DOCSLIB.ORG

Traffic Load?

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Traffic Load? 1. Introduction Lect01.ppt S-38.145 - Introduction to Teletraffic Theory – Spring 2004 1 1. Introduction Contents • Purpose of Teletraffic Theory • Teletraffic models • Classical model for telephone traffic • Classical model for data traffic 2 1. Introduction Traffic point of view • Telecommunication system from the traffic point of view: incoming outgoing users traffic system traffic • Ideas: – the system serves the incoming traffic – the traffic is generated by the users of the system 3 1. Introduction Interesting questions • Given the system and incoming traffic, what is the quality of service experienced by the user? • Given the incoming traffic and required quality of service, how should the system be dimensioned? • Given the system and required quality of service, what is the maximum traffic load? incoming outgoing users traffic system traffic 4 1. Introduction General purpose (1) • Determine relationships between the following three factors: – quality of service – system capacity – traffic load quality of service system capacity traffic load 5 1. Introduction General purpose (2) • System can be – a single device (e.g. a link between two telephone exchanges, a processor routing packets in a data network, a statistical multiplexer in ATM network) or – a whole communications network (e.g. telephone or data network) or a part of it • Typically a system consists of – a device (hardware) and – principles controlling it (software) • Traffic, on the other hand, consists of (depending on the case) – calls, packets, bursts, cells, etc. 6 1. Introduction General purpose (3) • Quality of service can be described – from the users point of view • e.g. call blocking probability, distribution of delay experienced by a packet stream – from the system point of view (= performance of the system) • e.g. utilization • It is also possible to think quality of service – from the offered traffic point of view • e.g. blocking experienced by ATM-connection requests, or other connection level property; grade of service – from the carried traffic point of view • e.g. cell loss during an accepted ATM connection, or other criteria during an accepted connection; quality of service 7 1. Introduction Example • Telephone traffic – traffic = telephone calls – system = telephone network – quality of service = probability that “the line is not busy” 1234567 PRRRR!!! 8 1. Introduction Relationships between the three factors • Qualitatively, the relationships are as follows: system capacity quality of service quality of service traffic load traffic load system capacity with given with given with given quality of service system capacity traffic load • To describe the relationships quantitatively, mathematical models are needed 9 1. Introduction Teletraffic models • Teletraffic models are usually stochastic (= probabilistic) – systems themselves are usually deterministic but traffic is typically stochastic • The underlying reason for it is thus the stochastic nature of traffic: – “you never know, who calls you and when” • It follows that the variables, which are needed to describe the quality of service, are also stochastic by nature, i.e. they are random variables: – number of ongoing calls – number of packets in a buffer • Random variable is described by its distribution, e.g. – probability that there are n ongoing calls – probability that there are n packets in the buffer •Astochastic process describes the temporal development of a random variable 10 1. Introduction Related fields • Probability Theory • Stochastic Processes • Queueing Theory • Statistical Analysis (of traffic measurements) • Operations Research • Optimization Theory • Decision Theory (Markov decision processes) • Simulation Techniques (object oriented programming) 11 1. Introduction Difference between the real system and the model • It is good to keep in mind the difference between the real system and the model – (Ideally), a model is a description of only a certain part or property of the real system – Often, due to various reasons, the model is not very accurate but rather approximative caution is needed when conclusions are drawn 12 1. Introduction Practical goals • Network planning – dimensioning – optimization – performance analysis • Network management and control – efficient operation – fault recovery – traffic management – routing – accounting 13 1. Introduction Literature • Teletraffic Theory – V. B. Iversen, Chapter 1 of “Teletraffic Engineering