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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。 相似文献
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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。 相似文献
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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。 相似文献
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无线传感器网络数据融合研究综述 总被引:1,自引:0,他引:1
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。 相似文献
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基于数据融合的无线传感器网络路由算法 总被引:2,自引:0,他引:2
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. 相似文献
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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。 相似文献
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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。 相似文献
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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. 相似文献
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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. 相似文献
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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. 相似文献
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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。 相似文献