基于抽样估计的能量异构无线传感器网络分簇算法

提出一种基于抽样估计的能量异构无线传感器网络分簇算法.采取对网络中节点抽样的办法估计出网络中的平均剩余能量,节点根据剩余能量与网络平均能量的比例来进行簇首竞争,使簇首选择更加合理.仿真实验表明:该算法可以更好地实现负载均衡,延长的网络生存时间.     

一种基于休眠调度策略的无线传感网络分簇协议

文中设计了一种基于休眠调度策略的无线传感网络分簇协议.该协议计算出簇首最佳比例和网络瞬时剩余能量,采用固定簇首数目与剩余能量估计的方法对网络进行分簇,在成簇后的数据传送阶段采用蚁群算法计算出节点的唤醒概率,最后通过仿真实验与LEACH、SEP协议进行了比较.实验结果表明:该协议在对目标保持较好探测效果的前提下能更均匀的消耗网络的能量,从而延长网络的生命周期.     

无线传感器网络的分区异构分簇协议研究

针对无线传感器网络能量受限和路由协议中节点能量消耗不均衡的问题,提出一种新的无线传感器网络的分区异构分簇协议(PHC协议).该协议的核心是将3种不同能量等级的节点根据能量的不同分别部署在不同区域,能量较高的高级节点和中间节点使用聚类技术通过簇头直接传输数据到汇聚点,能量较低的普通节点则直接传输数据到汇聚点.仿真结果表明,该协议通过对节点合理的分配部署,使簇头分布均匀,更好地均衡了节点的能量消耗,延长了网络的稳定期,提高了网络的吞吐量,增强了网络的整体性能.     

无线传感器网络能量异构分簇算法的研究

在无线传感器网络能量异构环境下对低功耗自适应的分簇算法(Low Energy Adaptive Clustering Hierarchy,LEACH)与稳定选举协议(Stable Election Protocol,SEP)算法进行了分析,针对其存在的不足提出了一种改进的方案。在簇头选举过程中提高了剩余能量高、距离基站较近节点当选为簇头的概率,同时对当选为簇头的节点设定能量阈值,避免能量过低的节点当选为簇头。仿真结果表明,改进后的算法较好地均衡了网络中节点的能量消耗,有效地提高了网络中能量的利用效率,并且极大地延长了网络正常工作的生命周期。     

面向异构无线传感器网络的节点调度算法

针对传感器网络中的节点冗余问题,提出了一种冗余判别方法来关闭冗余节点,以达到延长网络生命周期的目的.首先按邻居节点的不同位置对节点进行分类,研究了每组邻居节点的网络覆盖率与工作节点数k之间的约束关系,在此基础上,按不同的冗余法则对节点进行判断,关闭冗余节点.理论分析和实验结果表明,提出的算法能关闭网络中的冗余节点从而有效地延长网络的生存时间.     

一种近似秩排序的无线传感器网络分簇路由算法

为了延长无线传感器网络(WSN)的生存期,能量有效的路由算法至关重要。以分配网络中的业务负载为目标的传感器节点聚类是解决无线传感器网络能量均衡的有效方法。文中为无线传感器网络提出一种基于近似秩排序(ARO)的分层和基于距离的组合聚类方法,并使用多跳数据传输。仿真结果表明,ARO-WSN在能耗和网络生存期方面优于经典的LEACH算法、LEACH-C算法和K-means聚类算法,能有效地延长网络的生存期。     

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。     

一种新的无线可充电传感器网络分簇算法

为了弥补现有无线可充电传感器网络充电效率低下和节点能量冗余并存的问题,提出了一种基于节点信息的分簇算法。首先,根据传感器节点的剩余能量状态,选择候选簇首。其次,计算候选簇首集合中节点之间的距离,并与基于节点密度的距离阈值比较,最终筛选出合适的簇首。其他节点根据就近原则选择簇首,形成对应的簇。该算法由于同时考虑节点剩余能量和簇首之间的距离,可以使得具有较多剩余能量的节点成为簇首,且簇首均匀分布整个网络中。仿真结果表明,提出的算法可以提高充电效率,减少节点的能量冗余或节点能量消耗过快而死亡的现象,从而有效延长整个网络的寿命。     

分簇式无线传感器网络睡眠调度机制研究

提出了一个容忍节点失效和时间同步误差的簇内睡眠调度算法JCSS(Intra-Cluster Sleeping scheduling),该算法不需要外部的精确时间同步机制,对不同类型的节点采用不同的调度机制,在对时间同步的估计中考虑了误差和更新.仿真实验显示在密集部署的网络环境中,该睡眠调度算法在满足网络传输性能的情况下,相对于无同步的固定时间间隔调度和有同步的固定时间间隔调度,网络生存周期分别提高了16.7%和10.5%.     