Handbook”, available from http://www.tele.dtu.dk/teletraffic/ – Teletronikk (1995) Vol. 91, Nr. 2/3, Special Issue on “Teletraffic” – COST 242, Final report (1996) “Broadband Network Teletraffic”, Eds. J. Roberts, U. Mocci, J. Virtamo, Springer – J.M. Pitts and J.A. Schormans (1996) “Introduction to ATM Design and Performance”, Wiley – J. Roberts, “Traffic Theory and the Internet”, available from http://www.comsoc.org/ci/public/preview/roberts.html • Queueing Theory – L. Kleinrock (1975) “Queueing Systems, Volume I: Theory”, Wiley – L. Kleinrock (1976) “Queueing Systems, Volume II: Computer Applications”, Wiley – D. Bertsekas and R. Gallager (1992) “Data Networks”, 2nd ed., Prentice-Hall – P.G. Harrison and N.M. Patel (1993) “Performance Modelling of Communication Networks and Computer Architectures”, Addison-Wesley 14 1. Introduction Contents • Purpose of Teletraffic Theory • Teletraffic models • Classical model for telephone traffic • Classical model for data traffic 15 1. Introduction Teletraffic models • Two phases of teletraffic modelling: – modelling of the incoming traffic traffic model – modelling of the system itself system model • Roughly, teletraffic models can be divided into two categories by the system model – loss systems (loss models) – waiting/queueing systems (queuing models) • During this course, we present simple teletraffic models describing a single resource • These models can be combined to create models for whole telecommunication networks – loss networks – queueing networks 16 1. Introduction Simple teletraffic model • Customers arrive at rate λ (customers per time unit on average) –1/λ = average inter-arrival time • Customers are served by n parallel servers • When busy, a server serves at rate µ (customers per time unit) –1/µ = average service time of a customer • There are m waiting places in the system • It is assumed that blocked customers (arriving in a full system) are lost µ 1 λ m n 17 1. Introduction Exercise • Consider the simple teletraffic model presented on the previous slide – What is the traffic model? – What is the system model? µ 1 λ m n 18 1. Introduction Pure loss system • No waiting places (m = 0) – If the system is full (with all n servers occupied) when a customer arrives, she is not served at all but lost. System is thus lossy. • From the customer’s point of view, it is interesting to know e.g. – What is the probability that the system is full when she arrives? • From the system’s point of view, it is interesting to know e.g. – What is the utilization factor of the servers? µ 1 λ n 19 1. Introduction Pure waiting system • Infinite number of waiting places (m = ∞) – If all n servers are occupied when a customer arrives, she occupies one of the waiting places. No customers are lost but some of them have to wait before getting served; system is thus lossless. • From the customer’s point of view, it is interesting to know e.g. – what is the probability that she has to wait “too long”? • From the system’s point of view, it is interesting to know e.g. – what is the utilization factor of the servers? µ 1 λ ∞ n 20 1. Introduction Mixed system • Finite number of waiting places (0 < m < ∞) – If all n servers are occupied but there are free waiting places when a customer arrives, she occupies one of the waiting places – If all n servers and all m waiting places are occupied when a customer arrives, she is not served at all but lost – Some customers are lost and some customers have to wait before getting served. Also this system is thus lossy. µ 1 λ m n 21 1. Introduction Infinite system • Infinite number of servers (n = ∞) – No customers are lost or even have to wait before getting served; it is a lossless system. – This (hypothetical) system is often much more simple to analyze than the corresponding real system with finite capacity. – Sometimes, this can be the only way to get even some approximate results for the real system µ 1 λ • • • ∞ 22 1. Introduction Little’s formula • Consider a system where λλ – new customers arrive at rate λ • Stability assumption: – Customers do not accumulate in the system, occasionally system is empty • Consequence: – Customers depart from the system at rate λ • Denote N = average number of customers in the system T = average time a customer spends in the system • Little’s formula: N = λT 23 1. Introduction Contents • Purpose of the Teletraffic Theory • Teletraffic models • Classical model for telephone traffic • Classical model for data traffic 24 1. Introduction Classical model for telephone traffic (1) • Loss models have traditionally been used to describe (circuit-switched) telephone networks – Pioneering work made by Danish mathematician A.K. Erlang (1878-1929) • Consider a link between two telephone exchanges (classical teletraffic problem) – traffic consists of the ongoing telephone calls on the link 25 1. Introduction Classical model for telephone traffic (2) • Erlang modelled this as a pure loss system (m = 0) –customer = call • λ = call arrival rate – service time = (call) holding time • h = 1/µ = average holding time – server = channel on the link
