Interaction of ISPs: Distributed Resource Allocation and Revenue Maximization

The Internet is a hierarchical architecture comprising heterogeneous entities of privately owned infrastructures, where higher level Internet service providers (ISPs) supply connectivity to the local ISPs and charge the local ISPs for the transit services. One of the challenging problems facing service providers today is how the profitability can be increased while maintaining good service qualities as the network scales up. In this work, we seek to understand the fundamental issues on the "interplay" (or interaction) between ISPs at different tiers. Although the local ISPs (which we term peers) can communicate with each other by purchasing the connectivity from transit ISPs, there stands an opportunity for them to set up private peering relationships. Under this competitive framework, we explore the issues on 1) the impact of peering relationship; 2) resource distribution; 3) revenue maximization; and 4) condition for network upgrade. First, a generalized model is presented to characterize the behaviors of peers and the transit ISP, in which their economic interests are reflected. We study how a peer can distributively determine its optimal peering strategy. Furthermore, we show how a transit ISP is able to utilize the available information to infer its optimal pricing strategy, under which a revenue maximization is achieved. Two distributed algorithms are proposed to help ISPs to provide a fair and efficient bandwidth allocation to peers, avoiding a resource monopolization of the market. Last, we investigate the above issues in a "many-peers region," that is, when we scale up the network. We provide insightful evidence to show that the ISPs can still gain profits as they upgrade the network infrastructures. Extensive simulations are carried out to support our theoretical claims.     

DocXS distributed operator construction and execution system

In the field of computer vision and pattern recognition, data processing and data analysis tasks are often implemented as a consecutive or parallel application of more-or-less complex operations. In the following we will present DocXS, a computing environment for the design and the distributed and parallel execution of such tasks. Algorithms can be programmed using an Eclipse-based user interface, and the resulting Matlab and Java operators can be visually connected to graphs representing complex data processing workflows. DocXS is platform independent due to its implementation in Java, is freely available for noncommercial research, and can be installed on standard office computers. One advantage of DocXS is that it automatically takes care about the task execution and does not require its users to care about code distribution or parallelization. Experiments with DocXS show that it scales very well with only a small overhead. The text was submitted by the authors in English. Steffen Wachenfeld received B.Sc. and M.Sc. (honors) degrees in Information Systems in 2003 and 2005 from the University of Muenster, Germany, and an M.Sc. (honors) degree in Computer Science in 2003 from the University of Muenster. He is currently a research fellow and PhD student in the Computer Science at the Dept. of Computer Science, University of Muenster. His research interests include low resolution text recognition, computer vision on mobile devices, and systems/system architectures for computer vision and image analysis. He is author or coauthor of more than ten scientific papers and a member of IAPR. Tobias Lohe, M.Sc. degree in Computer Science in 2007 from the University of Muenster, Germany, is currently a research associate and PhD student in Computer Science at the Institute for Robotics and Cognitive Systems, University of Luebeck, Germany. His research interests include medical imaging, signal processing, and robotics for minimally invasive surgery. Michael Fieseler is currently a student of Computer Science at the University of Muenster, Germany. He has participated in research in the field of computer vision and medical imaging. Currently he is working on his Master thesis on depth-based image rendering (DBIR). Xiaoyi Jiang studied Computer Science at Peking University, China, and received his PhD and Venia Docendi (Habilitation) degree in Computer Science from the University of Bern, Switzerland. In 2002 he became an associate professor at the Technical University of Berlin, Germany. Since October 2002 he has been a full professor at the University of Münster, Germany. He has coauthored and coedited two books published by Springer and has served as the co-guest-editor of two special issues in international journals. Currently, he is the Coeditor-in-Chief of the International Journal of Pattern Recognition and Artificial Intelligence. In addition he also serves on the editorial advisory board of the International Journal of Neural Systems and the editorial board of IEEE Transactions on Systems, Man, and Cybernetics—Part B, the International Journal of Image and Graphics, Electronic Letters on Computer Vision and Image Analysis, and Pattern Recognition. His research interests include medical image analysis, vision-based man-machine interface, 3D image analysis, structural pattern recognition, and mobile multimedia. He is a member of IEEE and a Fellow of IAPR.     

HBA: Distributed Metadata Management for Large Cluster-Based Storage Systems

An efficient and distributed scheme for file mapping or file lookup is critical in decentralizing metadata management within a group of metadata servers. This paper presents a novel technique called Hierarchical Bloom Filter Arrays (HBA) to map filenames to the metadata servers holding their metadata. Two levels of probabilistic arrays, namely, the Bloom filter arrays with different levels of accuracies, are used on each metadata server. One array, with lower accuracy and representing the distribution of the entire metadata, trades accuracy for significantly reduced memory overhead, whereas the other array, with higher accuracy, caches partial distribution information and exploits the temporal locality of file access patterns. Both arrays are replicated to all metadata servers to support fast local lookups. We evaluate HBA through extensive trace-driven simulations and implementation in Linux. Simulation results show our HBA design to be highly effective and efficient in improving the performance and scalability of file systems in clusters with 1,000 to 10,000 nodes (or superclusters) and with the amount of data in the petabyte scale or higher. Our implementation indicates that HBA can reduce the metadata operation time of a single-metadata-server architecture by a factor of up to 43.9 when the system is configured with 16 metadata servers.     