邻近信息约束下的随机异构无线传感器网络节点调度算法

针对高密度部署的随机异构传感器网络内部存在的覆盖冗余问题,该文提出一种随机异构无线传感器网络的节点调度算法(NSSH)。在网络原型拓扑的支撑下构建Delaunary三角剖分,规划出节点进行本地化调度的局部工作子集。通过折中与邻近节点的空外接圆半径,完成对感知半径的独立配置;引入几何线、面概念,利用重叠面积和有效约束圆弧完成对灰、黑色节点的分类识别,使得节点仅依赖本地及邻居信息进行半径调整和冗余休眠。仿真结果表明,NSSH能以低复杂度的代价,近似追平贪婪算法的去冗余性能,并表现出了对网络规模、异构跨度和参数配置的低敏感性。     

异构多媒体传感器网络服务质量研究

随着异构无线多媒体传感器网络应用日益广泛,如何满足不同数据源的要求,为其提供区分服务,保证其服务质量成为研究热点问题。该文在引进区分队列服务算法的基础上,提出了解决方法。该方法通过设置分组生存时间来实现在标量节点能够及时可靠地向汇聚节点报告事件发生的前提下,保证实时分组优先转发。仿真实验显示,汇聚节点在规定时间内收到了足够多的事件相关标量分组,实时分组时延满足实时性要求。表明文中方法是正确有效的。     

Scheduling Sleeping Nodes in High Density Cluster-based Sensor Networks

In order to conserve battery power in very dense sensor networks, some sensor nodes may be put into the sleep state while other sensor nodes remain active for the sensing and communication tasks. In this paper, we study the node sleep scheduling problem in the context of clustered sensor networks. We propose and analyze the Linear Distance-based Scheduling (LDS) technique for sleeping in each cluster. The LDS scheme selects a sensor node to sleep with higher probability when it is farther away from the cluster head. We analyze the energy consumption, the sensing coverage property, and the network lifetime of the proposed LDS scheme. The performance of the LDS scheme is compared with that of the conventional Randomized Scheduling (RS) scheme. It is shown that the LDS scheme yields more energy savings while maintaining a similar sensing coverage as the RS scheme for sensor clusters. Therefore, the LDS scheme results in a longer network lifetime than the RS scheme. Jing Deng received the B.E. and M.E. degrees in Electronic Engineering from Tsinghua University, Beijing, P. R. China, in 1994 and 1997, respectively, and the Ph.D. degree in Electrical and Computer Engineering from Cornell University, Ithaca, NY, in 2002. Dr. Deng is an assistant professor in the Department of Computer Science at the University of New Orleans. From 2002 to 2004, he visited the CASE center and the Department of Electrical Engineering and Computer Science at Syracuse University, Syracuse, NY as a research assistant professor, supported by the Syracuse University Prototypical Research in Information Assurance (SUPRIA) program. He was a teaching assistant from 1998 to 1999 and a research assistant from 1999 to 2002 in the School of Electrical and Computer Engineering at Cornell University. His interests include mobile ad hoc networks, wireless sensor networks, wireless network security, energy efficient wireless networks, and information assurance. Wendi B. Heinzelman is an assistant professor in the Department of Electrical and Computer Engineering at the University of Rochester. She received a B.S. degree in Electrical Engineering from Cornell University in 1995 and M.S. and Ph.D. degrees in Electrical Engineering and Computer Science from MIT in 1997 and 2000 respectively. Her current research interests lie in the areas of wireless communications and networking, mobile computing, and multimedia communication. Dr. Heinzelman received the NSF Career award in 2005 for her work on cross-layer optimizations for wireless sensor networks, and she received the ONR Young Investigator award in 2005 for her research on balancing resource utilization in wireless sensor networks. Dr. Heinzelman was co-chair of the 1st Workshop on Broadband Advanced Sensor Networks (BaseNets '04), and she is a member of Sigma Xi, the IEEE, and the ACM. Yunghsiang S. Han was born in Taipei, Taiwan, on April 24, 1962. He received the B.S. and M.S. degrees in electrical engineering from the National Tsing Hua University, Hsinchu, Taiwan, in 1984 and 1986, respectively, and the Ph.D. degree from the School of Computer and Information Science, Syracuse University, Syracuse, NY, in 1993. From 1986 to 1988 he was a lecturer at Ming-Hsin Engineering College, Hsinchu, Taiwan. He was a teaching assistant from 1989 to 1992 and from 1992 to 1993 a research associate in the School of Computer and Information Science, Syracuse University. From 1993 to 1997 he was an Associate Professor in the Department of Electronic Engineering at Hua Fan College of Humanities and Technology, Taipei Hsien, Taiwan. From 1997 to 2004 he was with the Department of Computer Science and Information Engineering at National Chi Nan University, Nantou, Taiwan. He was promoted to Full Professor in 1998. From June to October 2001 he was a visiting scholar in the Department of Electrical Engineering at University of Hawaii at Manoa, HI, and from September 2002 to January 2004 he was the SUPRIA visiting research scholar in the Department of Electrical Engineering and Computer Science and CASE center at Syracuse University, NY. He is now with the Graduate Institute of Communication Engineering at National Taipei University, Taipei, Taiwan. His research interests are in wireless networks, security, and error-control coding. Dr. Han is a winner of 1994 Syracuse University Doctoral Prize. Pramod K. Varshney was born in Allahabad, India on July 1, 1952. He received the B.S. degree in electrical engineering and computer science (with highest honors), and the M.S. and Ph.D. degrees in electrical engineering from the University of Illinois at Urbana-Champaign in 1972, 1974, and 1976 respectively. Since 1976 he has been with Syracuse University, Syracuse, NY where he is currently a Professor of Electrical Engineering and Computer Science and the Research Director of the New York State Center for Advanced Technology in Computer Applications and Software Engineering. His current research interests are in distributed sensor networks and data fusion, detection and estimation theory, wireless communications, intelligent systems, signal and image processing, and remote sensing he has published extensively. He is the author of Distributed Detection and Data Fusion, published by Springer-Verlag in 1997 and has co-edited two other books. Dr. Varshney is a member of Tau Beta Pi and is the recipient of the 1981 ASEE Dow Outstanding Young Faculty Award. He was elected to the grade of Fellow of the IEEE in 1997 for his contributions in the area of distributed detection and data fusion. In 2000, he received the Third Millennium Medal from the IEEE and Chancellor's Citation for exceptional academic achievement at Syracuse University. He serves as a distinguished lecturer for the AES society of the IEEE. He is on the editorial board Information Fusion. He was the President of International Society of Information Fusion during 2001.     