Load more

Recommended publications
  • Measuring, Modelling and Understanding Internet Traffic
    PRODUCED ON ACID-FREE PAPER MEASURING, UNDERSTANDING AND MODELLING INTERNET TRAFFIC Nicolas Hohn SUBMITTED IN TOTAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY JULY 2004 DEPARTMENT OF ELECTRICAL AND ELECTRONIC ENGINEERING THE UNIVERSITY OF MELBOURNE AUSTRALIA A mes parents, pour leur amour, encouragement et constant support, sans qui rien ne serait. iii Abstract This thesis concerns measuring, understanding and modelling Internet traffic. We first study the origins of the statistical properties of Internet traffic, in particular its scaling behaviour, and propose a constructive model of packet traffic with physically motivated parameters. We base our analysis on a large amount of empirical data measured on different networks, and use a so called semi-experimental approach to isolate certain features of traffic we seek to model. These results lead to the choice of a particular Poisson cluster process, known as Bartlett-Lewis point process, for a new packet traffic model. This model has a small number of parameters with simple networking meaning, and is mathematically tractable. It allows us to gain valuable insight on the underlying mechanisms creating the observed statistics. In practice, Internet traffic measurements are limited by the very large amount of data generated by high bandwidth links. This leads us to also investigate traffic sampling strate- gies and their respective inversion methods. We argue that the packet sampling mechanism currently implemented in Internet routers is not practical when one wants to infer the sta- tistics of the full traffic from partial measurements. We advocate the use of flow sampling for many purposes. We show that such sampling strategy is much easier to invert and can give reasonable estimates of higher order traffic statistics such as distribution of number of packets per flow and spectral density of the packet arrival process.
    [Show full text]
  • Formative Evaluation of Optical Network Projects in Metropolitan Area
    D. »urepiÊ, I. Boπnjak, T. Bauk: Formative Evaluation of Optical Network Projects in Metropolitan Area DANKO »UREPI∆, B.Eng. Traffic Infrastructure Hrvatske telekomunikacije Review Planinska 1a, 10000 Zagreb, Republika Hrvatska U.D.C.: 629.052.3 IVAN BO©NJAK, D.Sc. Accepted: Jun. 23, 2003 Fakultet prometnih znanosti Approved: Dec. 15, 2003 VukeliÊeva 4, 10000 Zagreb, Republika Hrvatska TON»I BAUK, B.Eng. Hrvatske telekomunikacije Planinska 1a, 10000 Zagreb, Republika Hrvatska FORMATIVE EVALUATION OF OPTICAL NETWORK PROJECTS IN METROPOLITAN AREA ABSTRACT Unlike most of the old approaches to planning network facilities, we adapt new paradigm with for- The paper discusses the approach to formative and sum- mative evaluation where teletraffic engineering and mative evaluation of alternative solutions for next generation service management interact in different levels of optical access network. Unlike most of the old approaches systems description. Beyond the standardised techni- to planning of network facilities, we adapt the new paradigm cal solutions at the physical and logical layer, huge where teletraffic engineering and service management inter- act at different levels of systems description. The basic thesis work has to deliver effective solutions to customers is that formative traffic evaluation has to be the key part of and other stakeholders: network operators, service initial and ongoing project activities in deploying new tech- providers, vendors, local community, etc. nological solutions in urban telecommunications network. The basic thesis is that formative traffic evalua- Passive Optical Network (PON) is analysed as one effective tion has to be part of initial and ongoing project ac- solution because it satisfies the broadband traffic require- tivities in developing and deploying new solutions in ments with minimal amount of optical equipment and fiber metropolitan area access networks.
