WSN中一种最优的汇聚节点移动方案

研究了无线传感器网络中,如何在不同的候选位置放置数据汇聚节点来最大化网络生命周期。通过定义＂放置模式＂这一概念,对数据流通模式进行分类,从而从量级上降低了需要调度的因素的数目。基于这样的理念,对问题建立了线性优化模型,来构建一种最佳的放置策略。最后,通过具体的试验验证了提出方法的有效性,说明了即使使用一个移动位置受限的汇聚节点,也会极大地提升网络生命周期。     

圆片级封装的凸点制作技术

圆片级封装是一种先进的电子封装技术,近年来,圆片级封装技术的发展速度很快,主要应用于系统级芯片、光电器件和MEMS等.凸点制作是圆片级封装工艺的关键工序,目前凸点制作工艺方法有多种,重点介绍常用的电镀法、植球法和蒸发沉积法凸点工艺,分别介绍这三种凸点制作技术的工艺流程、关键技术.     

基于网格点覆盖模型的高效传感器网络节点配置算法

节点配置问题是传感器网络研究的关键问题.在DhillonS.S.的模型化方法基础上,完成了两种改进的高效节点配置算法.以最少化传感器数目为目标,通过减少局部冗余、优化整体性能以及考虑传感器检测范围的有限性,修改算法的初始化模型等方法,对现有的传感器节点配置算法进行了改进.通过仿真分析,充分验证了两种模型的可行性与性能的优越性.     

基于覆盖网络的应用层选播服务的设计与研究

针对网络层的选播通信存在着可扩展性和无状态服务等根本问题,在现有的应用层选播研究基础上,提出了一种基于覆盖网络的应用层选播的结构,并把这种结构从代理节点的部署和链路的选取上进行求解,并通过实验对此拓扑结构进行了验证.     

贴片机X/Y轴快速高精度定位的实现

负载惯量和外界干扰是影响贴片机X,Y轴快速高精度定位的两个关键因素。本文针对负载惯量和外界干扰对控制性能的影响,提出了基于RBF神经网络的自适应滑模控制算法。利用RBF神经网络的万能逼近特性实现对外加干扰和被控对象模型信息的逼近,运用自适应控制算法计算前馈补偿量以补偿负载惯量和摩擦力对运动性能的影响,采用滑模控制算法以抑制其他不确定干扰对运动控制的影响。通过仿真分析可以得出,所采用的控制算法能够有效地补偿负载惯量和外界干扰对定位性能的影响,从而实现贴片机X,Y轴的快速高精度定位。     

软件定义网络中可靠性优化控制器的位置研究(英)

By decoupling control plane and data plane,Software-Defined Networking(SDN) approach simplifies network management and speeds up network innovations.These benefits have led not only to prototypes,but also real SDN deployments.For wide-area SDN deployments,multiple controllers are often required,and the placement of these controllers becomes a particularly important task in the SDN context.This paper studies the problem of placing controllers in SDNs,so as to maximize the reliability of SDN control networks.We present a novel metric,called expected percentage of control path loss,to characterize the reliability of SDN control networks.We formulate the reliability-aware control placement problem,prove its NP-hardness,and examine several placement algorithms that can solve this problem.Through extensive simulations using real topologies,we show how the number of controllers and their placement influence the reliability of SDN control networks.Besides,we also found that,through strategic controller placement,the reliability of SDN control networks can be significantly improved without introducing unacceptable switch-to-controller latencies.     

MEMS压力传感器上柔性化凸点制备方法

介绍了一种适用于MEMS压力传感器的低成本、柔性化凸点下金属层(Under Bump Metal,UBM)和凸点(Bump)的制备工艺。其中凸点下金属层分为Ni-P/Cu两层,使用化学镀的方法沉积在Al焊盘表面;凸点通过焊膏印刷回流预制于陶瓷基片上,再通过转移工艺移植到焊盘上。为了检验此套工艺制出的凸点结构是否具有足够的强度,对凸点进行了剪切破坏试验。结果表明,凸点与凸点下金属层、凸点下金属层与Al焊盘均结合牢固,破坏主要发生在焊料凸点内最薄弱的金属间化合物层(Intermetallic Compound,IMC)。     