A Constrained Line Search Optimization Method for Discriminative Training of HMMs

In this paper, we propose a novel optimization algorithm called constrained line search (CLS) for discriminative training (DT) of Gaussian mixture continuous density hidden Markov model (CDHMM) in speech recognition. The CLS method is formulated under a general framework for optimizing any discriminative objective functions including maximum mutual information (MMI), minimum classification error (MCE), minimum phone error (MPE)/minimum word error (MWE), etc. In this method, discriminative training of HMM is first cast as a constrained optimization problem, where Kullback-Leibler divergence (KLD) between models is explicitly imposed as a constraint during optimization. Based upon the idea of line search, we show that a simple formula of HMM parameters can be found by constraining the KLD between HMM of two successive iterations in an quadratic form. The proposed CLS method can be applied to optimize all model parameters in Gaussian mixture CDHMMs, including means, covariances, and mixture weights. We have investigated the proposed CLS approach on several benchmark speech recognition databases, including TIDIGITS, Resource Management (RM), and Switchboard. Experimental results show that the new CLS optimization method consistently outperforms the conventional EBW method in both recognition performance and convergence behavior.     

A model reference robust control with application to a flight control system design

In this paper, a new model reference robust control scheme for plants with relative degree greater than one is proposed for the purpose of coping with the “explosion of complexity” problem in control law design. The key of the scheme is that we use a first‐order filter to link each subsystem, so that the derivative of some nonlinear functions can be avoided. As a result, the final control law can be greatly simplified. The application of this scheme to a flight control system shows that both the tracking performance and the control effort can be improved significantly in comparison with earlier research. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

图像匹配技术在套印误差自动检测中的应用

准确检测套印偏差是印刷机自动套印系统中最为关键的技术;针对印刷色标图案的特点,提出了一种新的基于图像匹配的套印误差检测方法,通过相关匹配处理获取各单色色标的位置,并巧妙利用色标圆线的直径确定了系统的标称分辨率,进而计算出各色组问纵向和横向的套印误差;文中详细给出了算法原理和实验结果;相对于经典的边缘检测方法,图像匹配技术充分利用了色标图案的整体信息;实验结果表明,该方法对像素灰度的变化和系统噪声具有鲁棒性,检测精度高。     

基于信息融合的管道泄漏检测与定位技术应用研究

基于目前已经在石油输送管道中应用的SCADA系统将信息融合技术应用于管道泄漏检测与定位系统中;该方法应用管道泄漏时的多种特征信号,采用最优加权融合算法将多元信息综合处理,扩展了时间和空间上的检测范围,提高了泄漏检测系统的灵敏度和可靠性;在实验室用水泵和不锈钢管道组成的水循环系统进行了模拟实验,通过对比验证了信息融合检漏方法比单一检漏方法具有明显的优越性。     

Combinatorial electrochemical cell array for high throughput screening of micro-fuel-cells and metal/air batteries

An electrochemical cell array was designed that contains a common air electrode and 16 microanodes for high throughput screening of both fuel cells (based on polymer electrolyte membrane) and metal/air batteries (based on liquid electrolyte). Electrode materials can easily be coated on the anodes of the electrochemical cell array and screened by switching a graphite probe from one cell to the others. The electrochemical cell array was used to study direct methanol fuel cells (DMFCs), including high throughput screening of electrode catalysts and determination of optimum operating conditions. For screening of DMFCs, there is about 6% relative standard deviation (percentage of standard deviation versus mean value) for discharge current from 10 to 20 mAcm(2). The electrochemical cell array was also used to study tin/air batteries. The effect of Cu content in the anode electrode on the discharge performance of the tin/air battery was investigated. The relative standard deviations for screening of metal/air battery (based on zinc/air) are 2.4%, 3.6%, and 5.1% for discharge current at 50, 100, and 150 mAcm(2), respectively.     

一种面向现场总线的时分同步MAC协议模型框架

现场总线是计算机网络技术向工业控制领域发展的必然结果,MAC子层协议是其网络协议的重要部分。本文提出一种时分同步多重访问（TSMA）协议,它以多频FSK技术为基础,实现总线无冲突访问。     

Three-dimensional QSAR of HPPD inhibitors, PSA inhibitors, and anxiolytic agents: effect of tautomerism on the CoMFA models

The present study was design to examine the effect of tautomerism upon the CoMFA results. Three selected data sets involving protropic tautomerism, which are 21 p-hydroxyphenylpyruvate dioxygenase (HPPD) inhibitors, 35 inhibitors of puromycin-sensitive aminopeptidase (PSA), and 67 anxiolytic agents, were used for this purpose. Atom-by-atom alignment technique was adopted to superimpose the molecules in the data sets onto a template. The structural alignments using different tautomeric forms had no significant difference except the atoms involved in tautomerism, which ensures, to a great extent, that the differences of the CoMFA results result primarily from the tautomerism. All-orientation and all-placement search (AOS-APS) based CoMFA models, in addition to the conventional ones, were derived for each system and proved to be capable of yielding much improved statistical results. In the cases of the data sets of HPPD inhibitors and PSA inhibitors, excellent AOS-APS CoMFA models (q2>0.8 with four components for the former and q2>0.7 with seven components for the latter) were obtained, and almost no significant difference in statistical quality was observed when using different tautomeric forms to derive the models. However, it was not the case when treating the data set of anxiolytic agents. The keto tautomer, which was the active form of the PBI type inhibitors, produced measurably better results (q2=0.54 with eight components) than that the enol one (q2=0.37 with five components), indicating the importance of selecting proper tautomer in the CoMFA studies. Furthermore, there existed some substantial differences of the electrostatic field contours between the two different tautomeric forms for all of the three systems considered, whereas the differences in the steric field contour maps were limited. This implies that the resulting new potent ligands may be quite different if one utilizes the CoMFA models of different tautomeric forms for guiding further structural refinements.