无线多媒体传感器网络中一种改进路由算法

随着网络负载增加,经典的TPGF( Two-Phase geographic Greedy Forwarding)算法难以找到节点分离路径,会导致网络吞吐量、投递率以及端到端时延性能下降。此外,当网络拓扑变动不大时, TPGF中每条路径所包含节点要消耗比其他节点更多的能量,会导致其过快死亡,从而影响网络性能。为此,将联合网络编码技术引入 TPGF,提出一种编码与能量感知的 TPGF 路由算法( NE-TPGF)。该算法综合考虑节点的地理位置、编码机会、剩余能量等因素,同时利用联合网络编码技术进一步扩展编码结构,充分利用网络编码优势来建立相对最优的传输路径。仿真结果表明, NE-TPGF能够增加编码机会,提高网络吞吐量和投递率,降低端到端时延,并且还有利于减少和平衡节点的能量消耗。     

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。     

一种无线传感器网络分簇路由算法研究

在分析LEACH协议的基础上提出一种基于能量和距离的多跳路由算法（CAED）。由基站依据节点剩余能量和簇头与基站的距离分别选出二层簇头,簇内节点利用单跳和多跳模式与簇头进行通信。仿真实验表明,新算法有效地平衡了节点的能量消耗,并显著地延长了网络的生命周期。     

基于蚁群算法的无线传感器网络数据聚合路由算法

传感器网络为减少冗余数据的传输耗能。降低延迟,需要在路由过程中采用数据聚合技术。文中采用定向传输方式,在消息路由机制基础上提出了一种基于蚁群算法的数据聚合路由算法。该算法主要思想在于将节点能耗、传输距离与聚合收益3方面作为启发因子,通过一组称为“蚂蚁”的人工代理寻找到达汇聚节点的最优路径。该算法利用蚁群算法的正反馈效应来达到数据汇集的目的,不需要网络节点维护全局信息,因此是一种实现数据聚合在能量与时延上折中的分布式路由算法。理论分析和仿真结果说明了新算法的有效性。     

一种传感器网络的分布式多播路由优化算法

传感器感知的信息需要通过网络传送给感兴趣目标节点,传统网络中的多播技术往往能耗高、实时性不够理想,不利于在传感器网络中使用。针对WSN中节点对网络拓扑未知,该文先将多播路由问题演化为最优多播路径问题,通过启发式算法求解分布式最优路径,并通过一种基于贪婪思想的裁剪合并策略优化多播路由树,直至整个网络得到最优路径,最后并结合了节点区域集中以及无线多播特性,提出了DCast路由算法。最后通过仿真实验与uCast, SenCast等经典的传感器网络的多播路由算法仿真比较,可以得出其算法在时延性以及能耗等方面性能有优势。     

基于遗传算法的无线传感器网络自适应数据融合路由算法

针对移动代理以能量有效的方式收集相关性数据的问题,该文提出了一种新的基于遗传算法的自适应数据融合路由算法。算法选择移动代理路由时,根据数据传输和融合能量开销及节能增益,对移动代理迁移到每个传感器节点是否进行数据融合做自适应选择,以在信息收集过程中提高网络能量效率。仿真结果表明自适应数据融合路由算法的能量效率优于完全数据融合路由算法和最邻近启发式算法。     

无线传感器网络能量均衡路由算法

设计了一种能量均衡的路由算法.路由的建立分两个阶段,在簇头建立阶段,让候选节点在覆盖范围内以剩余能量的多少和所处位置为标准来竞选簇头,以使簇头分布均匀,平衡网络覆盖;在通信阶段,根据簇头节点的剩余能量大小和其距离基站的远近,采用多跳的簇间通信方式建立路由,以此来降低簇头节点的通信负载.仿真结果表明该算法能够有效降低网络能耗和延长网络生存时间.     

