方面的不足,提出了几点改进方法,在簇头选择的算法中加入了能量控制条件,簇头与基站的路由改为更适合数据融合的多跳反向组播树,并基于信息熵提出了有效数据融合机制。仿真实验表明,改进之后的算法比原LEACH算法更有效地利用了节点资源,延长了网络生存时间。     

无线传感器网络中有效的安全数据融合机制

在无线传感器网络中,数据融合是实现有效传输和节省能源的一个重要途径,许多应用都需要可靠并且可信的数据来进行融合.针对上述要求,提出了一个新的安全数据融合算法来保证融合数据的机密性和完整性.算法使用端到端加密和逐跳加密相结合的方式进行数据传输,通过认证过程进行恶意节点及伪造数据的检测.仿真表明,提出的算法能够有效地检测出恶意节点,并保证融合结果的准确性.     

无线传感器网络数据融合研究

数据融合是无线传感器网络的一个研究热点,能减少传感器节点间传输的数据量和能量消耗,从而明显提高网络即时性能,延长网络生命周期,减小时间延迟。文章首先介绍了无线传感器网络中数据融合的必要性,然后介绍了数据融合的原理、层次、结构,重点介绍了多传感器数据融合的三个层次,并比较了三个融合层次的优缺点,最后对数据融合的发展趋势进行了展望。     

无线传感器网络中基于数据融合的路由算法

无线传感器网络（WSN）是远程通信方面一种极具潜力的关键技术。通过对无线传感器网络与典型通讯网络的对比分析,得出无线传感器网络路由协议都是以数据为中心进行工作的。详细分析了以MLR,GRAN,MFST和GROUP为代表的基于数据融合的路由算法。最后得出结论：将数据融合技术应用于无线传感器网络中可以明显地改善路由协议的进行效果,延长网络生存时间。     

无线传感器网络数据融合研究综述

针对近些年来数据融合的发展状况进行了综述,对现在的无线传感器网络数据融合模块的网络结构及算法进行分类研究,概述其思想并指出优缺点。文章在对无线传感器网络数据融合研究的基础上,指出该领域内存在的问题。     

无线传感器网络数据融合研究综述

由于无线传感器网络存在能量约束问题,因此在网内进行数据融合是降低节点消耗的重要手段之一。文章在简单介绍融合模型的基础上,重点分析目前提出的主要数据融合机制—应用层的数据融合、网络层的数据融合、独立的数据融合,最后给出了结论和展望。     

无线传感器网络数据融合安全机制研究

由于WSNs本身资源方面存在的局限性和脆弱性,使其安全问题成为一大挑战。随着WSNs向大范围配置的方向发展,其安全问题越来越重要。围绕WSNs的安全需求,结合WSNs的分层网络结构,研究了其各层易遭受的攻击及防御对策。本文分析了基于明文的数据融合安全机制和基于密文的数据融合安全机制,并在此基础上提出了相应的解决思路。     

基于数据融合的无线传感器网络路由算法

在分簇协议LEACH和链状协议PEGASIS的基础上,提出一种新的基于数据融合的分簇路由算法.簇首节点采用多跳方式传输数据,并根据周围节点的密集程度构造不同大小的簇;簇内节点计算上行和下行节点构造数据融合树,采用时分复用调度算法进行多跳路由.NS2仿真结果表明该路由算法均衡了各个节点的能量消耗,延长了网络存活时间,并降低了网络延迟.     

基于改进遗传算法的无线传感器网络数据融合方法

无线通信和电子技术的进步促进了无线传感器网络发展,无线传感器网络广泛应用于多个领域(如医疗,军事,家居等)。文章分析了无线传感器网络中的数据融合问题,提出了一种基于改进遗传算法的无线传感器网络数据融合方法,仿真实验表明,基于改进遗传算法的方法在运行效率上优于标准遗传算法。     

无线传感器网络优化生存时间的动态路由算法

 节能和延长网络生存时间是无线传感器网络研究领域的热点问题.该文综合考虑网络中节点的剩余能量和节点间传输数据的能耗,基于最短路径树算法,通过构造两种不同的权值函数,提出了"比例权值路由算法"(Ratio-W)与"和权值路由算法"(Sum-W).仿真分析表明,所提出的算法可以延长网络生存时间,并使能耗经济有效,比一些已有知名算法更优.     

