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.     

利用终点吸引子与正则化神经网络求解最小向量范数问题

本文结合终点吸引子与罚函数方法,构造了求解满足约束条件的最小向量范数问题的终点吸引子神经网络模型,所提出的方法克服了惩罚因子须取充分大的要求,使得网络易于收敛于稳定状态。利用正则化方法解决了求解向量范数极小化中的病态问题,从而得到了一个正则化神经网络。所有的网络均给出了电路结构图,我们的方法有利于ＶＬＳＩ实现及其实时求解。用具体例子进行了模拟实验,实验结果说明了方法的正确性与有效性。     

无线寻呼协议及网际通信

讨论了 5种主流寻呼体制的编码特色、传输内容、抗衰落误码、漫游能力、非基本业务、体制兼容性、升级过渡等技术性能 ,从发展角度分析了它们的应用状况。另外 ,还介绍了不同生产厂家寻呼终端之间组网、寻呼网与计算机之间的连接以及 Internet等业务通过无线设备传递方面的工业标准协议     

城市光纤CATV网络拓扑结构探讨

简要介绍光纤同轴电缆混合网（ＨＦＣ）的优势,分析ＨＦＣ网的几种拓扑结构及优缺点,并对城市ＨＦＣ网拓扑结构的工程实际进行了探讨。     

网上教学与测试系统开发设计

发展远程教是优化教育资源，实现高等教育大众化和构建终身教育的需求，而网上教学是现代远程教育的主要模式。深入研究了网上教学与测试系统的设计方法，并提出了一种基于Web客户／服务器（C／S）体系结构的系统模型。     

Interference power statistics in ad-hoc and sensor networks

There exist accurate calculation methods for estimation of interference power sum statistics in fixed-topology wireless networks based on the log-normal shadowing radio model. Here we publish essential additions to these estimation methods to expand their use to sensor networks and ad-hoc networks with changing topology. In our calculations we take into account radio propagation conditions, density of nodes, size of the network, traffic load per node and MAC protocol characteristics. The accuracy of our calculation method is verified by simulations. We highlight the influence of MAC protocols on interference and show that an increase in network size or in node density does not necessarily lead into higher interference values. Our results can be deployed to estimate the network capacity. Ramin Hekmat received M.Sc. degree in electrical engineering from Delft University of Technology (TU Delft) in the Netherlands in 1990. He worked since then for several telecommunication companies in the Netherlands and the United States in Research and Development as well as managerial positions. In September 2005 he obtained Ph.D. degree for his work related to Ad-hoc Networks form TU Delft. Currently he is working as assistant professor in the faculty of Electrical Engineering, Mathematics and Computer Science of TU Delft. His prime research interest includes multi-user communication systems, wireless communications and peer-to-peer networks. Email: r.hekmat@ewi.tudelft.nl Mailing address: Delft University of Technology Electrical Engineering, Mathematics and Computer Science P.O. Box 5031 2600 GA Delft The Netherlands. Piet Van Mieghem has obtained the Master and Ph. D. in Electrical Engineering from the K.U.Leuven (Belgium) in 1987 and 1991, respectively. He has joined the Interuniversity Micro Electronic Center (IMEC) from 1987-1991. He was a visiting scientist at MIT, department of electrical engineering from 1992-1993. From 1993 to 1998, he was working in Alcatel Corporate Research Center in Antwerp where he has gained experience in performance analysis of ATM systems and network architectural concepts of both ATM networks (PNNI) and the Internet. Currently, he is full professor at Delft University of Technology with a chair in telecommunication networks. The main theme of the research is evolution of the Internet architecture towards a broadband and QoS-aware network. Email: p.vanmieghem@ewi.tudelft.nl Mailing address: Delft University of Technology Electrical Engineering, Mathematics and Computer Science P.O. Box 5031 2600 GA Delft The Netherlands.     

