Advanced Queueing Theory
|
|
- Clarence Hodge
- 5 years ago
- Views:
Transcription
1 Advanced Queueing Theory 1 Networks of queues (reversibility, output theorem, tandem networks, partial balance, product-form distribution, blocking, insensitivity, BCMP networks, mean-value analysis, Norton's theorem, sojourn times) Analytical-numerical techniques (matrix-analytical methods, compensation method, error bound method, approximate decomposition method) Polling systems (cycle times, queue lengths, waiting times, conservation laws, service policies, visit orders) Richard J. Boucherie department of Applied Mathematics University of Twente Queueing Theory/AQT.html
2 Advanced Queueing Theory Today (lecture 6): Compensation approach 2 IJBF Adan, J. Wessels, and WHM Zijm. Analysis of the symmetric shortest queue problem. Stochastic Models, 6: , OJ Boxma, GJ van Houtum. The compensation approach applied to a 2x2 switch, Prob. Inf Sci, 7: , Model Global balance equations as difference equations The boundary Shortest queue problem
3 Model 3 Consider Markov chain with transition rates: Global balance equations
4 Advanced Queueing Theory Today (lecture 6): Compensation approach 4 IJBF Adan, J. Wessels, and WHM Zijm. Analysis of the symmetric shortest queue problem. Stochastic Models, 6: , OJ Boxma, GJ van Houtum. The compensation approach applied to a 2x2 switch, Prob. Inf Sci, 7: , Model Global balance equations as difference equations The boundary Shortest queue problem
5 Global balance as difference equations 5 Consider Markov chain with transition rates: Global balance equations Difference equations Solution
6 Global balance as difference equations 6 Consider Markov chain with transition rates: Global balance equations Difference equations Solution
7 Global balance as difference equations 7 Quadratic form: on curve through (1,1), shape depending on drift
8 Global balance as difference equations 8 Consider curve C with all solutions of α m β n {q 10 + q 11 + q 01 + q 11 + q 10 + q q q 1 1 } = α m 1 β n q 10 + α m 1 β n 1 q 11 + α m β n 1 q 01 + α m +1 β n 1 q 11 +α m +1 β n q 10 + α m +1 β n +1 q α m β n +1 q α m 1 β n +1 q 1 1 Theorem: Let p(m,n) be an invariant measure. Then there exists a unique Borel probability measure ζ on (0, ) 2 such that p(m,n) = α m β n dζ(α,β) C
9 Advanced Queueing Theory Today (lecture 6): Compensation approach 9 IJBF Adan, J. Wessels, and WHM Zijm. Analysis of the symmetric shortest queue problem. Stochastic Models, 6: , OJ Boxma, GJ van Houtum. The compensation approach applied to a 2x2 switch, Prob. Inf Sci, 7: , Model Global balance equations as difference equations The boundary Shortest queue problem
10 Global balance as difference equations 10 Consider Markov chain with transition rates: Global balance equations Difference equations Solution
11 Influence of the boundary 11 Jackson network Horizontal boundary: linear equation Vertical boundary: linear equation Unique solution that satisfies both boundary equations
12 Influence of the boundary 12 General setting: For each stable geometric solution of interior rates, there exist boundary rates such that geometric solution is equilibrium distribution. Boundary rates not unique (determined up to linear equation at each boundary separately) Given selection for boundary rates: product form determined Rates for sum of product forms? When rates are prescribed?
13 Advanced Queueing Theory Today (lecture 6): Compensation approach 13 IJBF Adan, J. Wessels, and WHM Zijm. Analysis of the symmetric shortest queue problem. Stochastic Models, 6: , OJ Boxma, GJ van Houtum. The compensation approach applied to a 2x2 switch, Prob. Inf Sci, 7: , Model Global balance equations as difference equations The boundary Shortest queue problem
14 Exercise on compensation approach and boundary modification Consider the Markov chain with transition rates as depicted. A) Let h(-1,1)=q(-1,1), h(0,1)=q(0,1), h(1,1)=q(1,1), v(1,1)=q(1,1), v(1,0)=q(1,0), v(1,-1)=q(1,-1), r(1,1)=q(1,1).show that for each stable geometric solution of the global balance equations in the interior, boundary rates can be found such that this geometric solution is the unique equilibrium distribution. B) Investigate whether or not boundary rates can be established such that the equilibrium distribution is a linear combination of stable geometric solutions of the interior global balance equations. 2. Consider the shortest queue problem. Obtain an expression for the coefficient of correlation of the two queue lengths.
