异构无线传感器网络覆盖优化算法

针对异构传感网络节点在初始随机部署时产生覆盖盲区的问题,受简单随机抽样理论和最优化算法的启发,该文提出一种适用于感知半径异构的无线传感网覆盖优化算法。该算法以提高网络覆盖率和节点移动距离最小为优化目标,根据采样直线与平面感知圆的交点坐标之间的关系,建立了二次优化的数学模型。当平面中的多条采样直线段达到最优覆盖时,该文算法可以使平面的覆盖得到优化。实验证明,该算法能够有效提高异构网的覆盖率。     

一种新的无线异构网络的自适应垂直切换算法

针对当前无线异构网络融合技术中的垂直切换机制,提出了一种以平均接收信号强度为评价指标,并由此指标判断可能的运动趋势的自适应垂直切换算法。仿真结果表明:相比于传统的固定门限的平均接收信号强度垂直切换算法,提出的方法能较好地预测并提前触发该发生的切换,改善切换性能。     

基于混沌鱼群改进算法的无线传感网覆盖优化

针对无线传感器节点覆盖分布极不均匀,冗余度高,导致网络覆盖率低、成本高的问题,提出一种改进人工鱼群算法进行优化的覆盖方法。采用以节点的有效覆盖率、利用率和功耗作为优化目标,建立相应的数学模型,然后通过引入混沌初始化和自适应步长、视野的搜索机制对算法进行改进,并使用改进后鱼群算法对模型进行求解,得到优化的无线传感器网络覆盖方案。通过与原始鱼群算法的对比仿真,得出结果表明改进后的算法提高了节点的覆盖率,在一定程度减少了冗余度,使网络的有效生存时间得到了延长。     

一种无线传感网终端系统设计

对无线传感器网络的特点进行了分析和总结。以低功耗、短距离多跳通信为出发点提出了系统设计思路和方法,讨论了系统设计中的关键技术和问题并给出相应的解决策略。在设计中采用了超低功耗的单片机并提出了超帧异步的通信方式。分析了系统设计上的一些问题,给出了相应的解决方法。     

基于准格型策略的无线传感网协作覆盖算法

该文提出了一种基于准格型策略的无线传感网协作覆盖QGCC(Quasi-Grid based Cooperative Coverage)算法,通过在随机分布节点中构造准格型结构并结合协作感测模型,减少活动节点数量,延长覆盖周期。QGCC设计了低复杂度的分布式虚拟网格确定方法及能量高效的节点调度策略,定义了不规则度指标以分析网络的不规则程度对覆盖性能的影响。仿真实验表明,相比于参照算法,QGCC能够较大程度地减少活动节点的数量,大幅延长网络的覆盖周期;此外,该算法的覆盖周期和节点密度具有近似线性的关系,且比参考算法具有更大的斜率,说明其对冗余节点具有更高的利用效率。     

一种异构配置的无线传感网成本分析

根据对无线传感节点组成与无线传感网应用环境中各物理特征量非均匀分布,且在分布密度上具有较大差异的情况分析,提出一种异构分布配置模型,在网络配置时采用与感知物理特征量空间分布特征相适应的异构节点配置方法。由此减少节点配置冗余和信息冗余,降低无线传感网的配置成本。仿真实验证明,该模型可节省成本,是更适合于未来无线传感网实际应用要求的通用结构配置模型。     

一种带有可控动态参数的优化覆盖算法

能耗与覆盖问题是无线传感器网络研究领域的基本问题,也是一个重点问题。针对传感器节点所呈现的同构性特点,提出了一种带有可控动态参数的优化覆盖算法（OCCDP）。该算法首先给出了3节点联合覆盖时,最大无缝覆盖率的求解过程;其次,给出了在监测区域内存在传感器节点覆盖时,覆盖质量期望值求解方法以及与邻居节点进行覆盖比对时覆盖率的判定方法;当存在冗余覆盖时,给出了任意传感器节点处于冗余节点覆盖时的覆盖率的计算过程;最后,通过仿真实验与其他算法在覆盖质量和网络生存周期等方面进行对比,其性能指标平均提升了11.02%和13.27%,从而验证了提出算法的有效性和可行性。     