基于 VPR的 FPGA 布局算法的改进

通过在原模拟退火算法中加入回火过程对原算法进行优化,同时,减小内循环次数用于弥补回火导致的布局时间增量。回火过程用于寻找“被遗漏”的最优解。结果表明新算法利于跳出局部最优“陷阱”,进一步搜索最优解,具体体现在改进后的算法不但能够保证布局质量,而且缩减了布局时间,同时,布线时间与电路关键路径延时得到不同程度的改善。     

深亚微米SOI工艺SoC设计中天线效应的消除

深亚微米SOI片上系统芯片(SoC)因其工艺特性,按照常规的布局布线(PNR)流程,出现了约一万个天线效应违规。介绍了一种在布局布线阶段不插入反偏二极管就可以消除大量天线效应违规的优化迭代流程。通过对天线效应的产生以及天线比率公式的分析,从线长和栅面积角度考虑天线效应的修复,结合自动布局布线设计工具SoC Encounter对这些因素的控制,可以在布局布线阶段消除天线效应的违规,并能与版图验证的结果保持一致。在一款通用抗辐照SoC芯片的设计中,应用该优化流程在布局布线阶段消除了设计中的天线效应违规,有效节约了芯片整体设计时间。     

Algorithm design for a class of base station location problems in sensor networks

Base station placement has significant impact on sensor network performance. Despite its significance, results on this problem remain limited, particularly theoretical results that can provide performance guarantee. This paper proposes a set of procedure to design (1− ε) approximation algorithms for base station placement problems under any desired small error bound ε > 0. It offers a general framework to transform infinite search space to a finite-element search space with performance guarantee. We apply this procedure to solve two practical problems. In the first problem where the objective is to maximize network lifetime, an approximation algorithm designed through this procedure offers 1/ε² complexity reduction when compared to a state-of-the-art algorithm. This represents the best known result to this problem. In the second problem, we apply the design procedure to address base station placement problem when the optimization objective is to maximize network capacity. Our (1− ε) approximation algorithm is the first theoretical result on this problem. 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. His current research focuses on algorithms and optimizations for wireless sensor networks, wireless ad hoc networks, UWB-based networks, and SDR-based networks. His work has appeared in journals and highly selective international conferences (ACM Mobicom, ACM Mobihoc, and IEEE Infocom). Y. Thomas Hou received the 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. Since Fall 2002, he has been an Assistant Professor at Virginia Tech, the Bradley Department of Electrical and Computer Engineering, Blacksburg, VA. His current research interests are radio resource (spectrum) management and networking for software-defined radio wireless networks, optimization and algorithm design for wireless ad hoc and sensor networks, and video communications over dynamic ad hoc networks. From 1997 to 2002, Dr. Hou was a Researcher at Fujitsu Laboratories of America, Sunnyvale, CA, where he worked on scalable architectures, protocols, and implementations for differentiated services Internet, service overlay networking, video streaming, and network bandwidth allocation policies and distributed flow control algorithms. Prof. Hou is a recipient of an Office of Naval Research (ONR) Young Investigator Award (2003) and a National Science Foundation (NSF) CAREER Award (2004). He is a Co-Chair of Technical Program Committee of the Second International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CROWNCOM 2007), Orlando, FL, August 1–3, 2007. He also was the Chair of the First IEEE Workshop on Networking Technologies for Software Defined Radio Networks, September 25, 2006, Reston, VA. Prof. Hou holds two U.S. patents and has three more pending. Alon Efrat earned his Bachelor in Applied Mathematics from the Technion (Israel’s Institute of Technology) in 1991, his Master in Computer Science from the Technion in 1993, and his Ph.D in Computer Science from Tel-Aviv University in 1998. During 1998–2000 he was a Post Doctorate Research Associate at the Computer Science Department of Stanford University, and at IBM Almaden Research Center. Since 2000, he is an assistant professor at the Computer Science Department of the University of Arizona. His main research areas are Computational Geometry, and its applications to sensor networks and medical imaging.