Advanced Queueing Theory
Advanced Queueing Theory 1 Networks of queues (reversibility, output theorem, tandem networks, partial balance, product-form distribution, blocking, insensitivity, BCMP networks, mean-value analysis, Norton's
More informationThe shortest queue problem
The shortest queue problem Ivo Adan March 19, 2002 1/40 queue 1 join the shortest queue queue 2 Where: Poisson arrivals with rate Exponential service times with mean 1/ 2/40 queue 1 queue 2 randomly assign
More informationarxiv: v2 [math.pr] 2 Jul 2014
Necessary conditions for the invariant measure of a random walk to be a sum of geometric terms arxiv:1304.3316v2 [math.pr] 2 Jul 2014 Yanting Chen 1, Richard J. Boucherie 1 and Jasper Goseling 1,2 1 Stochastic
More informationStability and Rare Events in Stochastic Models Sergey Foss Heriot-Watt University, Edinburgh and Institute of Mathematics, Novosibirsk
Stability and Rare Events in Stochastic Models Sergey Foss Heriot-Watt University, Edinburgh and Institute of Mathematics, Novosibirsk ANSAPW University of Queensland 8-11 July, 2013 1 Outline (I) Fluid
More informationContents Preface The Exponential Distribution and the Poisson Process Introduction to Renewal Theory
Contents Preface... v 1 The Exponential Distribution and the Poisson Process... 1 1.1 Introduction... 1 1.2 The Density, the Distribution, the Tail, and the Hazard Functions... 2 1.2.1 The Hazard Function
More informationA Joining Shortest Queue with MAP Inputs
The Eighth International Symposium on Operations Research and Its Applications (ISORA 09) Zhangjiajie, China, September 20 22, 2009 Copyright 2009 ORSC & APORC, pp. 25 32 A Joining Shortest Queue with
More informationUpper and lower bounds for the waiting time in the symmetric shortest queue system Adan, I.J.B.F.; van Houtum, G.J.J.A.N.; van der Wal, J.
Upper and lower bounds for the waiting time in the symmetric shortest queue system Adan, I.J.B.F.; van Houtum, G.J.J.A.N.; van der Wal, J. Published: 01/01/1992 Document Version Publisher s PDF, also known
More information6 Solving Queueing Models
6 Solving Queueing Models 6.1 Introduction In this note we look at the solution of systems of queues, starting with simple isolated queues. The benefits of using predefined, easily classified queues will
More informationAnswers to selected exercises
Answers to selected exercises A First Course in Stochastic Models, Henk C. Tijms 1.1 ( ) 1.2 (a) Let waiting time if passengers already arrived,. Then,, (b) { (c) Long-run fraction for is (d) Let waiting
More informationAsymptotics for Polling Models with Limited Service Policies
Asymptotics for Polling Models with Limited Service Policies Woojin Chang School of Industrial and Systems Engineering Georgia Institute of Technology Atlanta, GA 30332-0205 USA Douglas G. Down Department
More informationSERIE RE5EHRCH RIERIORRHDR
SERIE RE5EHRCH RIERIORRHDR A SIMPLE PERFORMABILITY ESTIMATE FOR JACKSON NETWORKS WITH AN UNRELIABLE OUTPUT CHANNEL N.M. van Dijk Research Memorandum 1989-32 July 1989 VRIJE UNIVERSITEIT FACULTEIT DER ECONOMISCHE
More informationOn open problems in polling systems
Queueing Syst (2011) 68:365 374 DOI 10.1007/s11134-011-9247-9 On open problems in polling systems Marko Boon Onno J. Boxma Erik M.M. Winands Received: 10 May 2011 / Revised: 10 May 2011 / Published online:
More informationarxiv: v2 [math.pr] 2 Nov 2017
Performance measures for the two-node queue with finite buffers Yanting Chen a, Xinwei Bai b, Richard J. Boucherie b, Jasper Goseling b arxiv:152.7872v2 [math.pr] 2 Nov 217 a College of Mathematics and