一种新的基于磁感应技术无线地下传感网收发器设计

针对无线地下传感器网络（Wireless Underground Sensor Network,WUSN）中的信道高路径损耗、信道条件动态变化大和天线尺寸过大等问题,提出一种基于磁感应技术的WUSN收发节点的硬件设计方案。设计了通信系统节点的硬件结构及主控制器和线圈的选型,以及包括天线发射电路、接收电路、程控放大电路和高速A/D采样电路的收发器外围电路,并给出了相关关键参数设计性能指标,搭建了收发通信和性能测试平台。实验结果表明：经FIR滤波器和希尔伯特检波后低频干扰被滤除,降低了误包率,硬件节点满足要求,验证了设计的可行性和可靠性。     

一种基于异构网络的自适应垂直切换算法

提出一种基于WSN与WLAN异构网络环境下无缝移动通信的垂直切换算法。该算法针对日益普及的传感器网络自身特点与室内应急通信应用的特殊性,提出网络选取优先级参数。针对传感器网络在应急通信等特殊场合的应用．制定了专门的切换判决策略。实验分析表明,该算法可以一定程度地提高通信网络对现场场景变化的适应程度,满足室内环境下异构网络通信的需求。     

Localized algorithms for coverage boundary detection in wireless sensor networks

Connected coverage, which reflects how well a target field is monitored under the base station, is the most important performance metric used to measure the quality of surveillance that wireless sensor networks (WSNs) can provide. To facilitate the measurement of this metric, we propose two novel algorithms for individual sensor nodes to identify whether they are on the coverage boundary, i.e., the boundary of a coverage hole or network partition. Our algorithms are based on two novel computational geometric techniques called localized Voronoi and neighbor embracing polygons. Compared to previous work, our algorithms can be applied to WSNs of arbitrary topologies. The algorithms are fully distributed in the sense that only the minimal position information of one-hop neighbors and a limited number of simple local computations are needed, and thus are of high scalability and energy efficiency. We show the correctness and efficiency of our algorithms by theoretical proofs and extensive simulations. Chi Zhang received the B.E. and M.E. degrees in Electrical Engineering from Huazhong University of Science and Technology, Wuhan, China, in July 1999 and January 2002, respectively. Since September 2004, he has been working towards the Ph.D. degree in the Department of Electrical and Computer Engineering at the University of Florida, Gainesville, Florida, USA. His research interests are network and distributed system security, wireless networking, and mobile computing, with emphasis on mobile ad hoc networks, wireless sensor networks, wireless mesh networks, and heterogeneous wired/wireless networks. Yanchao Zhang received the B.E. degree in computer communications from Nanjing University of Posts and Telecommunications, Nanjing, China, in July 1999, the M.E. degree in computer applications from Beijing University of Posts and Telecommunications, Beijing, China, in April 2002, and the Ph.D. degree in electrical and computer engineering from the University of Florida, Gainesville, in August 2006. Since September 2006, he has been an Assistant Professor in the Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark. His research interest include wireless and Internet security, wireless networking, and mobile computing. He is a member of the IEEE and ACM. Yuguang Fang received the BS and MS degrees in Mathematics from Qufu Normal University, Qufu, Shandong, China, in 1984 and 1987, respectively, a Ph.D. degree in Systems and Control Engineering from Department of Systems, Control and Industrial Engineering at Case Western Reserve University, Cleveland, Ohio, in January 1994, and a Ph.D. degree in Electrical Engineering from Department of Electrical and Computer Engineering at Boston University, Massachusetts, in May 1997. From 1987 to 1988, he held research and teaching position in both Department of Mathematics and the Institute of Automation at Qufu Normal University. From September 1989 to December 1993, he was a teaching/research assistant in Department of Systems, Control and Industrial Engineering at Case Western Reserve University, where he held a research associate position from January 1994 to May 1994. He held a post-doctoral position in Department of Electrical and Computer Engineering at Boston University from June 1994 to August 1995. From September 1995 to May 1997, he was a research assistant in Department of Electrical and Computer Engineering at Boston University. From June 1997 to July 1998, he was a Visiting Assistant Professor in Department of Electrical Engineering at the University of Texas at Dallas. From July 1998 to May 2000, he was an Assistant Professor in the Department of Electrical and Computer Engineering at New Jersey Institute of Technology, Newark, New Jersey. In May 2000, he joined the Department of Electrical and Computer Engineering at University of Florida, Gainesville, Florida, where he got early promotion to Associate Professor with tenure in August 2003, and to Full Professor in August 2005. His research interests span many areas including wireless networks, mobile computing, mobile communications, wireless security, automatic control, and neural networks. He has published over one hundred and fifty (150) papers in refereed professional journals and conferences. He received the National Science Foundation Faculty Early Career Award in 2001 and the Office of Naval Research Young Investigator Award in 2002. He also received the 2001 CAST Academic Award. He is listed in Marquis Who’s Who in Science and Engineering, Who’s Who in America and Who’s Who in World. Dr. Fang has actively engaged in many professional activities. He is a senior member of the IEEE and a member of the ACM. He is an Editor for IEEE Transactions on Communications, an Editor for IEEE Transactions on Wireless Communications, an Editor for IEEE Transactions on Mobile Computing, an Editor for ACM Wireless Networks, and an Editor for IEEE Wireless Communications. He was an Editor for IEEE Journal on Selected Areas in Communications:Wireless Communications Series, an Area Editor for ACM Mobile Computing and Communications Review, an Editor for Wiley International Journal on Wireless Communications and Mobile Computing, and Feature Editor for Scanning the Literature in IEEE Personal Communications. He has also actively involved with many professional conferences such as ACM MobiCom’02 (Committee Co-Chair for Student Travel Award), MobiCom’01, IEEE INFOCOM’06, INFOCOM’05 (Vice-Chair for Technical Program Committee), INFOCOM’04, INFOCOM’03, INFOCOM’00, INFOCOM’98, IEEE WCNC’04, WCNC’02, WCNC’00 Technical Program Vice-Chair), WCNC’99, IEEE Globecom’04 (Symposium Co-Chair), Globecom’02, and International Conference on Computer Communications and Networking (IC3N) (Technical Program Vice-Chair).     

