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Overlay Partition: Iterative Detection and Proactive Recovery

Overlay Partition: Iterative Detection and Proactive Recover...

引用

IEEE International Conference on Communications (ICC)

作者： T. Qiu E. Chan G. Chen Department of Computer Science City University of Hong Kong Hong Kong China State Key Laboratory for Novel Software Technology Nanjing University China

Overlay networks provide infrastructures for a large variety of Internet applications, like file sharing, online gaming, and multimedia streaming. However, these networks often face unexpected node failures and network disconnections, causing the overlay to be partitioned into several components, which may seriously affect the performance of the network. In this paper, we analyze the cause of overplay partitions and its impact on the efficiency of the system. After explaining the notion of half-life , a measurement used to describe the evolution of peers in overlay network, we propose a new construct called half-success as a measure of critical partition. Furthermore, we propose an iterative method for the detection of potential partitions and a proactive strategy for the prevention of such partitions. Simulation experiments show that our detection method can efficiently find almost all of the cut vertices at a low cost. In addition, we demonstrate that the proposed proactive scheme is more effective and much faster than reactive approaches.

关键词： Peer to peer computing IP networks Application software Streaming media Iterative methods Communications Society Laboratories computer science Costs Web and internet services

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Cache Invalidation Strategies for Mobile Ad Hoc Networks

Cache Invalidation Strategies for Mobile Ad Hoc Networks

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International Conference on Parallel Processing (ICPP)

作者： Wenzhong Li Edward Chan Yilin Wang Daoxu Chen Department of Computer Science City University of Hong Kong Kowloon Hong Kong China State Key Laboratory for Novel Software Technology Nanjing University China

Cache invalidation is an important issue in mobile caching and has received much attention by researchers. However most existing studies on cache invalidation strategies are limited to cellular wireless networks in which the mobile terminals can communicate with the base stations directly. In this paper, we address the seldom studied issue of cache invalidation in mobile ad hoc networks (MANETs), where the use of multi-hop communications poses serious challenges. We propose three cache invalidation strategies for MANETs. The three methods, namely pull on demand (POD), modified amnesic terminals (MAT) and pull-based amnesic terminals (PAT) are adapted from Barbara and Imielinski's classic cache invalidation schemes to handle the special requirements of MANETs. Both analytical results as well as simulation experiments are used to examine the performance of these three schemes, and it is shown that PAT provides the best overall performance.

关键词： Mobile ad hoc networks Broadcasting Mobile computing Analytical models Performance analysis Base stations Spread spectrum communication Mobile communication Computational modeling Delay

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An Online Semi-supervised Active Learning Algorithm with Self-organiing Incremental Neural Network

An Online Semi-supervised Active Learning Algorithm with Sel...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Shen Furao Keisuke Sakurai Youki Kamiya Osamu Hasegawa Japan Society for the Promotion of Science Japan State Key Laboratory for Novel Software Technology Nanjing University Nanjing China Department of Computer Intelligence and System Science Tokyo Institute of Technology Japan Imaging Science and Engineering Laboratory Tokyo Institute of Technology Japan

An online semi-supervised active learning algorithm is proposed, which is based on self-organizing incremental neural network (SOINN). The proposed method do not need any priori knowledge such as number of nodes or number of classes; it can automatically learn number of nodes and teacher vectors needed by the current task; It can realize online incremental learning even life-long learning. The experiments for artificial data and real world data show that the proposed method works efficiently.

关键词： Neural networks Learning systems Semisupervised learning Topology Training data Laboratories Artificial neural networks Supervised learning Costs Labeling

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Feature selection and partial least squares based dimension reduction for tumor classification

Feature selection and partial least squares based dimension ...

引用

7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

作者： Bu, Hua-Long Li, Guo-Zheng Zeng, Xue-Qiang Yang, Jack Y. Yang, Mary Qu School of Computer Engineering and Science Shanghai University Shanghai 200072 China State Key Laboratory for Novel Software Technology Nanjing University Nanjing 210093 China Harvard Medical School Harvard University Cambridge MA 02140 United States U.S. Department of Health and Human Services Bethesda MD 20852 United States

ISBN: (纸本)1424415098

Partial Least Squares (PLS) is one of the widely used dimension reduction methods for analysis of gene expression microarray data, it represents the data in a low dimensional space through linear transformation, the size of the reduced space by PLS is critical to generalization performance of classifiers. The previous works always determined the top fixed number of components or the top several components by cross-validation. Here we demonstrate the usage of feature selection for PLS based dimension reduction. As a case study, PLS is combined with two feature selection methods (Genetic Algorithm and Sequential Backward Floating Selection) to get more robust and efficient dimensional space, and then the constructed data from the selected components is used as input for the Support Vector Machine (SVM) classifier. We use the method for tumor classification on gene microarray data, experimental results illustrate that our proposed framework is effective both to reduce classification error rates and get compact dimensional space. ©2007 IEEE.

