1,241 research outputs found
Accurate Heavy Tail Distribution Approximation For Multifractal Network Traffic
No full textIn this paper, we propose the use of a Gaussian mixture model to represent the heavy tail distribution of modern network traffic traces. Another novel contribution of this work is the derivation of a general expression for loss probability estimation in a single server queueing system for traffic traces with multifractal characteristics. The efficiency of this statistical modeling and the accuracy of the estimated loss probabilities are experimentally validated by comparing with other four multifractal based approaches: two of them considering two specific heavy tail distributions (lognormal, Pareto) and the well-known MSQ (Multiscale Queue) and CDTSQ (Critical Dyadic Time-Scale Queue) methods.45317Leland, W., Taqqu, M., Willinger, W., Wilson, D., On The Self-Similar Nature of Ethernet Traffic (1994) IEEE/ACM Transactions on Networking, 2 (1), pp. 1-15. , extended version FebNorros, I., A Storage Model with Self-Similar Input (1994) Queueing, 16, pp. 387-396Park, K., Willinger, W., (2000) Self-Similar Network Traffic and Performance Evaluation, , John Wiley and Sons New YorkRiedi, R.H., Crouse, M.S., Ribeiro, V.J., Baraniuk, R.G., A Multifractal Wavelet Model with Application to Network Traffic (1999) IEEE Transactions on Information Theory. (Special Issue on Multiscale Signal Analysis and Modeling), 45, pp. 992-1018. , AprilVieira, F.H.T., Lee, L.L., Adaptive Wavelet Based Multifractal Model Applied to the Effective Bandwidth Estimation of Network Traffic Flows (2009) IET Communications, pp. 906-919. , JuneKrishna, P.M., Gadre, V.M., Desai, U.B., (2003) Multifractal Based Network Traffic Modeling, , Kluwer Academic Publishers, Boston, MAPeltier, R., Véhel, J.L., (1995) Multifractional Brownian Motion: Definition and Preliminary Results, , Technical Report 2695, INRIAVieira, F.H.T., Bianchi, G.R., Lee, L.L., A Network Traffic Prediction Approach Based on Multifractal Modeling (2010) J. High Speed Netw, 17 (2), pp. 83-96McLachlan, G., (1988) Mixture Models, , Marcel Dekker, New York, NYMartinez, W.L., Martinez, A.R., (2008) Computational Statistics Handbook with Matlab, , Chapman & Hall/CRC, Boca Raton, FloridaFisher, A., Calvet, L., Mandelbrot, B.B., (1997) Multifractality of Deutschmark/US Dollar Exchanges Rates, , Yale UniversitySeuret, S., Gilbert, A.C., Pointwise Hölder Exponent Estimation in Data Network Traffic ITC Specialist Semina, Monterey, 2000Stenico, J.W.G., Lee, L.L., Modelagem de Processos Multifractais Baseada em uma Nova Cascata Conservativa Multiplicativa (2011) XXIX Simpósio Brasileiro de Telecomunicações - SBRT 11, 1, pp. 1-6. , 10/2011, Curitiba, PR, BrasilStenico, J.W.G., Lee, L.L., A New Binomial Conservative Multiplicative Cascade Approach for Network Traffic Modeling 27th IEEE International Conference on Advanced Information Networking and Applications - IEEE AINA 2013Falconer, K., (2003) Fractal Geometry: Mathematical Foundations and Applications, , Second Edition Wiley2 Edition November 17Riedi, R.H., An improved multifractal formalism and self-similar measures (1995) Journal of Mathematical Analysis and Applications, 189, pp. 462-1190Asmussen, S., (2000) Ruin Probabilities, , World Sicientific, SingapuraBenes, V., (1963) General Stochastic Processes in Theory of Queues, , Reading, MA: Addison WesleyStenico, J.W.G., Ling, L.L., A Multifractal Based Dynamic Bandwidth Allocation Approach for Network Traffic Flows IEEE International Conference on Communications (ICC), 23-27 May 2010, pp. 1-6Stenico, J.W.G., Ling, L.L., A Control Admission Scheme for Pareto Arrivals with Multi-Scale Characteristics Proceedings of the International Workshop on Telecommunications - IWT 2011, pp. 220-224. , May - 2011, Rio de Janeiro - BrazilRibeiro, V.J., Riedi, R.H., Crouse, M.S., Baraniuk, R.G., Multiscale Queueing Analysis of Long-Range-Dependent Network Traffic IEEE INFOCOM 2000, pp. 1026-1035. , Tel Aviv, Israelhttp://ita.ee.lbl.gov/html/traces.htmlhttp://www.cs.columbia.edu/~hgs/internet/traces.htmlhttp://crawdad.cs.dartmouth.edu/umd/sigcomm200