An energy-efficient optimization deployment scheme for wireless sensor networks

Most of the current deployment schemes for Wireless Sensor Networks (WSNs) do not take the network coverage and connectivity features into account, as well as the energy consumption. This paper introduces topology control into the optimization deployment scheme, establishes the mathematical model with the minimum sum of the sensing radius of each sensors, and uses the genetic algorithm to solve the model to get the optimal coverage solution. In the optimal coverage deployment, the communication and channel allocation are further studied. Then the energy consumption model of the coverage scheme is built to analyze the performance of the scheme. Finally, the scheme is simulated through the network simulator NS-2. The results show the scheme can not only save 36% energy averagely, but also achieve 99.8% coverage rate under the condition of 45 sensors being deployed after 80 iterations. Besides, the scheme can reduce the five times interference among channels.     

无线传感网中移动式蠕虫的抑制与清理

在无线传感器网络(Wireless Sensor Networks, WSNs)中引入移动节点可以极大地提升网络性能。然而,移动节点一旦被蠕虫感染则会大大加快蠕虫在WSNs中的传播。针对这一新的研究问题,该文分2步来抑制和清理移动蠕虫传播源。首先建立了移动蠕虫感染模型,设计启发式算法以确定移动感染区域的边界,通过挂起感染边界附近的高风险节点来阻断蠕虫的进一步传播。第2步设计定向扩散的良性蠕虫对网络中被感染的节点进行修复,以彻底清除蠕虫病毒。理论分析和仿真实验结果均表明,该文所提方法能够在付出较小的代价下达到较好的移动蠕虫清理效果,适合能量受限的无线传感器网络。     

基于压缩感知的无线传感器网络多目标定位算法

目标定位是无线传感器网络的重要应用场景。该文提出了一种将压缩感知应用于无线传感器网络多目标定位的方法,把基于网格的多目标定位问题转化为压缩感知问题。应用多分辨率分析的思想,设计了迭代回溯的压缩感知算法,该方法的特点是可同时进行多目标定位,并且大大减少了网络通信的数据量从而延长网络寿命,代价是融合中心的算法复杂度的增加。仿真结果显示,采用迭代回溯算法定位精度提高了50%以上,具有较好的多目标定位效果。     