关键词： Linear transformations

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Support vector regression with feature selection for the multivariate calibration of spectrofluorimetric determination of aromatic amino acids

Support vector regression with feature selection for the mul...

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7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

作者： Li, Guo-Zheng Meng, Hao-Hua Yang, Mary Qu Yang, Jack Y. State Key Laboratory for Novel Software Technology Nanjing University Nanjing 210093 China School of Computer Science and Engineering Shanghai University Shanghai 200072 China U.S. Department of Health and Human Services Bethesda MD 20852 United States Harvard Medical School Harvard University Cambridge MA 02140 United States

ISBN: (纸本)1424415098

Several artificial intelligent methods, including Support Vector Regression (SVR), Artificial Neural Networks (ANNs), and Partial Least Square (PLS) are used for the multivariate calibration in the determination of the three aromatic amino acids (phenylalanine, tyrosine and tryptophan) in their mixtures by fluorescence spectroscopy. The results of the leave-one-out method show that SVR perform better than other methods, and appear to be good methods for this task. Furthermore, feature selection is performed for SVR to remove redundant features and a novel algorithm named PRIFER (Prediction RIsk based FEature selection for support vector Regression) is proposed. Results on the above multivariate calibration data set show that PRIFER is a powerful tool for solving the multivariate calibration problems. ©2007 IEEE.

关键词： Amino acids

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Secure Hop-Count Based Localization in Wireless Sensor Networks

Secure Hop-Count Based Localization in Wireless Sensor Netwo...

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International Conference on Computational Intelligence and Security

作者： Yingpei Zeng Shigeng Zhang Shanqing Guo Xie Li State Key Laboratory of Novel Software Technology Nanjing University Nanjing P.R. China School of Computer Science and Technology Shandong University Jinan P.R. China

Many sensor network applications rely on sensors' location information. However, most of existing location algorithms assume a non-adversarial environment or assume beacons lying within 1-hop. In this paper, we fo- cus on Hop-Count based localization (multihop) and de- velop a Secure HOp-Count based LOCalization scheme, called SHOLOC, to make localization attack-resistant. In SHOLOC, we assume both ordinary nodes and bea- con nodes can be moving, and the whole network period- ically restarts localization. SHOLOC proposes a proto- col to authenticate beacon information and protect hop- count from being arbitrary changed. SHOLOC employs beacon nodes to detect wormhole attacks. Theoretical analysis and simulation results are presented. Our con- clusion also includes two interest findings: 1)hop-count increment attacks are not effective to Hop-Count based algorithms, 2)filter mechanisms such as least median squares (LMS) are not resistant to wormhole attacks, and our method of detecting at beacon nodes side works well.

关键词： Wireless sensor networks Analytical models Information security Intelligent sensors Protocols Protection Least squares approximation Computational intelligence Laboratories Application software

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Feature selection for co-training: A QSAR study

Feature selection for co-training: A QSAR study

引用

2007 International Conference on Artificial Intelligence, ICAI 2007

作者： Li, Guo-Zheng Li, Dan Lu, Wen-Cong Yang, Mary Q. Yang, Jack Y. School of Computer Science and Engineering Shanghai University Shanghai 200072 China State Key Laboratory for Novel Software Technology Nanjing University Nanjing 210093 China Department of Chemistry School of Science Shanghai University Shanghai 200444 China U.S. Department of Health and Human Services Bethesda MD 20852 United States Harvard Medical School Harvard University Cambridge MA 02140 United States

ISBN: (纸本)9781601320254

Activities of drug molecules can be predicted by QSAR (quantitative structure activity relationship) models, which overcomes the disadvantages of high cost and long cycle by employing the traditional experimental method. With the fact that the number of drug molecules with known activity is less than that of unknown, it is important to predict molecular activities utilizing unlabeled instances. Here, semi-supervised learning (SSL) is introduced and a SSL method, Co-Training is investigated on predicting drug activities utilizing unlabeled instances. At the same time, the numerous features extracted from the structures of drug molecules affect prediction accuracy of QSAR models. Therefore, a novel algorithm named FESCOT is proposed, which applies an embedded feature selection method to remove redundant and irrelevant features for Co-Training. Numerical experimental results on a data set of molecular activities show that Co-Training improves prediction accuracy of molecular activities with unlabeled instances, and feature selection furthermore helps to improve the prediction ability of Co-Training.