Statistical Evaluation Of Pruning Methods Applied In Hidden Neurons Of The Mlp Neural Network [avaliação Estatística De Métodos De Poda Aplicados Em Neurônios Intermediários Da Rede Neural Mlp]
No full textThere are several papers on pruning methods in the artificial neural networks area. However, with rare exceptions, none of them presents an appropriate statistical evaluation of such methods. In this article, we proved statistically the ability of some methods to reduce the number of neurons of the hidden layer of a multilayer perceptron neural network (MLP), and to maintain the same landing of classification error of the initial net. They are evaluated seven pruning methods. The experimental investigation was accomplished on five groups of generated data and in two groups of real data. Three variables were accompanied in the study: apparent classification error rate in the test group (REA); number of hidden neurons, obtained after the application of the pruning method; and number of training/retraining epochs, to evaluate the computational effort. The non-parametric Friedman's test was used to do the statistical analysis.44249256Reed, R., Pruning algorithms - A survey (1993) IEEE Trans. Neural Networks, 4 (5), pp. 740-747Karnin, E.D., A simple procedure for pruning back-propagation trained neural networks (1990) IEEE Trans. Neural Networks, 1 (2), pp. 239-242Lecun, Y., Denker, J.S., Solla, S.A., Optimal brain damage (1990) Advances in Neural Information Processing, 2, pp. 598-605. , D.S. Touretzky, Ed. DenverMao, J., Mohiuddin, K., Jain, A.K., Parsimonious network design and feature selection through node pruning (1994) Proc. International Conf. Pattern Recognition, pp. 622-624Park, Y.R., Murray, T.J., Chen, C., Predicting sun spots using a layered perceptron neural network (1996) IEEE Trans. Neural Networks, 7 (2), pp. 501-505Murase, K., Matsunaga, Y., Nakade, Y., A backpropagation algorithm which automatically determines the number of association units Proc. International Conf. Neural Networks, pp. 783-788. , 199Castellano, G., Fanelli, A.M., Pelillo, M., An iterative pruning algorithm for feedforward neural networks (1997) IEEE Trans. Neural Networks, 8 (3), pp. 519-531Silvestre, M.R., Ling, L.L., Reduzindo a arquitetura de uma rede via gap das saliências dos neurônios (1998) Anais V Simpósio Brasileiro de Redes Neurais, pp. 91-96Silvestre, M.R., Ling, L.L., Optimization of neural classifiers based on Bayesian decision boundaries and idle neurons pruning (2002) Proc. International Conf. Pattern Recognition, pp. 387-390Murphy, P.M., Aha, D.W., (1994) UCI Repository of Machine Learning Databases, , http://www.ics.uci.edu/~mlearn/MLRepository.html, 1994. Irvine, CA: University of California, Department of Information and Computer Science [Online]. AvailableHaykin, S., (1994) Neural Networks: A Comprehensive Foundation, p. 696. , New Jersey: WileyPontes, A.C.F., (2002) Obtenção Dos Níveis de Significância para Os Testes de Kruskal-Wallis, Friedman e Comparações Múltiplas Não-paramétricas, , Dissertação (Mestrado) - Dep. de Ciências Exatas, Escola Superior de Agricultura Luiz de Queiroz, Universidade de São Paulo, PiracicabaBjörck, A., Elfving, T., Accelerated projection methods for computing in artificial neural networks (1979) BIT, 19, pp. 145-16
Optimization Of Neural Classifiers Based On Bayesian Decision Boundaries And Idle Neurons Pruning