无线传感器网络能量空洞问题研究进展

本文分析了无线传感器网络特征和能量空洞产生的主要因素,总结和评估了近年来提出的能量空洞避免策略,同时对该领域的尚存问题以及发展趋势进行了讨论。     

无线传感器网络中保障生命期和有效延时的数据融合调度方法

In scenarios of real-time data collection of long-term deployed Wireless Sensor Networks (WSNs), low-latency data collection with long network lifetime becomes a key issue. In this paper, we present a data aggregation scheduling with guaranteed lifetime and efficient latency in WSNs. We first construct a Guaranteed Lifetime Minimum Radius Data Aggregation Tree (GLMRDAT) which is conducive to reduce scheduling latency while providing a guaranteed network lifetime, and then design a Greedy Scheduling algorithM (GSM) based on finding the maximum independent set in conflict graph to schedule the transmission of nodes in the aggregation tree. Finally, simulations show that our proposed approach not only outperforms the state-of-the-art solutions in terms of schedule latency, but also provides longer and guaranteed network lifetime.     

一种多媒体传感器网络低能耗分簇协议

多媒体传感器网络面临的主要挑战是在能量受限的情况下传输大量数据。在经典分簇协议LEACH的基础上,提出一种考虑数据量的多媒体传感器网络低能耗分簇协议。在簇头选举阶段,选择剩余能量多和数据量大的节点作为簇头;在成簇阶段,同时考虑节点到簇头的通信距离和节点的数据量让节点加入簇。仿真结果表明,提出的协议能有效提高网络的生命周期。     

无线传感器网络中簇首选择算法研究

传统的低功耗自适应集簇分层型协议（LEACH）算法在选择簇首时未能考虑到节点剩余能量对网络寿命的影响,使得簇首分布不够合理。为了克服该问题,在完全分布式成簇算法（HEED）协议的基础上,设计了一种根据节点剩余能量选择簇首的算法。在该算法中,剩余能量越大的节点越有可能成为簇首,进而承担更多数据传输责任,能量消耗更加平均,增强了算法的健壮性。仿真结果证实,提出的算法可以有效提高网络能量的使用效率,减少功耗,延长网络生存时间。     

无线传感器网络能量均衡分簇路由协议

LEACH是无线传感器网络(Wireless Sensor Network,WSN)中一种经典的分层式路由协议,在此基础上通过对LEACH成簇算法及簇间路由的改进,提出了一种新的均衡能量消耗分簇路由协议。该协议在无线传感器网络成簇过程中充分考虑了传感器节点的能量状态,同时簇首向基站的通信采用基于能量的簇间路由。理论分析及仿真结果表明,改进的协议能够均衡传感器节点的能量消耗,有效地延长网络寿命。     