Range-Based Sleep Scheduling (RBSS) for Wireless Sensor Networks

Sleep scheduling in a wireless sensor network is the process of deciding which nodes are eligible to sleep (enter power-saving mode) after random deployment to conserve energy while retaining network coverage. Most existing approaches toward this problem require sensor’s location information, which may be impractical considering costly locating overheads. This paper proposes range-based sleep scheduling (RBSS) protocol which needs sensor-to-sensor distance but no location information. RBSS attempts to approach an optimal sensor selection pattern that demands the fewest working (awake) sensors. Simulation results indicate that RBSS is comparable to its location-based counterpart in terms of coverage quality and the reduction of working sensors.

基于聚类的无线传感网络的合作MIMO传输方案

Wireless sensor network is becoming more and more popular in recent years, but energy-constrained characteristic of sensor nodes is one of the critical issues that we must consider in system design. In this paper, a cluster-based virtual V-BLAST transmission scheme is proposed to achieve energy savings for energy-constrained wireless sensor networks. In the proposed scheme, instead of using cluster member as cooperative nodes, multiple cluster heads cooperate to form virtual antenna array so that V-BLAST based virtual MIMO transmission can be implemented. Based on the communication energy consumption model, a way to optimize the parameters for the scheme is given. In addition, detailed simulation is performed to evaluate the performance of the proposed scheme for both densely and sparsely deployed sensor networks. Theoretical analysis and simulation results verify the energy efficiency of the proposed scheme.     

基于分簇的无线多媒体传感器网络数据聚合方案研究

该文提出了一种基于分簇的无线多媒体传感器网络(WMSNs)数据聚合方案(Cluster-based Data Aggregation Algorithm, CDAA)。利用新的分簇方法和数据聚合策略,CDAA可以有效延长网络生命期。根据多媒体节点数据采集的方向性和节点剩余能耗,该文提出新的无线多媒体传感器网络的分簇方法,并基于该分簇方法进行网内多媒体数据聚合。仿真结果表明,该方法能够有效减少冗余数据的传送,与LEACH, PEGASIS等传统WSNs路由协议和针对WMSNs的AntSensNet协议相比,在能耗均衡和节能方面表现出更好的性能。     