No full textIn this article we describe a feature extraction algorithm for pattern classification based on Bayesian Decision Boundaries and Pruning techniques. The proposed method is capable of optimizing MLP neural classifiers by retaining those neurons in the hidden layer that realy contribute to correct classification. Also in this article we proposed a method which defines a plausible number of neurons in the hidden layer based on the stem-and-leaf graphics of training samples. Experimental investigation reveals the efficiency of the proposed method. © 2002 IEEE.163387390Castellano, G., Fanelli, A.M., Pelillo, M., An iterative pruning algorithms for feedforward neural networks (1997) IEEE Trans. Neural Networks, 8 (3), pp. 519-531Cavalcanti, H.M.C., (2000) Feature Extraction Based on Decision Boundary Using Neural Networks, , Master's thesis, UNICAMPCavalcanti, H.M.C., Ling, L.L., Fast and efficient feature extraction based on bayesian decision boundaries (2000) Proc. Intl. Conf. Pattern RecognitionConover, W.J., (1980) Practical Nonparametric Statistics, , John Wiley and Sons, 2 editionKamin, E.D., A simple procedure for pruning back-propagation trained neural networks (1990) IEEE Trans. Neural Networks, 1 (2), pp. 239-242LeCun, Y.L., Denker, J.S., Solla, S.A., Optimal brain damage (1990) Advances in Neural Information Processing, pp. 598-605. , D. S. TouretzkyLippmann, R.P., Pattern classification using neural networks (1989) IEEE Comm. Magazine, pp. 47-64Mao, J., Mohiuddin, K., Jain, A.K., Parsimonious network design and feature selection through node pruning (1994) Proc. 12th Intl. Conf. Pattern Recognition, 2, pp. 622-624. , Jerusalem, ILMurase, K., Matsunaga, Y., Nakade, Y., A backpropagation algorithm which automatically determines the number of association units Proc. Intl. Conf. Neural Networks, pp. 783-788. , Singapore, apud [1]Murphy, P.M., Aha, D.M., (1994) UCI Repository of Machine Learning Databases, , http://www.ics.uci.edu/mlearn/MLRepository.html, Uniwrsity of California, Department of Information and Computer Science, Irvine, CAPark, Y.R., Murray, T.J., Chen, C., Predicting sun spots using a layered perceptron neural network (1996) IEEE Trans. Neural Networks, 7 (2), pp. 501-505Reed, R., Pruning algorithms - A survey (1993) IEEE Trans. Neural Networks, 4 (5), pp. 740-747Silvestre, M.R., Ling, L.L., Reducting the architecture of a network by gap of saliency of the neurons (1998) Anais v Simpósio Brasileiro de Redes Neurain, pp. 91-96. , Belo Horizonte, BrTukey, J.W., (1977) Exploratory Data Analysis, , Addison-Wesley, Massachusett
A Window-based Hybrid Signature Verification System
No full textIn this work we present a hybrid handwritten signature verification system where the on-line reference data acquired through a digitizing tablet serves as the basis for the segmentation process of the corresponding scanned off-line data. Local windows are determined over the image through a self-adjustable learning process and are used to focus the feature extraction step. The positions of the windows are determined according to the complexity of the underlying strokes given by the observation of a handwritten reproduction model. Local feature extraction is bounded by the windows formed and it is used with global primitives to feed the classifier. The overall performance of the system is then measured. © Springer-Verlag Berlin Heidelberg 2004.3072562568Leclerc, F., Plamondon, R., Automatic Signature Verification: The State of the Art - 1989-1993 (1994) International Journal of Pattern Recognition and Artificial Intelligence, 8 (3), pp. 643-660Brault, J.-J., Plamondon, R., Segmenting Handwritten Signatures at Their Perceptually t Important Points (1993) IEEE Transactions on PAMI, 15 (9), pp. 953-957Zimmer, A., Ling, L.L., Preprocessing: Segmenting by Stroke Complexity (2001) Proceedings of the VI Iber-American Symposium on Pattern Recognition, pp. 89-94. , BrazilGuerfali, W., Plamondon, R., The Delta LogNormal Theory for the Generation and Modeling of Cursive Characters (1995) Proceedings of the ICDAR, 2, pp. 495-498O'Gorman, L., Curvilinear Feature Detection from Curvature Estimation (1988) Proceedings of the 9th International Conference on Pattern Recognition, pp. 1116-1119Otsu, N., A Threshold selection Method from Grey Level Histograms (1979) IEEE Transactions on Systems Man and Cybernetics, 9, pp. 62-66Sabourin, R., Genest, G., An extended Shadow-Code Based Approach for Off-Line Signature Verification: Part I (1994) Proceedings of the IAPR, pp. 450-455. , Jerusalem, Israe
