Characterizing pairwise contact patterns in human contact networks

We use a counting process representation of the pairwise contact process to analyze pairwise contact patterns. Studying two real-world traces, we find that the pairwise contact patterns have three characteristics. First, human contact patterns are influenced by daily and weekly cycles of activity. Second short time intervals with intensive contact event (bursts) are separated by long periods with few contact events. Third, the pairwise contact process exhibits long range dependence. We introduce a Markov modulated Poisson process (MMPP) as a flexible model for pairwise contact process exhibiting both regular structure and irregular bursts of activity. Using standard statistical techniques, we demonstrate that the proposed model is consistent with the empirical data. Our work has significant implication for mobility modeling and performance analysis in human contact networks.     

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.     

Performance of adaptive token allocation in the leaky bucket

The leaky bucket is a popular method that can regulate traffic into an ATM broadband network. This paper examines a simple but innovative modification that would also provide priority to access the network. This is done by requiring cells of different classes to obtain different numbers of tokens before receiving their services. As a step further, a dynamic scheme can be used in which the tokens allocated to each class are changed according to the traffic load. Performance evaluations of mean cell delays and cell loss probabilities are obtained to provide insight into the behaviour of the system and to provide guideline for furture design.     

Integrated Services over ATM/MAN-Based Personal Communication Networks

IEEE 802.6 metropolitan area networks (MANs) providean efficient architecture for supporting wirelesspersonal communication services (PCSs) overmetropolitan areas by interconnecting wireless basestations into personal communication networks (PCNs).They also serve as peripheral gathering networks totransport PCS traffic over a wide area broadbandintegrated services digital network employingasynchronous transfer mode (ATM), enabling integrationof PCNs in different cities into a global PCN. Bycombining the various access methods and employing adynamic bandwidth integration scheme, a MAN canfunction as a powerful distributed switch forintegrating different types of local traffic.Simulation results are presented to illustrate theadvantages of the integration scheme. To provideubiquitous PCS, we also propose a simplesuffix-dialing method for integrating telephone, fax,paging and email services over the ATM/MAN-based PCNsusing a single personal telecommunication number. Withthis method, the current practice of printing a longlist of phone numbers on one's business card will nolonger be necessary.     

业务分离的一种神经网络方法

在分组交换网络中,源目节点对（ｓｏｕｒｃｅ－ｄｅｓｔｉｎａｔｉｏｎ ｐａｉｒ,下称ＳＤ对）之间的业务常常需要在多条路径上并行传输。本文研究如何将业务流有效地分布于一组路径上,以使网络具有最小的分组平均时延。由于这个问题在很多情况下需要实时处理,因此我们提出了一种神经网络方法来加以解决,在一个典型网络上的试验表明,我们的方法获得的结果优于前人用各种严格的数学分析方法得到的好的结果。     

ATM上的多协议规范技术与实现

ATM上的多协议规范（MPOA,MultinleProtocolOverATM）是最新的ATM和以太网络间的互联技术,它提供快速的3层交换性能,并支持服务质量（QoS）,适合于构建大型园区和企业网络。首先比较详细地介绍了MPOA的技术原理、工作机制,然后对其工作过程进行了分析。     

基于PNNI递阶拓扑结构的VP网络规划

ＡＴＭ网络中的ＶＰ层网络规划在大规模网络情形下求解会发生困难,文章借鉴了ＰＮＮＩ网络递阶结构,设计了一种分级规划方法,有效地解决了大规模ＡＴＭ网络ＶＰ层规划问题,并用进化规划对规划问题进行了求解。文中给出了数值算例。     

ATM网络中综合连接接纳控制与路由选择的模糊决策策略

本文提出了一种新的模糊决策策略,用于综合考虑连续接纳控制和路由选择,以求在ＡＴＭ网络中增加整个网络的吞吐量和降低信元丢失率与呼损率。文章中详细阐述了该模糊决策系统的原理,并给出了一种自适应调节系统参数的方法。仿真结果说明利用神经网络能够成功地实现此模糊系统。     

ATM交叉连接的性能优势

本文通过分析ＡＴＭ的特点和原理及对ＡＴＭ交叉连接与传统的交叉连接的比较,讨论了ＡＴＭ交叉连接的性能特点和优势。