基于网格的移动无线传感网生存时间优化算法

为克服陆地静态无线传感网和水下无线传感网因节点能耗分布不均衡而出现的能量空穴问题,和具有单一移动Sink节点的无线传感网数据收集时延过长问题,该文提出基于网格的移动无线传感网生存时间优化算法(Grid-based Lifetime Optimization Algorithm,GLOA)。GLOA算法考虑多个Sink节点的移动,将监测区域分成多个大小相同的网格。根据网格潜能值确定Sink节点移动的锚点,将锚点分配给不同的Sink节点,建立路径选择优化模型并获得Sink节点的最短移动路径,采用移动收集方法或静态收集方法循环收集数据。仿真结果表明:与Ratio_w或TPGF算法相比,GLOA算法能延长网络生存时间,降低和均衡节点能耗。与LOA_SMSN算法相比,GLOA算法能降低数据收集时延。在一定的条件下,比Ratio_w,TPGF和LOA_SMSN算法更优。     

无线传感器网络中基于概率的能量平衡算法

各传感器节点的能耗不平衡严重地影响了无线传感器网络的生命周期。该文提出了基于传输概率的能量平衡算法。首先把圆形区域网络模型划分成若干圆环,每一圆环中的传感器节点以混合传输的方式传输数据。其次,为使每个传感器节点能耗均衡,提出了一种混合传输概率求解算法,获得一组传输概率决定节点传输数据的方式,从而更好地平衡网络能耗。然后对圆环宽度进行了分析和优化。仿真结果证明这些算法可以有效地降低网络能耗,延长网络生命周期。     

Lightweight Deployment-Aware Scheduling for Wireless Sensor Networks

Wireless sensor networks consist of a large number of tiny sensors that have only limited energy supply. One of the major challenges in constructing such networks is to maintain long network lifetime as well as sufficient sensing areas. To achieve this goal, a broadly-used method is to turn off redundant sensors. In this paper, the problem of estimating redundant sensing areas among neighbouring wireless sensors is analysed. We present simple methods to estimate the degree of redundancy without the knowledge of location or directional information. We also provide tight upper and lower bounds on the probability of complete redundancy and on the average partial redundancy. With random sensor deployment, our analysis shows that partial redundancy is more realistic for real applications, as complete redundancy is expensive, requiring up to 11 neighbouring sensors to provide a 90 percent chance of complete redundancy. Based on the analysis, we propose a scalable Lightweight Deployment-Aware Scheduling (LDAS) algorithm, which turns off redundant sensors without using accurate location information. Simulation study demonstrates that the LDAS algorithm can reduce network energy consumption and provide desired QoS requirement effectively. This research was partially supported by Natural Sciences and Engineering Research Council of Canada. Kui Wu received his Ph.D. in Computing Science from the University of Alberta, Canada, in 2002. He joined the Department of Computer Science at the University of Victoria, Canada in the same year and is currently an Assistant Professor there. His research interests include mobile and wireless networks, network performance evaluation, and network security. Yong Gao received his Master's degree and Ph.D. degree in computer science from University of Alberta, Canada, in 2000 and 2005 respectively. He is currently with the Irving K. Barber School of Arts and Sciences, UBC Okanagan, Canada. His research interests include search algorithms and AI, communication networks, and computational biology. Yang Xiao worked at Micro Linear as an MAC (Medium Access Control) architect involving the IEEE 802.11 standard enhancement work before he joined Department of Computer Science at The University of Memphis in 2002. Dr. Xiao is an IEEE Senior member. He was a voting member of IEEE 802.11 Working Group from 2001 to 2004. He currently serves as Editor-in-Chief for International Journal of Security and Networks (IJSN) and for International Journal of Sensor Networks (IJSNet). He serves as an associate editor or on editorial boards for the following refereed journals: (Wiley) International Journal of Communication Systems, (Wiley) Wireless Communications and Mobile Computing (WCMC), EURASIP Journal on Wireless Communications and Networking, and International Journal of Wireless and Mobile Computing. He serves as five lead/sole guest editor for five journal special issues. He serves as a referee/reviewer for many funding agencies, as well as a panelist for NSF. His research interests are Security/ Reliable Communications, Medium Access Control, Mobility/Location/Paging Managements, Cache Access and Replacement Policies, Quality of Service, Energy Efficiency, and Routing in wireless networks and mobile computing.     

传感器网络簇头选举与调度策略研究

 为了最大化分簇网络的生存周期,提出基于线性规划的簇头选举策略(LPCHS)和基于簇头时间比的簇头调度算法(CHSA).LPCHS根据数据流守恒约束和能量约束等条件,建立线性规划方程,得到簇生存周期、簇中各节点轮为簇头的时间及相应的簇头时间比.CHSA采用多路径路由技术完成簇间数据转发,得到基于簇头时间比的簇头调度方案.