Secreted Frizzled Related Protein 2 (sFRP2) Decreases Susceptibility to UV-Induced Apoptosis in Primary Culture of Canine Mammary Gland Tumors by NF-κB Activation or JNK Suppression
No full textLetter to L.L. McGee from unknown author regarding members of an all state team
No full textLetter listing selections for the all state team for Douglass High School
Essay about how the image of Maine is constructed by institutions like L.L. Bean
No full textEssay about how the image of Maine is constructed by institutions like L.L. Bean and Bert and I. The author asks if local imagemakers are more true to life than their mass market counterparts
Offline Signature Verification System Based On The Online Data
No full textMost of the signature verification work done in the past years focused either on offline or online approaches. In this paper, a different methodology is proposed, where the online reference data acquired through a digitizing tablet serves as the basis for the segmentation process of the corresponding scanned offline data. Local windows are built over the image through a self-adjustable learning process and are used to focus on the feature extraction step. The windows positions are determined according to the complexity of the underlying strokes based on the observation of a delta-lognormal handwritten reproduction model. Local features extraction that takes place focused on the windows formed, and it is used in conjunction with the global primitives to feed the classifier. The overall performance of the system is then measured with three different classification schemes.2008Plamondon, R., Lorette, G., Automatic signature verification and writer identificationthe state of the art (1989) Pattern Recognition, 22 (2), pp. 107-131Leclerc, F., Plamondon, R., Automatic signature verification: The state of the Art19891993 (1994) International Journal of Pattern Recognition and Artificial Intelligence, 8 (3), pp. 643-660Plamondon, R., Srihari, S.N., On-line and off-line handwriting recognition: A comprehensive survey (2000) IEEE Transactions on Pattern Analysis and Machine Intelligence, 22 (1), pp. 63-84Quan, Z., Huang, D., Xia, X., Lyu, M.R., Lok, T.-M., Spectrum analysis based on windows with variable widths for online signature verification Proceedings of the 18th International Conference on Pattern Recognition (ICPR 06), 2, pp. 1122-1125. , August 2006 Hong KongKhan, M.K., Khan, M.A., Khan, M.A.U., Ahmad, I., On-line signature verification by exploiting inter-feature dependencies Proceedings of the 18th International Conference on Pattern Recognition (ICPR 06), 2, pp. 796-799. , August 2006 Hong KongLei, H., Palla, S., Govindaraju, V., ER 2: An intuitive similarity measure for on-line signature verification Proceedings of the 9th International Workshop on Frontiers in Handwriting Recognition (IWFHR 04), pp. 191-195. , October 2004 Tokyo, JapanArmand, S., Blumenstein, M., Muthukkumarasamy, V., Off-line signature verification based on the modified direction feature Proceedings of the 18th International Conference on Pattern Recognition (ICPR 06), 4, pp. 509-512. , August 2006 Hong KongZhang, B., Off-line signature recognition and verification by Kernel principal component self-regression Proceedings of the 5th International Conference on Machine Learning and Applications (ICMLA06), pp. 28-33. , December 2006 Orlando, Fla, USAFerrer, M.A., Alonso, J.B., Travieso, C.M., Offline geometric parameters for automatic signature verification using fixed-point arithmetic (2005) IEEE Transactions on Pattern Analysis and Machine Intelligence, 27 (6), pp. 993-997Brault, J.