无线传感器网络簇内数据汇聚方法

数据汇聚是降低传感器网络传输能耗的重要手段。分簇传感网数据汇聚通常包括簇内汇聚及汇聚结果传输,现有方案大多关注簇构造或簇内汇聚结果传递到基站的效率。文章提出一种分簇传感网簇内数据汇聚方法,通过位置信息选择代理点,仅与代理点有不同测量值的节点进行数据发送,减少了簇内数据汇聚中的数据传输量。分析与试验表明,与相关方案比较,文章方案簇内汇聚的数据传输量较小,降低了通信开销。     

无线传感器网络中基于移动代理的自适应数据融合路由算法

该文提出在无线传感器网络中基于移动代理的自适应数据融合路由(AFMR)算法,解决移动代理如何以能量有效的方式融合、收集相关性数据的问题。该算法综合考虑了移动代理在路由过程中传输能量和融合能量的消耗,并根据数据融合算法的能量开销和节能增益,对移动代理迁移到各节点时是否执行数据融合操作进行自适应调整,以达到在各种不同的应用场景中优化移动代理能量开销的目的。通过仿真验证了在无线传感器网络的各种相关性数据收集的应用环境中,AFMR算法在节省能量方面比现有TSP和FMR的移动代理路由算法更加有效。     

具有能量供给的无线传感器网络路由算法研究

针对现有具有能量供给的无线传感器网络由算法出现的簇头分布不均匀、簇头无法连任的问题,本文提出了一种新的路由算法一CAEH（clustering algorithm for energy harvesting）,该算法通过对簇头选举机制阈值进行改进,均衡了全网簇头节点的分布,同时簇头能够连续担任不再重复选举,从而充分保存与利用供给能量。理论和仿真实验表明：与另一种对比算法相比较,CAEH算法能够提高节点平均剩余能量以及存活节点的数量。     

A Performance Evaluation of a Novel Energy-Aware Data-Centric Routing Algorithm in Wireless Sensor Networks