On Node Lifetime Problem for Energy-Constrained Wireless Sensor Networks

A fundamental problem in wireless sensor networks is to maximize network lifetime under given energy constraints. In this paper, we study the network lifetime problem by considering not only maximizing the time until the first node fails, but also maximizing the lifetimes for all the nodes in the network, which we define as the Lexicographic Max-Min (LMM) node lifetime problem. The main contributions of this paper are two-fold. First, we develop a polynomial-time algorithm to derive the LMM-optimal node lifetime vector, which effectively circumvents the computational complexity problem associated with an existing state-of-the-art approach, which is exponential. The main ideas in our approach include: (1) a link-based problem formulation, which significantly reduces the problem size in comparison with a flow-based formulation, and (2) an intelligent exploitation of parametric analysis technique, which in most cases determines the minimum set of nodes that use up their energy at each stage using very simple computations. Second, we present a simple (also polynomial-time) algorithm to calculate the flow routing schedule such that the LMM-optimal node lifetime vector can be achieved. Our results in this paper advance the state-of-the-art algorithmic design for network-wide node lifetime problem and facilitate future studies of the network lifetime problem in energy-constrained wireless sensor networks. Y. Thomas Hou obtained his B.E. degree from the City College of New York in 1991, the M.S. degree from Columbia University in 1993, and the Ph.D. degree from Polytechnic University, Brooklyn, New York, in 1998, all in Electrical Engineering. From 1997 to 2002, Dr. Hou was a research scientist and project leader at Fujitsu Laboratories of America, IP Networking Research Department, Sunnyvale, California(Silicon Valley). Since Fall 2002, he has been an Assistant Professor at Virginia Tech, the Bradley Department of Electrical and Computer Engineering, Blacksburg, Virginia. Dr. Hou's research interests are in the algorithmic design and optimization for network systems. His current research focuses on wireless sensor networks and multimedia over wireless ad hoc networks. In recent years, he has worked on scalable architectures, protocols, and implementations for differentiated services Internet; service overlay networking; multimedia streaming over the Internet; and network bandwidth allocation policies and distributed flow control algorithms. He has published extensively in the above areas and is a co-recipient of the 2002 IEEE International Conference on Network Protocols (ICNP) Best Paper Award and the 2001 IEEE Transactions on Circuits and Systems for Video Technology (CSVT) Best Paper Award. He is a member of ACM and a senior member of IEEE. Yi Shi received his B.S. degree from University of Science and Technology of China, Hefei, China, in 1998, a M.S. degree from Institute of Software, Chinese Academy of Science, Beijing, China, in 2001, and a second M.S. degree from Virginia Tech, Blacksburg, VA, in 2003, all in computer science. He is currently working toward his Ph.D. degree in electrical and computer engineering at Virginia Tech. While in undergraduate, he was a recipient of Meritorious Award in International Mathematical Contest in Modeling and 1997 and 1998, respectively. Yi's current research focuses on algorithms and optimization for wireless sensor networks and wireless ad hoc networks. His work has appeared in highly selective international conferences (e.g., ACM MobiCom and MobiHoc). Hanif D. Sherali is the W. Thomas Rice Endowed Chaired Professor of Engineering in the Industrial and Systems Engineering Department at Virginia Polytechnic Institute and State University. His area of research interest is in discrete and continuous optimization, with applications to location, transportation, and engineering design problems. He has published about 200 papers in Operations Research journals, has co-authored four books in this area, and serves on the editorial board of eight journals. He is a member of the National Academy of Engineering.     

在传感器网络中构造延迟限定的最大化生命周期树

在一些对延迟敏感的持续性监视应用中,无线传感器网络中的数据收集需要构造延迟限定的最大化生命周期树,这属于NP完全问题。提出一个新的算法MILD,通过限定树的高度来满足延迟限定,然后通过使树上“瓶颈节点”的度最小化来延长树的生命周期。实验表明,与目前已有的协议相比,MILD能有效地限定延迟并延长树的生命周期。     

基于非均匀分簇的能耗高效WSN路由协议

本文提出了能耗高效的非均匀分簇路由协议（EERP）.核心为由远及近依次求取各层成簇半径值,使得靠近sink节点的成簇半径小于远离sink节点的成簇半径;以节点剩余能量和相对距离为每个节点确定簇首竞争能力;簇间采用动态路由;依据接收比特值和簇首节点剩余能量发起簇重构.在Omnet＋＋仿真平台下模拟实验结果显示,EERP有效的均衡了全网节点能耗,显著延长了网络生命周期.     

无线传感器网络中的网内信息处理技术

无线传感器网络（WSN）的传输技术发展迅速,但单纯的传输原始感知数据并不能满足传感器网络应用日益发展的智能化需求。传感器网络的网内信息处理技术在原始采集数据的基础上,将大量的信息处理和计算移植到传感网内部进行,从海量的、杂乱无章的、难以理解的原始数据中抽取并推导出对于某些特定的用户来说具有特定意义和判决参考价值的数据。网内信息处理技术能够降低网络数据传输量、节约能量资源、提高数据精度、减小传输延迟,以达到提高网络性能,高度契合用户信息需求的目标,是未来传感器网络技术发展的重要方向。