-J., Plamondon, R., Segmenting handwritten signatures at their perceptually important points (1993) IEEE Transactions on Pattern Analysis and Machine Intelligence, 15 (9), pp. 953-957Zimmer, A., Ling, L.L., Preprocessing: Segmenting by stroke complexity Proceedings of the 6th Iber-American Symposium on Pattern Recognition, pp. 89-94. , 2001 Florianpolis, SC, BrazilDrouhard, J.P., Sabourin, R., Godbout, M., A neural network approach to off-line signature verification using directional PDF (1996) Pattern Recognition, 29 (3), pp. 415-424Guerfali, W., Plamondon, R., The delta lognormal theory for the generation and modeling of cursive characters Proceedings of the 3rd International Conference on Document Analysis and Recognition (ICDAR 95), 1, pp. 495-498. , August 1995 Montreal, CanadaZimmer, A., Ling, L.L., A model-based signature verification system Proceedings of the 1st IEEE International Conference on Biometrics: Theory, Applications, and Systems (BTAS 07), pp. 1-6. , September 2007 Crystal City, Va, USAPlamondon, R., Guerfali, W., Why handwriting segmentation can be misleading? Proceedings of the 13th International Conference on Pattern Recognition (ICPR 96), 4, pp. 396-400. , August 1996 Vienna, AustriaPlamondon, R., Guerfali, W., The generation of handwriting with delta-lognormal synergies (1998) Biological Cybernetics, 78 (2), pp. 119-132Gerald, C.F., Wheatley, P.O., (1989) Applied Numerical Analysis, , New York, NY, USA Addison-WesleyOgorman, L., Curvilinear feature detection from curvature estimation Proceedings of the 9th International Conference on Pattern Recognition, 2, pp. 1116-1119. , 1988 Rome, ItalyOtsu, N., A threshold selection method from gray level histograms (1979) IEEE Transactions on Systems Man and Cybernetics, 9 (1), pp. 62-66Gonzalez, R., Woods, R., (1992) Digital Image Processing, , New York, NY, USA Addison-WesleyMardia, K.V., (1972) Statistics of Directional Data, , San Diego, Calif, USA Academic Pres
A New Bandwidth Estimation Approach For Fractal Processes [uma Nova Abordagem Para Estimação Da Banda Efetiva Em Processos Fractais]
No full textRecent extensive traffic analyses carried out over different network technologies have shown network traffic in its "monofractal" or "multifractal" nature as well as in its impact on network performance. Based on the results of these "monofractal" and " multifractal" traffic studies we introduce a new traffic parameter, capable of simultaneously expressing both "monofractal" and "multifractal" characteristics. This traffic characterization parameter is used for the design of more accurate effective bandwidth estimation approaches. In order to achieve a general and good methodology for effective bandwidth estimation for given traffic when the QoS requirements is take into account, we propose a broader optimization procedure. For the validation of the proposed effective bandwidth estimation approach, we intensely performed tests using real traffic traces and simulations. The obtained analytical and experimental results clearly indicate that the proposed bandwidth estimation approach for fractal traffic processes satisfies the QoS requirements for all analyzed traffic traces. Copyright 2010 IEEE - All Rights Reserved.35436446Feldmann, A., Gilbert, A.C., Willinger, W., Kurtz, T.G., The Changing Nature of Network Traffic: Scaling Phenomena (1998) Computer Communication Review, 28 (2). , Abril deFeldmann, A., Gilbert, A.C., Willinger, W., Data Networks as Cascades: Investigating the multifractal Nature of Internet WAN Traffic (1998) Procedures of the ACM SIGCOMM98, pp. 25-38. , Vancouver, B.C., CanadáPeitgen, H.-O., Jurgens, H., Saupe, D., (1994) Chaos and Fractals, , Spriger-Verlag, InglaterraStark, H., Woods, J.W., (1994) Probability, Random Processes and Estimation Theory for Engineers, , Prentice HallNorros, I., Pruthi, P., On the Applicability of Gaussian Traffic ModelsNorros, I., On the Use of Fractional Brownian Motion in the Theory of Connectionless Networks (1995) IEEE Journal on Selected Areas in Communications, , Agosto deNorros, I., A Storage Model with Self-Similar Input (1994) Queuing SystemsBeran, J., (1994) Statistics for Long-Memory Process, , Chapman & HallRoberts, J., Mocci, U., Virtamo, J., (1996) Broadband Network Traffic - Final Report of Action COST 242, , Springer-Verlag, AlemanhaJerkins, J.L., Wang, J.L., (1998) From Network Measurement Collection to Traffic Performance Modeling: Challenges and Lesson Learned, , IEEE, CAMAD, São Paulo, BrasilKesidis, G., Walrand, J., Chang, C.