More information/department of mathematics and computer science 1/46
LNMB Course Advanced Queueing Theory Lecture 9, April 23, 2012 Onno Boxma, Sem Borst (TU/e) http://www.win.tue.nl/ sem/aqt/ /department of mathematics and computer science 1/46 Course overview 1. Product-form
More information1 Continuous-time chains, finite state space
Université Paris Diderot 208 Markov chains Exercises 3 Continuous-time chains, finite state space Exercise Consider a continuous-time taking values in {, 2, 3}, with generator 2 2. 2 2 0. Draw the diagramm
More informationAn Introduction to Stochastic Modeling
F An Introduction to Stochastic Modeling Fourth Edition Mark A. Pinsky Department of Mathematics Northwestern University Evanston, Illinois Samuel Karlin Department of Mathematics Stanford University Stanford,
More informationTHE ON NETWORK FLOW EQUATIONS AND SPLITTG FORMULAS TRODUCTION FOR SOJOURN TIMES IN QUEUEING NETWORKS 1 NO FLOW EQUATIONS
Applied Mathematics and Stochastic Analysis 4, Number 2, Summer 1991, III-I16 ON NETWORK FLOW EQUATIONS AND SPLITTG FORMULAS FOR SOJOURN TIMES IN QUEUEING NETWORKS 1 HANS DADUNA Institut flit Mathematische
More informationTales of Time Scales. Ward Whitt AT&T Labs Research Florham Park, NJ
Tales of Time Scales Ward Whitt AT&T Labs Research Florham Park, NJ New Book Stochastic-Process Limits An Introduction to Stochastic-Process Limits and Their Application to Queues Springer 2001 I won t
More informationQueuing Networks: Burke s Theorem, Kleinrock s Approximation, and Jackson s Theorem. Wade Trappe
Queuing Networks: Burke s Theorem, Kleinrock s Approximation, and Jackson s Theorem Wade Trappe Lecture Overview Network of Queues Introduction Queues in Tandem roduct Form Solutions Burke s Theorem What
More informationreversed chain is ergodic and has the same equilibrium probabilities (check that π j =
Lecture 10 Networks of queues In this lecture we shall finally get around to consider what happens when queues are part of networks (which, after all, is the topic of the course). Firstly we shall need
More informationExercises Stochastic Performance Modelling. Hamilton Institute, Summer 2010
Exercises Stochastic Performance Modelling Hamilton Institute, Summer Instruction Exercise Let X be a non-negative random variable with E[X ]
More informationNATCOR: Stochastic Modelling
NATCOR: Stochastic Modelling Queueing Theory II Chris Kirkbride Management Science 2017 Overview of Today s Sessions I Introduction to Queueing Modelling II Multiclass Queueing Models III Queueing Control
More informationWeek 5: Markov chains Random access in communication networks Solutions
Week 5: Markov chains Random access in communication networks Solutions A Markov chain model. The model described in the homework defines the following probabilities: P [a terminal receives a packet in
More informationIntroduction to Queuing Networks Solutions to Problem Sheet 3
Introduction to Queuing Networks Solutions to Problem Sheet 3 1. (a) The state space is the whole numbers {, 1, 2,...}. The transition rates are q i,i+1 λ for all i and q i, for all i 1 since, when a bus
More informationJ. MEDHI STOCHASTIC MODELS IN QUEUEING THEORY
J. MEDHI STOCHASTIC MODELS IN QUEUEING THEORY SECOND EDITION ACADEMIC PRESS An imprint of Elsevier Science Amsterdam Boston London New York Oxford Paris San Diego San Francisco Singapore Sydney Tokyo Contents
More informationStability of the two queue system