关键词： Feature Selection

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UMP-PerComp: A Ubiquitous Multiprocessor Network-Based Pipeline Processing Framework for Pervasive Computing Environments

UMP-PerComp: A Ubiquitous Multiprocessor Network-Based Pipel...

引用

International Conference on Advanced Information Networking and Applications (AINA)

作者： M. Kubo Baoliu Ye A. Shinozaki T. Nakatomi Minyi Guo Future Creation Laboratory Olympus Corporation Shinjuku Tokyo Japan Department of Computer Software University of Aizu Fukushima Japan State Key Laboratory for Novel Software and Technology Nanjing University Nanjing China

Pervasive computing provides an attractive vision for the future of computing where contextual intelligent services will be available anywhere at any time. However, how to integrate distributed resources existed among heterogeneous devices to build pervasive applications that can constantly adapt to the highly dynamic computing environment is still a challenge. By analyzing the pipelining feature within a user task and exploiting the parallelism among ubiquitous processors, we propose UMP-PerComp, a ubiquitous multiprocessor-based pipeline processing architecture to support high performance pervasive application development. UMP-PerComp is an integrated comprehensive framework that makes the development of pervasive applications easier. It includes a set of common services such as context management, resource management, service migration, topology management, that help to build applications and directly simplify the task decoupling and service composition. We describe the design and implementation of UMP-PerComp in this paper. Besides, we develop a distributed JPEG encoding application successfully on the UMP-PerComp. Our experience confirms that UMP-PerComp is a flexible, scalable and practicable framework with high performance.

关键词： Pipeline processing Pervasive computing Resource management Context-aware services computer vision Distributed computing Performance analysis Parallel processing computer architecture Topology

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ANT COLONY OPTIMIZATION METHODFOR MULTIPLE SEQUENCE ALIGNMENT

ANT COLONY OPTIMIZATION METHODFOR MULTIPLE SEQUENCE ALIGNMEN...

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2007 International Conference on Machine Learning and Cybernetics(IEEE第六届机器学习与控制论国际会议)

作者： LING CHEN WEI LIU JUAN CHEN Department of Computer Science Yangzhou University Yangzhou China State Key Lab of Novel Software Department of Computer Science Yangzhou University Yangzhou China Yangzhou Institute of Electronic Technology Yangzhou China

Among all the methods for multiple sequence alignment, progressive alignment is the most popular technique because of its simplicity and *** main drawback of progressive alignment is that the errors occurring in early stages can not be corrected in later *** this paper, we propose a novel algorithm called ProAnt which combines ant colony optimization and progressive alignment to improve the accuracy of alignment To avoid the errors occurring in the early stage, the algorithm first calculates the posterior probability of all pairs of characters using ant colony optimization and probabilistic consistency *** the algorithm computes the final alignment using progressive method where the matching score of character pair is replaced by their posterior *** results on data from the BAliBASE database show that our algorithm can obtain much more accurate results and higher speed than the other progressive alignment method.

关键词： Bioinformatics Ant colony optimization Multiple sequences alignment

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An Energy-Aware Protocol for Data Gathering Applications in Wireless Sensor Networks

An Energy-Aware Protocol for Data Gathering Applications in ...

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IEEE International Conference on Communications (ICC)

作者： M. Liu Y. Zheng J. Cao G. Chen L. Chen H. Gong School of Computer Science and Engineering University of Electronic Science and Technology China Internet and Mobile Computing Lab Department of Computing Hong Kong Polytechnic University Hong Kong China State Key Laboratory for Novel Software Technology Nanjing University China

Data gathering is a major function of many applications in wireless sensor networks (WSNs). The most important issue in designing a data gathering algorithm is how to save energy of sensor nodes while meeting the requirement of applications/users such as sensing area coverage. In this paper, we propose a novel hierarchical clustering protocol for long-lived sensor network. EAP achieves a good performance in terms of lifetime by minimizing energy consumption for in-network communications and balancing the energy load among all nodes. EAP introduces a new clustering parameter for cluster head election, which can better handle the heterogeneous energy capacities. Furthermore, it also introduces a simple but efficient approach, namely intra-cluster coverage to cope with the area coverage problem. We evaluate the performance of the proposed protocol using a simple temperature sensing application. Simulation results show that our protocol significantly outperforms LEACH and HEED in terms of network lifetime and the amount of data gathered.

关键词： Wireless application protocol Wireless sensor networks Energy consumption Application software Temperature sensors computer networks Clustering algorithms Peer to peer computing Scalability Paper technology

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