    [Show full text]
  • Network Traffic Modeling
    Chapter in The Handbook of Computer Networks, Hossein Bidgoli (ed.), Wiley, to appear 2007 Network Traffic Modeling Thomas M. Chen Southern Methodist University, Dallas, Texas OUTLINE: 1. Introduction 1.1. Packets, flows, and sessions 1.2. The modeling process 1.3. Uses of traffic models 2. Source Traffic Statistics 2.1. Simple statistics 2.2. Burstiness measures 2.3. Long range dependence and self similarity 2.4. Multiresolution timescale 2.5. Scaling 3. Continuous-Time Source Models 3.1. Traditional Poisson process 3.2. Simple on/off model 3.3. Markov modulated Poisson process (MMPP) 3.4. Stochastic fluid model 3.5. Fractional Brownian motion 4. Discrete-Time Source Models 4.1. Time series 4.2. Box-Jenkins methodology 5. Application-Specific Models 5.1. Web traffic 5.2. Peer-to-peer traffic 5.3. Video 6. Access Regulated Sources 6.1. Leaky bucket regulated sources 6.2. Bounding-interval-dependent (BIND) model 7. Congestion-Dependent Flows 7.1. TCP flows with congestion avoidance 7.2. TCP flows with active queue management 8. Conclusions 1 KEY WORDS: traffic model, burstiness, long range dependence, policing, self similarity, stochastic fluid, time series, Poisson process, Markov modulated process, transmission control protocol (TCP). ABSTRACT From the viewpoint of a service provider, demands on the network are not entirely predictable. Traffic modeling is the problem of representing our understanding of dynamic demands by stochastic processes. Accurate traffic models are necessary for service providers to properly maintain quality of service. Many traffic models have been developed based on traffic measurement data. This chapter gives an overview of a number of common continuous-time and discrete-time traffic models.
    [Show full text]
  • Teletraffic Engineering Course Brief and Outline
    f Electr o ica ol l a School of Electrical and Information Engineering o h n c d S University of the Witwatersrand, Johannesburg I n g f n o i r r m ee at in ion Eng ELEN7015 { Teletraffic Engineering Course Brief and Outline: 2015 Course Lecturer: Dr L. Cheng Room: CM4 380 Tel: 011 7177228 Email: [email protected] 1 Course Background and Purpose Teletraffic engineering, based on teletraffic theory, provides the means to analyse, design and monitor networks to ensure that the networks carry end user and signalling information to the satisfaction of end users. Teletraffic started early in the history of telephony with a Danish School- master wondering about the capacity of the village telephone exchange. As switched circuits grew in complexity, a large body of theory and practice emerged for engineering telephone networks to carry voice traffic with acceptable quality of service using measures such as the probability of an attempt to make a call failing because all equipment is busy. With the emergence of packet switched networks the subject expanded. Approaches to engineering packet switched networks to carry user packets have much in common with switched circuit networks but required extensions. Engineering of packet networks for traffic also has its own nuances. Teletraffic theory is rooted in probability. Ideally, the student should be well versed in probability concepts. However, as this is often not the case, the course is structure with the opportunity to learn or refresh key concepts in probablity and to reinforce this learning through computer exercises. 2 Course Outcomes By the end of the course the student will demonstrate ability to: 1.
    [Show full text]
  • Prospectus for Undergraduate Admissions 2021
    NED UNIVERSITY of Engineering & Technology 1921-2021 www.neduet.edu.pk At •FOREWORD NED University of Engineering & Technology is one of the oldest engineering universities of Pakistan with its impact and reputation completing hundred years in 2021. In its centennial year, the University has maintained its prominence in the Times Impact Ranking which evaluates academic institute against the Sustainable Development Goals. Correspondingly, in the renowned and reliable QS Ranking, NED University is among the top 2.5 percent institutions in Asia. Our alumni are placed across the globe and have been contributing in various professional capacities in almost every sector making a difference to engineering, technology, economy and ultimately society and humanity at large. The success stories and global presence of our alumni reflect the quality of graduates being educated and trained at this prestigious institution. The University with its strong academia-industry linkage enhances student learning through industry-exposure opportunities and industry engagement on demand-based research for the industry. State-of-the-art laboratories established in various departments in collaboration with the partner industries and the NED Alumni with the recent ones including National Centre for AI, Cyber Security, Robotics, Data Analysis, Virtual Reality Centre and Centre for Infectious Disease Modelling are actively engaged in doing research on pressing, emerging and critical problems. The newly founded constituent college of the University; Thar Institute of Engineering, Sciences and Technology (TIEST) at Islamkot, Thar has completed its second year of establishment. The students admitted at TIEST are fully facilitated with modern and state- of-the-art academic and relevant equipment aligned with the University’s commitment to provide its students, applied, analytical, design, and computing skills that underpin modern engineering practices, while encouraging their creativity and problem-solving skills essential for contemporary engineers and professionals in allied disciplines.