一种城域网物理拓扑快速自动发现实现方法

根据城域网网管软件开发过程中的设计经验,本文阐述了一种基于路由接口地址空间和SNMP异步扫描的网络物理拓扑快速发现的方法,并在具体项目中予以实现和应用,解决了拓扑发现过程中面临的设备搜索的完整性、拓扑发现的速度和拓扑判定的准确性三个主要问题,并取得了良好的效果。     

基于互补分裂谐振环的零阶谐振微带带通滤波器的设计

文章介绍了以互补分裂谐振环和一系列沟道组成的LHM为单元的零阶谐振系统（ZOR）,并给出了此系统共振频率和导纳斜率参数的确定方法。描述了由带有J－变案频器的ZOR组成的带通滤波器的设计方法。     

An unequal cluster-based routing protocol in wireless sensor networks

Clustering provides an effective method for prolonging the lifetime of a wireless sensor network. Current clustering algorithms usually utilize two techniques; selecting cluster heads with more residual energy, and rotating cluster heads periodically to distribute the energy consumption among nodes in each cluster and extend the network lifetime. However, they rarely consider the hot spot problem in multihop sensor networks. When cluster heads cooperate with each other to forward their data to the base station, the cluster heads closer to the base station are burdened with heavier relay traffic and tend to die much faster, leaving areas of the network uncovered and causing network partitions. To mitigate the hot spot problem, we propose an Unequal Cluster-based Routing (UCR) protocol. It groups the nodes into clusters of unequal sizes. Cluster heads closer to the base station have smaller cluster sizes than those farther from the base station, thus they can preserve some energy for the inter-cluster data forwarding. A greedy geographic and energy-aware routing protocol is designed for the inter-cluster communication, which considers the tradeoff between the energy cost of relay paths and the residual energy of relay nodes. Simulation results show that UCR mitigates the hot spot problem and achieves an obvious improvement on the network lifetime. Guihai Chen obtained his B.S. degree from Nanjing University, M. Engineering from Southeast University, and PhD from University of Hong Kong. He visited Kyushu Institute of Technology, Japan in 1998 as a research fellow, and University of Queensland, Australia in 2000 as a visiting professor. During September 2001 to August 2003, he was a visiting professor at Wayne State University. He is now a full professor and deputy chair of Department of Computer Science, Nanjing University. Prof. Chen has published more than 100 papers in peer-reviewed journals and refereed conference proceedings in the areas of wireless sensor networks, high-performance computer architecture, peer-to-peer computing and performance evaluation. He has also served on technical program committees of numerous international conferences. He is a member of the IEEE Computer Society. Chengfa Li was born 1981 and obtained his Bachelor’s Degree in mathematics in 2003 and his Masters Degree in computer science in 2006, both from Nanjing University, China. He is now a system programmer at Lucent Technologies Nanjing Telecommunication Corporation. His research interests include wireless ad hoc and sensor networks. Mao Ye was born in 1981 and obtained his Bachelor’s Degree in computer science from Nanjing University, China, in 2004. He served as a research assistant At City University of Hong Kong from September 2005 to August 2006. He is now a PhD candidate with research interests in wireless networks, mobile computing, and distributed systems. Jie Wu is a professor in the Department of Computer Science and Engineering at Florida Atlantic University. He has published more than 300 papers in various journal and conference proceedings. His research interests are in the areas of mobile computing, routing protocols, fault-tolerant computing, and interconnection networks. Dr. Wu serves as an associate editor for the IEEE Transactions on Parallel and Distributed Systems and several other international journals. He served as an IEEE Computer Society Distinguished Visitor and is currently the chair of the IEEE Technical Committee on Distributed Processing (TCDP). He is a member of the ACM, a senior member of the IEEE, and a member of the IEEE Computer Society.     

浅谈网络信息背景下的银行人力资源管理

当前已经逐步成为信息化、网络化,各个银行之间的竞争主要体现在其核心能力的竞争。人力资源在银行竞争中具有重要的地位和作用,在银行竞争优势中也是一种难以模仿的特定资源,是保持银行竞争优势的源泉,更是决定银行在信息化社会中竞争成败与否的关键因素。本文以网络信息时代下人力资源管理理论为基础分析我国现阶段银行人力资源管理的特点和所存在的一些问题,并针对这些问题提出对策建议,以提高人力资源管理效率,推进我国银行的发展。