-S., Effective Bandwidth for Multiclass Markov Fluids and Other ATM Sources (1993) IEEE Trans. NetworkingSexton, M., Reid, A., (1997) Broadband Networking: ATM, SDH and Sonet, , Artech House, USADekking, M., Véhel, J.L., Lutton, E., Tricot, C., (1999) Fractals: Theory and Applications in Engineering, , Springer-Verlag, EnglandTaqqu, M.S., Teverovsky, V., Willingger, W., Is Network Traffic Self-Similar or multifractal? (1996) Journal FractalsMannersalo, P., Norros, I., Multifractal Analysis: A Potential Tool for Teletraffic Characterization?, , COST 257Balakrishnan, R., Williamson, C., (2002) A Performance Comparison of "Monofractal" and "Multifractal" Traffic Streams, , Department of Computer Science University of Saskatchewan, CanadáPontes, R., Coelho, R., (2001) The Scaling Characteristics of the Video Traffic and Its Impacts on the Acceptance Regions, , ITC 17, BrasilRelatório 01, Projeto Ericsson UNI-20, Março de 2001Relatório 02, Projeto Ericsson UNI-20, Setembro de 2001Relatório 03, Projeto Ericsson UNI-20, Março de 2002Peltier, R.F., Véhel, J.L., (1995) Multifractal" Brownian Motion: Definition and Preliminary Results, , INRIA, França, Março deRiedi, R.H., Véhel, J.L., (1997) Multifractal Properties of TCP Traffic: A Numerical Study, , INRIA, França, Março deKarlin, S., Taylor, H.M., (1975) A First Course in Stochastic Processes, , Academic PressWillinger, W., Sherman, R., Wilson, D., Self-Similarity Through High-Variability: Statistical Analysis of Ethernet LAN Traffic at the Source Level (1997) IEEE/ACM Transaction on Networking, 5 (1). , Fevereiro dehttp://www.INRIA.com.fr, FRACLABCanus, C., Véhel, J.L., Tricot, C., (1998) Continuous Large Deviations "Multifractal" Spectrum: Definition and Estimation, , INRIA, FrançaRiedi, R.H., Crouse, M.S., Ribeiro, V.J., Baranuik, R.G., A Multifractal Wavelet Model with Application to Network Traffic (1999) IEEE Transaction on Information Theory, 45 (3). , Abril deVojak, R., Véhel, J.L., (1998) Higher Order "Multifractal" Analysis, , INRIA, FrançaPerlingeiro, F.R., Ling, L.L., (1999) Data Traffic Characterization in a Corporate Environment, , Globecomm, Rio de JaneiroKelly, F., Notes on Effective Bandwidths, , http://www.statslab.cam.ac.uk/~frank/, University of Cambridge, UKMandelbrot, B., (1977) The Fractal Geometry of Nature, , W.H.Freeman and Co., Nova YorkThanki, S.G., (1999) Classification of Galaxies Using Fractal Dimensions, , MS Thesis, Department of Physics, University of Nevada - UNLV, USACanus, C., (1998) Robust Large Deviation Multifractal Spectrum Estimation, , INRIA, FrançaGilbert, A.C., Willinger, W., Feldmann, A., (1998) Scaling Analysis of Conservative Cascades, with Application to Network TrafficDembo, A., Zeitouni, O., (1998) Large Deviations Techniques and Applications, , Springer-VerlagLévy Véhel, J., Riedi, R., (1997) Fractional Brownian Motion and Data Traffic Modeling: The Other End of the Spectrum, , INRIA, FrançaLayton, W., Lee, H.K., Peterson, J., Numerical Solution of the Stationary Navier Stokes Equations Using a Multilevel Finite Element Method (1998) SIAM Journal on Scientific Computing, 20 (1), pp. 1-12. , Society for Industrial and Applied MathematicsGammel, B.M., (1994) Kritisches Verhalten und Niederfrequenz-Anomalien Beim Quanten-Hall-Effekt, , Technische Universität MünchenRelatório 04, Projeto Ericsson UNI-20, Novembro de 2002Billingsley, P., (1986) Probability and Measure, , John Wiley & SonsSpiegel, M.R., (1965) Shaum's Outline of Theory and Problems of Laplace Transforms, , MacGraw-Hill Book Co, USARiedi, R.H., (1999) Introduction to Multifractals, , Department of ECE, Rice University, Huston, TX, USA, Outubro deRiedi, R.H., Willinger, W., (2000) Self-similar Network Traffic and Performance Evaluation, , WileyDuffield, H.G., O'Connell, (1993) Large Deviations and Overflow Probabilities for the General Single-Server Queue, with Applications, , DIAS-STPGlynn, P., Whitt, W., (1993) Logarithmic Asymptotics for Steady-State Tail Probabilities in a Single-Server QueueYaïche, H., Mazumdar, R., Rosenberg, C., A Game Theoretic Framework for Bandwidth Allocation and Pricing in Broadband Networks (2000) IEEE/ACM Transactions on Networking, 8 (5). , OutubroRamaswamy, S., Gburzynski, P., (1998) A Neural Network Approach to Effective Bandwidth Characterization in ATM Networks, , Universidade de Alberta, CanadáCheng, R.