    [Show full text]
  • Quality of Service Oriented Traffic Engineering
    Quality of Service oriented Traffic Engineering Methods for Multi-Service Cellular Networks Dienstgüte-orientierte verkehrstheoretische Methoden für die Bereitstellung unterschiedlicher Dienste in zellularen Netzen Der Technischen Fakultät der Universität Erlangen-Nürnberg zur Erlangung des Grades DOKTOR INGENIEUR vorgelegt von LARISSA N. POPOVA Erlangen – 2009 Als Dissertation genehmigt von der Technischen Fakultät der Friedrich-Alexander-Universität Erlangen-Nürnberg Tag der Einreichung: 07. Dezember 2009 Tag der Promotion: 12. February 2010 Dekan: Prof. Dr.-Ing. Reinhard German Berichterstatter: Prof. Dr.-Ing. Villy Baek Iversen Prof. Dr.-Ing. Wolfgang Koch To my husband Denis and my sons Konstantin and Maxim Acknowledgment First of all, I would like to thank my supervisor Prof. Wolfgang Koch, for giving me the opportunity to pursue my Ph.D. at his Institute of Mobile Communication and for providing an environment where it was a pleasure to work. I am grateful to him for the fruitful discussions on my work, for his continued support and faith in the success of my research. I am indebted to Prof. Villy Baek Iversen for his kind-hearted mentoring, for reviewing my thesis, and for making my memorable stay at Technical University of Denmark, Lyngby, possible. I am very grateful to Dr. Wolfgang Gerstacker for his interest in my work, for his great encouragement, and for finding time to participate in the defense of this work. I would also like to thank all my colleagues at the Telecommunications Laboratory in Erlangen for creating pleasant and humorous atmosphere. Special thanks go to my roommate Armin Schmidt, for interesting scientific and non- scientific discussions, as well as for his technical LaTeX support.
    [Show full text]
  • Information Booklet
    Institute of Information and Communication Technology (IICT) Information Booklet Bangladesh University of Engineering and Technology (BUET) Dhaka-1000, Bangladesh IICT Information Booklet 2016 ii 8th Edition April 2016 Published by Institute of Information and Communication Technology (IICT) Bangladesh University of Engineering and Technology (BUET), Dhaka-1000, Bangladesh IICT Information Booklet 2016 iii CONTENTS Preface………………………………………………………..……..……..1 CHAPTER 1: General Information ..................................... 3 1.1 The University .......................................................... 3 1.2 Faculties, Departments and Degrees Offered ......... 4 1.3 The Central Library .................................................. 7 1.4 University Institutes, Centers, Directorates and Link Programs .............................................................................. 7 1.4.1 Institutes and Centers: ......................................... 7 1.4.2 Directorates .......................................................... 8 1.4.3 Bureau ................................................................... 8 1.4.4 Linkage Projects: .................................................. 8 1.5 University Administration .......................................... 9 1.5.1 The Chancellor of the University .......................... 9 1.5.2 The Vice Chancellor ............................................. 9 1.5.3 The University Syndicate ..................................... 9 1.5.4 Deans of Faculties.............................................