In this paper, we present a novel Energy-Aware Data-Centric Routing algorithm for wireless sensor networks, which we refer to as EAD. We discuss the algorithm and its implementation, and report on the performance results of several workloads using the network simulator ns-2. EAD represents an efficient energy-aware distributed protocol to build a rooted broadcast tree with many leaves, and facilitate the data-centric routing in wireless micro sensor networks. The idea is to turn off the radios of all leaf nodes and let the non-leaf nodes be in charge of data aggregation and relaying tasks. The main contribution of this protocol is the introduction of a novel approach based on a low cost backbone provisioning within a wireless sensor network in order to turn off the non backbone nodes and save energy without compromising the connectivity of the network, and thereby extending the network lifetime. EAD makes no assumption on the network topology, and it is based on a residual power. We present an extensive simulation experiments to evaluate the performance of our EAD forwarding-to-parent routing scheme over a tree created by a single EAD execution, and compare it with the routing scheme over a regular Ad hoc On-Demand Distance Vector (AODV) Protocol. Last but not least, we evaluate the performance of our proposed EAD algorithm and compare it to the Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol, a cluster-based, energy-aware routing protocol specifically designed for sensor networks. Our results indicate clearly that EAD outperforms AODV and LEACH in energy conservation, throughput, and network lifetime extension.Dr. A. Boukerche was partially supported by NSERC, Canada Research Program, Canada Foundation for Innovation, and Ontario Innovation Funds/Ontario Distinguished Research Award.Azzedine Boukerche is a Full Professor and holds a Canada Research Chair Position at the University of Ottawa. He is also the Founding Director of PARADISE Research Laboratory at Ottawa U. Prior to this, he hold a faculty position at the University of North Texas, USA, and he was working as a Senior Scientist at the Simulation Sciences Division, Metron Corporation located in San Diego. He was also employed as a Faculty at the School of Computer Science McGill University, and taught at Polytechnic of Montreal. He spent a year at the JPL-California Institute of Technology where he contributed to a project centered about the specification and verification of the software used to control interplanetary spacecraft operated by JPL/NASA Laboratory.His current research interests include wireless networks, mobile and pervasive computing, wireless multimedia, QoS service provisioning, wireless ad hoc and sensor networks, distributed systems, distributed computing, large-scale distributed interactive simulation, and performance modeling. Dr. Boukerche has published several research papers in these areas. He was the recipient of the best research paper award at PADS’97, and the recipient of the 3rd National Award for Telecommunication Software 1999 for his work on a distributed security systems on mobile phone operations, and has been nominated for the best paper award at the IEEE/ACM PADS’99, and at ACM MSWiM 2001. Dr. A. Boukerche serves as an Associate Editor and on the editorial board for ACM/Springer Wireless Networks, the Journal of Parallel and Distributed Computing, The Wiley Journal of Wireless Communication and Mobile Computing. He served as a Founding and General Chair of the first Int’l Conference on Quality of Service for Wireless/Wired Heterogeneous Networks (QShine 2004), ACM/IEEE MASCOST 1998, IEEE DS-RT 1999-2000, ACM MSWiM 2000; Program Chair for ACM/IFIPS Europar 2002, IEEE/SCS Annual Simulation Symposium ANNS 2002, ACM WWW’02, IEEE/ACM MASCOTS 2002, IEEE Wireless Local Networks WLN 03-04; IEEE WMAN 04-05, ACM MSWiM 98–99, and TPC member of numerous IEEE and ACM conferences. He served as a Guest Editor for JPDC, and ACM/kluwer Wireless Networks and ACM/Kluwer Mobile Networks Applications, and the Journal of Wireless Communication and Mobile Computing.Dr. Boukerche serves as a Steering Committee Chair for ACM MSWiM, IEEE DS-RT, and ACM PE-WASUN Conferences.Xiuzhen Cheng is an Assistant Professor in the Department of Computer Science at the George Washington University. She received her MS and Ph.D. degrees in Computer Science from University of Minnesota—Twin Cities in 2000 and 2002, respectively. Her current research interests include localization, data aggregation services, and data storage in sensor networks, routing in mobile ad hoc networks, and approximation algorithm design and analysis. She is a member of the ACM and IEEE.Joseph Linus has recently graduated with a MSc Degree from the Department of Computer Sciences, University of North Texas. His current research interests include wireless sensors networks, and mobile ad hoc networks.     

无线传感器网络中基于自适应定时器策略的分簇算法

提出了一种适用于无线传感器网络的基于自适应定时器策略的分簇算法,该算法通过自适应调整节点的等待时间来保证较多电池能量的节点有更大的机会成为簇首.理论分析表明该算法不仅实现了系统的动态负载均衡,并且能够通过参数的设置确保簇首的均匀分布.仿真结果显示该算法有效地延长了系统生命,提高了网络的能耗效率.     

基于BWAS的无线传感器网络静态分簇路由算法

为提高路径搜索效率,避免动态分簇较多的能量消耗,提出了基于最优-最差蚂蚁系统(BWAS)的无线传感器网络静态分簇路由算法.BWAS是对蚁群算法的改进,在路径搜寻过程中评价出最优最差蚂蚁,引入奖惩机制,加快了路径搜索速度.通过无线传感器网络静态分簇、簇内动态选举簇头,在簇头节点间运用BWAS算法搜寻从簇头节点到汇聚节点的多跳最优路径,能减少路径寻优能量消耗,实现均衡能量管理,延长网络寿命,且具有较强的鲁棒性.通过与基于BWAS的动态分簇和基于蚁群算法的动态分簇路由的仿真实验相比较,证实了本算法的有效性.     