-G., Chang, C.-J., Lin, L.-F., A QoS-Provisioning Neural Fuzzy Connection Admission Controller for Multimedia High-Speed Networks (1999) IEEE/ACM Transactions on Networking, 7 (1). , FEVEREIRO(1995) An Application of Chaotic Maps to Packet Traffic Modelling, , Tese de Doutorado, Royal Institute of Technology, SuéciaLe Boudec, J.-Y., (1996) Network Calculus Made Easy, , Ecole Polytecnique Fédérale de Lausanne, Technical Report EPFL-DI 96/218, Dezembro dePerlingeiro, F.R., Ling, L.L., (1999) Effective Bandwidth Allocation Approach for Self-Similar Traffic for a Single ATM Connection, , Globecomm, Rio de JaneiroLeland, W.E., Willinger, W., Wilson, D.V., (1994) On the Self-Similar Nature of Ethernet Traffic (Extended Version), pp. 1-15. , IEE
A New Approach For Buffer Queueing Evaluation Under Network Flows With Multi-scale Characteristics
No full textIn this paper, we propose a new analytical expression for estimating byte loss probability at a single server queue with multi-scale traffic arrivals. In order to make the estimation procedure numerically tractable without losing the accuracy, we assume and demonstrate that an exponential model is adequate for representing the relation between mean square and variance of Pareto distributed traffic processes under different time scale aggregation. Extensive experimental tests validate the efficiency and accuracy of the proposed loss probability estimation approach and its superior performance for applications in network connection with respect to some well-known approaches suggested in the literature.3133138Leland, W., Taqqu, M., Willinger, W., Wilson, D., On The Self- Similar Nature of Ethernet Traffic (extended version) (1994) IEEE/ACM Transactions on Networking, 2 (1), pp. 1-15Rezaul, K.M., Grout, V., An Overview of Long-Range Dependent Network Traffic Engineering and Analysis: Characteristics, Simulation, Modelling and Control (2007) Proc. of the 2nd International. Confernce. on Performance Evaluation Methodologies and Tools, 29, pp. 1-10Paxson, V., Floyd, S., Wide Area Traffic: The Failure of Poisson Modeling (1995) IEEE/ACM Transactions on Networking, 3 (3), pp. 226-244Feldmann, A., Gilbert, A.C., Willinger, W., Kurtz, T.G., The Changing Nature of Network Traffic: Scaling Phenomena (1998) SIGCOMM ACM Computer Communication Review, 28, pp. 5-29Stenico, J.W.G., Lee, L.L., Multifractal Nature of Wireless Network Traffic (2012) 15th Communications and Networking Simulation (CNS’12) Symposium, 1. , Orlando, EUATaqqu, M.S., Teverovsky, V., Willinger, W., Is Network Traffic Self-Similar or Multifractal? (1997) Fractals, 5, pp. 63-74Ribeiro, V.J., Riedi, R.H., Crouse, M.S., Baraniuk, R.G., Multiscale Queueing Analysis of Long-Range-Dependent Net work Traffic IEEE INFOCOM 2000, pp. 1026-1035. , Tel Aviv, IsraelDuffield, N.G., O’connell, N., (1994) Large Deviations and Overflow Probabilities for the General Singles-Server Queue, with Applications, , Dublin Institute dor Advanced Studies-applied ProbabilityLiu, N.X., Baras, J.S., Statistical Modeling and Performance Analysis of Multi-Scale Traffic Proceedings of Twenty – Second Annual Joint Conference of the IEEE Computer and Communications Societies, INFOCOM 2003, pp. 1837-1847. , San Francisco, CA, USA, March/April 2003Stenico, J.W.G., Lee, L.L., A Multifractal Based Dynamic Bandwidth Allocation Approach for Network Traffic Flows (2010) IEEE ICC2010 – International Conference on Communications, , 23-27 Cape Town, South AfricaBenes, V., (1963) General Stochastic Processes in theory of Queues, , Reading, MA: Addison Wesleyhttp://ita.ee.lbl.gov/html/traces.htmlPark, K., Willinger, W., (2002) Self-Si milar Network Traffic and Performance Evaluation, , New York: Wiley, Published Online: 7 Ja
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