    [Show full text]
  • Computer Modeling and Simulation of Teletraffic Models for 5G Networks
    Computer Modeling and Simulation of Teletraffic Models for 5G Networks E.P. Ivanova*, T. Iliev*, Gr. Mihaylov*, I. Stoyanov, * F. Tsvetanov**, E. Otsetova*** and D. Radev *** * University of Ruse, Ruse, Bulgaria ** Southwest University, Blagoevgrad, Bulgaria *** College of Telecommunications and Posts, Sofia, Bulgaria [email protected], [email protected], [email protected], [email protected], [email protected], [email protected], [email protected] Abstract - Advances in the new mobile networks are steadily more devices in the whole network. Typically, the increasing the demand on network resources, and new performance of the whole network containing many links standards must ensure that the networks are managed working in parallel and interfering with each other is of effectively in order to ensure that users of the network primary interest. remain satisfied with their Quality of Service (QoS) and Quality of Experience (QoE). The simulations opportunities This type of simulation allows the modeling of represent a chance to reduce the digital divide and to ensure resource management issues, admission of system users the new 5G networks with minimum cost of time and with different priority, interaction and network loading by financials. The simulation of teletraffic models allows the several types of traffic sources, etc. The aim of such modeling of resource management issues, admission of modeling is network capacity evaluation and probabilities system users with different parameters. of failure. I. INTRODUCTION II. TRENDS OF 5G MOBILE NETWORKS Mobile networks constantly evolve. In the 1980s, The trends of 5G mobile access is to be built upon new when wireless technology began to go mainstream, the 1G radio access technologies, evolving 4G, LTE, HSPA, analog networks supported the bulky, brick-like mobile GSM and WiFi.
    [Show full text]
  • Informe Profesional
    PEDECIBA Informática Instituto de Computación – Facultad de Ingeniería Universidad de la República Montevideo, Uruguay Tesis de Maestría en Informática Redes de Contenido: Taxonomía y Modelos de evaluación y diseño de los mecanismos de descubrimiento de contenido Pablo Rodríguez-Bocca Octubre 2005 Orientador de Tesis: Dr. Héctor Cancela Bosi Supervisor: Dr. Héctor Cancela Bosi Redes de Contenido: Taxonomía y Modelos de evaluación y diseño de los mecanismos de descubrimiento de contenido. Pablo Rodríguez-Bocca. ISSN 0797-6410 Tesis de Maestría en Informática, PEDECIBA. Reporte Técnico INCO-RT-05-xx (número en trámite). PEDECIBA. Instituto de Computación - Facultad de Ingeniería Universidad de la República. Montevideo, Uruguay, Octubre de 2005. Agradecimientos En primer lugar quiero agradecer a mi tutor, Héctor Cancela Bosi, por su apoyo y estímulo permanente. Al área de Informática del PEDECIBA por la admisión al programa de Maestría en Informática. Al programa de jóvenes investigadores de la Comisión Sectorial de Investigación Científica (CSIC), al proyecto RMS del Programa de Desarrollo Tecnológico (PDT) y al proyecto PAIR del programa de Equipos Asociados del INRIA (Francia) por su apoyo económico en distintas etapas de la maestría.Al Departamento de Investigación Operativa del Instituto de Computación y a la Administración Nacional de Telecomunicaciones (ANTEL) por permitir mi dedicación al proyecto. A mis padres, que con su esfuerzo me permitieron realizar las carreras de Ingeniería en Computación y Eléctrica, siempre fomentando en mi el ingenio y el trabajo. A mi hermana y amigos por ayudarme y disimular interés en estos temas académicos; y a mi novia por su incondicional apoyo y paciencia. Resumen En este trabajo se estudia a las Redes de Contenido en su conjunto, desde el punto de vista de su diseño y arquitectura.
    [Show full text]
  • 1. Introduction
    1. Introduction lect01.ppt S-38.145 - Introduction to Teletraffic Theory – Spring 2005 1 1. Introduction Contents • Telecommunication networks and switching modes • Purpose of Teletraffic Theory • Teletraffic models • Little’s formula 2 1. Introduction Telecommunication network • A simple model of a telecommunication network consists of – nodes • terminals • network nodes – links between nodes • Access network – connects the terminals to the network nodes • Trunk network – connects the network nodes to each other 3 1. Introduction Shared medium as an access network • In the previous model, – connections between terminals and network nodes are point-to- point type (⇒ no resource sharing within the access netw.) • In some cases, such as – mobile telephone network – local area network (LAN) connecting computers the access network consists of shared medium: – users have to compete for the resources of this shared medium – multiple access (MA) techniques are needed 4 1. Introduction Switching modes • Circuit switching – telephone networks – mobile telephone networks – optical networks • Packet switching – data networks – two possibilities • connection oriented: e.g. X.25, Frame Relay • connectionless: e.g. Internet (IP), SS7 (MTP) • Cell switching – ATM networks – connection oriented – fast packet switching with fixed length packets (cells) 5 1. Introduction Circuit switching (1) • Connection oriented: B – connections set up end-to-end before information transfer – resources reserved for the whole duration of connection – if resources are not available, the call is blocked and lost • Information transfer as A continuous stream 6 1. Introduction Circuit switching (2) • Before information transfer B – Set-up delay • During information transfer – signal propagation delay – no overhead – no extra delays A • Example: telephone network 7 1.