An Energy-Efficient Routing and Self-Organization Algorithm in Wireless Sensor Networks

1IntroductionAs the development of MEMStechnology,the microsensors whichintegrate manyfunctions such as sensing,signal processing and communication have been widelyused[1]. Wireless Sensor Network ( WSN) is construct-ed with hundreds to thousands of sensors and one ormore SINKs .Sensors can sense (monitor) many physi-cal signals such as sound,light ,electronics ,tempera-ture and humidity of the objects in a given region[2 ~3].Sensors transfer these signalsinto sensing data and sendsensin…     

一种传感器网络跨层能量优先成簇算法

文中提出CLEEC跨层能量优先成簇算法,基于节点剩余能量来选举簇头节点,使网络能量均匀消耗,延长网络的生存时间.模拟实验结果显示,与现有的典型成簇方案相比,新的成簇算法在传感器网络下提供了更长的网络生存时间和更大的网络吞吐量.     

基于分簇的水下传感器网络覆盖保持路由算法

在基于分簇架构的水下传感器网络（Underwater Sensor Networks ,UWSNs）中,当簇首以单跳或多跳的通信方式将数据传输至Sink节点时,由于簇首转发大量数据而负载过重,会过早耗尽能量而死亡,这将导致提前出现对监测区域的覆盖盲区。以改善覆盖效果为目标的LEACH-Coverage-U算法由于选举簇首的分簇方法具有随机性,也无法很好解决该问题。本文提出了一种水下传感器网络单跳覆盖保持路由算法（Single-hop Coverage-Preserving Routing Algo-rithm ,SCPR）,首先定义了覆盖冗余度（Coverage Redundancy ,CR）,然后根据该度量来选举簇首,最终以单跳方式直接将数据传送至Sink节点。为减少簇首能耗并获得更高的网络覆盖率,本文还提出一种多跳覆盖保持路由算法（Multi-hop Coverage-Preserving Routing Algorithm ,MCPR ）,簇首之间通信时优先考虑父节点中CR较高的簇首作为其下一跳路由,以多跳路由将数据传送至Sink节点。仿真结果表明,与LEACH-Coverage-U算法相比,SCPR、MCPR算法避免了其选举簇首时的随机性,提高了网络覆盖率,降低了网络能耗,延长了网络生命周期。     

一种适用于唤醒机制的异构传感器网络节点协同唤醒路由算法

基于定向扩散算法,本文提出一种适用于唤醒机制的异构传感器网络节点协同唤醒路由算法(CWR,Cooperative Wake-up Ruting),就近选取低能耗节点代替高能耗节点进行多级扩散,增加路由替换和路由修补两个步骤建立低能耗节点到相应高能耗节点的路由信息,为异构传感器网络中唤醒实现提供必要的网络拓扑基础.仿真实验表明本文算法在支持唤醒机制实现过程中的节能特性.     

基于生成树的无线传感器网络分布式路由协议

在无线传感器网络中,节点具有有限的电池能量,为了延长网络的生存时间,提出了一种基于生成树的分布式路由协议STRP及其具有能量意识的改进版本STRP-PA.每个传感器节点根据相邻节点与基站的距离、剩余能量等信息寻找父节点,构造一棵以基站为根的近优最小生成树,节点采集的数据沿树传输,并在树杈节点进行聚合.仿真实验结果表明:STRP-PA协议能够节省网络能量,显著延长网络稳定工作的时间,性能明显好于LEACH协议.     

WSANs中基于跳步数自适应的路由算法

无线传感反应网络是由大量传感节点和少量（可移动）资源丰富的反应节点构成.传感节点 负责收集外部环境信息,而反应节点对外部环境实施相应的操作.本文分析节点能量消耗模 型,求解出理想条件下单条路径上总能耗最小时的最优跳步数.在此基础上,提出了一种跳 步数自适应的路由算法HAR,用来实现数据收集的实时需求与能量消耗之间的平衡.仿真实验 表明：HAR算法在平衡能量消耗与时间延迟的性能上优于HBMECT算法,而且能较好地适用于 反应节点移动的情形.