无线传感器网络路径覆盖问题研究

目标跟踪是无线传感器网络的重要应用之一。在目标跟踪过程中,用户通常更关心目标移动路径的覆盖情况,而不是整个网络部署区域的覆盖情况。学术界对路径1覆盖的问题做了详细的研究,但是并没有给出路径k(k1)覆盖的分析。针对这一问题,该文首先将节点随机布设的2维传感器网络中目标移动路径的覆盖问题转化为1维线段覆盖问题,并通过理论分析给出任意直线路径满足k(k1)覆盖的概率下限。实验表明,在k较小时,该下限可以较好的逼近仿真结果。     

Defense against collusion scheme based on elliptic curve cryptography for wireless sensor networks

Wireless Sensor Networks (WSNs) are being deployed for a wide variety of applications and the security problems of them have received considerable attention. Considering the limitations of power, com-putation capability and storage resources, this paper proposed an efficient defense against collusion scheme based on elliptic curve cryptography for wireless sensor networks in order to solve the problems that sensor node-key leaking and adversaries make compromised nodes as their collusions to launch new attack. In the proposed scheme, the group-key distribution strategy is employed to compute the private key of each sensor node, and the encryption and decryption algorithms are constructed based on Elliptic Curve Cryptography (ECC). The command center (node) only needs to broadcast a controlling header with three group elements, and the authorized sensor node can correctly recover the session key and use it to decrypt the broadcasting message. Analysis and proof of the proposed scheme’s efficiency and security show that the proposed scheme can resist the k-collusion attack efficiently.     

无线传感器网络中基于有限反馈的协同MIMO策略

该文针对无线传感器网络中能量有限问题,提出了一种基于有限反馈的协同MIMO策略。该策略基于梯度算法,用1bit反馈来自动地调整簇头节点和协同簇头节点的发射功率。对无线传感器网络中基于有限反馈的Alamouti码的协同MISO系统的误码率进行了理论分析,推导了基于有限反馈Alamouti码的协同MISO策略能耗的契尔诺夫上限表达式。理论分析和仿真结果都表明,该文提出的协同MISO策略与基于标准Alamouti码的协同策略相比,无线传感器网络的总能耗更低,能效更高,且当簇头节点和协同簇头节点一直选择较好信道对应的节点来发送信息时,即最优策略,无线传感器网络的总能耗更低。     

无线多媒体传感器网络中的动态频谱分配技术研究

无线多媒体传感器网络(WMSNs)具有实时监控,收集和处理多媒体信息的功能,有广泛的应用前景。较之传统无线传感器网络,WMSNs无线传输多媒体信息需要更大带宽。然而,随着无线通信设备的广泛应用,有限的可用频谱资源日益匮乏。利用动态频谱分配技术,可以扩展WMSNs的通信频段,增强抗干扰能力。考虑到WMSNs节点的物理限制,如计算能力和能量供应,该文提出了适合WMSNs的频谱感知方法和频谱管理方法。频谱感知采用各节点的轮换机制感知整个频段;频谱管理可以确保对授权用户影响最小的信道被首先使用。WMSNs使用上述方法可以感知周围无线电环境,利用空闲私有频段进行无线通信。最后,通过实验证明了该文提出的动态频谱分配技术对WMSNs的有效性。     

A local dynamic cluster self-organization algorithm in wireless sensor networks for rainfall monitoring

Wireless Sensor Networks for Rainfall Monitoring (RM-WSNs) is a sensor network for the large-scale regional and moving rainfall monitoring, which could be controlled deployment. Delivery delay and cross-cluster calculation leads to information inaccuracy by the existing dynamic collaborative self-organization algorithm in WSNs. In this letter, a Local Dynamic Cluster Self-organization algorithm (LDCS) is proposed for the large-scale regional and moving target monitoring in RM-WSNs. The algorithm utilizes the resource-rich node in WSNs as the cluster head, which processes target information obtained by sensor nodes in cluster. The cluster head shifts with the target moving in chance and re-groups a new cluster. The target information acquisition is limited in the dynamic cluster, which can reduce information across-clusters transfer delay and improve the real-time of information acquisition. The simulation results show that, LDCS can not only relieve the problem of “too frequent leader switches” in IDSQ, also make full use of the history monitoring information of target and continuous monitoring of sensor nodes that failed in DCS.