    [Show full text]
  • Models and Methods for Traffic Engineering Problems with Single
    Models and methods for Traffic Engineering problems with single-path routing Martim Joyce-Moniz To cite this version: Martim Joyce-Moniz. Models and methods for Traffic Engineering problems with single-path routing. Operations Research [cs.RO]. Université Libre de Bruxelles (U.L.B.), Belgium, 2016. English. tel- 01421865 HAL Id: tel-01421865 https://hal.inria.fr/tel-01421865 Submitted on 4 Jan 2017 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Universite´ Libre de Bruxelles Facult´edes Sciences D´epartement d'Informatique Models and methods for Traffic Engineering problems with single-path routing Martim Joyce-Moniz Th`esepr´esent´eeen vue de l'obtention du grade acad´emique de Docteur en Sciences October 2016 ii To my family. iv This thesis has been written under the supervision of Prof. Bernard Fortz and Prof. Lu´ısGouveia. The members of the jury are: • Prof. Bernard Fortz (Universit´eLibre de Bruxelles, Belgium) • Prof. Bernard Gendron (Universit´ede Montreal, Canada) • Prof. Lu´ısGouveia (Universidade de Lisboa, Portugal) • Prof. Martine Labb´e(Universit´eLibre de Bruxelles, Belgium) • Prof. Ivana Ljubic (ESSEC Business School Paris, France) • Prof. Thomas St¨utzle(Universit´eLibre de Bruxelles, Belgium) The research of Martim Joyce-Moniz was done with the support of the COMEX (Combinatorial Optimization: Metaheuristics & Exact Methods) project.
    [Show full text]
  • Redalyc.Dimensioning of Optical Multicast for Dynamic WDM
    Ingeniare. Revista Chilena de Ingeniería ISSN: 0718-3291 [email protected] Universidad de Tarapacá Chile Puerto Leguizamón, Gustavo; Sastoque Caro, Miguel; Suárez Fajardo, Carlos Dimensioning of optical multicast for dynamic WDM convergent access networks Ingeniare. Revista Chilena de Ingeniería, vol. 23, núm. 2, abril, 2015, pp. 176-181 Universidad de Tarapacá Arica, Chile Available in: http://www.redalyc.org/articulo.oa?id=77236977003 How to cite Complete issue Scientific Information System More information about this article Network of Scientific Journals from Latin America, the Caribbean, Spain and Portugal Journal's homepage in redalyc.org Non-profit academic project, developed under the open access initiative Ingeniare. Revista chilena de ingeniería, vol. 23 Nº 2, 2015, pp. 175-181 Dimensioning of optical multicast for dynamic WDM convergent access networks Dimensionado de multicast óptico para redes WDM de acceso dinámicas convergentes Gustavo Puerto Leguizamón1 Miguel Sastoque Caro1 Carlos Suárez Fajardo1 Recibido 19 de mayo de 2014, aceptado 6 de agosto de 2014 Received: May 19, 2014 Accepted: August 6, 2014 ABSTRACT This paper presents a teletraffic study that evaluates the benefits of a passive optical access network, fix/mobile, by multiplexing wavelength division (WDM-PON) in which it is appreciated the impact of including extra wavelengths channels for the transmission of multicast services versus the multicast transport service using replicated unicast connections. The conclusion is that under heavy bulk-data traffic, the nominal data rate and tolerated efficiency are defined by the maximum number of out-of- profile users permitted for every multicast solution. Specifically, for the high values of efficiency the channels of extra wavelength avoid the need of multicast wavelengths used only when there is a fraction (significantly small) of out-of-profile users (5%).
    [Show full text]