Stability of the two queue system Iain M. MacPhee and Lisa J. Müller University of Durham Department of Mathematical Science Durham, DH1 3LE, UK (e-mail: i.m.macphee@durham.ac.uk, l.j.muller@durham.ac.uk)
More informationAdventures in Stochastic Processes
Sidney Resnick Adventures in Stochastic Processes with Illustrations Birkhäuser Boston Basel Berlin Table of Contents Preface ix CHAPTER 1. PRELIMINARIES: DISCRETE INDEX SETS AND/OR DISCRETE STATE SPACES
More informationSTABILIZATION OF AN OVERLOADED QUEUEING NETWORK USING MEASUREMENT-BASED ADMISSION CONTROL
First published in Journal of Applied Probability 43(1) c 2006 Applied Probability Trust STABILIZATION OF AN OVERLOADED QUEUEING NETWORK USING MEASUREMENT-BASED ADMISSION CONTROL LASSE LESKELÄ, Helsinki
More informationMatrix analytic methods. Lecture 1: Structured Markov chains and their stationary distribution
1/29 Matrix analytic methods Lecture 1: Structured Markov chains and their stationary distribution Sophie Hautphenne and David Stanford (with thanks to Guy Latouche, U. Brussels and Peter Taylor, U. Melbourne
More informationMAT SYS 5120 (Winter 2012) Assignment 5 (not to be submitted) There are 4 questions.
MAT 4371 - SYS 5120 (Winter 2012) Assignment 5 (not to be submitted) There are 4 questions. Question 1: Consider the following generator for a continuous time Markov chain. 4 1 3 Q = 2 5 3 5 2 7 (a) Give
More informationExamples of Countable State Markov Chains Thursday, October 16, :12 PM
stochnotes101608 Page 1 Examples of Countable State Markov Chains Thursday, October 16, 2008 12:12 PM Homework 2 solutions will be posted later today. A couple of quick examples. Queueing model (without
More informationQueueing Theory II. Summary. ! M/M/1 Output process. ! Networks of Queue! Method of Stages. ! General Distributions
Queueing Theory II Summary! M/M/1 Output process! Networks of Queue! Method of Stages " Erlang Distribution " Hyperexponential Distribution! General Distributions " Embedded Markov Chains M/M/1 Output
More informationLecture 20: Reversible Processes and Queues
Lecture 20: Reversible Processes and Queues 1 Examples of reversible processes 11 Birth-death processes We define two non-negative sequences birth and death rates denoted by {λ n : n N 0 } and {µ n : n
More informationDesign and evaluation of overloaded service systems with skill based routing, under FCFS policies
Design and evaluation of overloaded service systems with skill based routing, under FCFS policies Ivo Adan Marko Boon Gideon Weiss April 2, 2013 Abstract We study an overloaded service system with servers
More informationQueuing Theory. Richard Lockhart. Simon Fraser University. STAT 870 Summer 2011
Queuing Theory Richard Lockhart Simon Fraser University STAT 870 Summer 2011 Richard Lockhart (Simon Fraser University) Queuing Theory STAT 870 Summer 2011 1 / 15 Purposes of Today s Lecture Describe general
More informationTECHNISCHE UNNERSITEIT EINDHOVEN Faculteit Wiskunde en Informatica
TECHNISCHE UNNERSITEIT EINDHOVEN Faculteit Wiskunde en Informatica Memorandum COSOR 91-24 Matrix-geometric analysis of the shortest queue problem with threshold jockeying I.J.B.F. Adan W.H.M. Zijm Eindhoven
More informationStructured Markov Chains
Structured Markov Chains Ivo Adan and Johan van Leeuwaarden Where innovation starts Book on Analysis of structured Markov processes (arxiv:1709.09060) I Basic methods Basic Markov processes Advanced Markov
More informationOn Tandem Blocking Queues with a Common Retrial Queue
On Tandem Blocking Queues with a Common Retrial Queue K. Avrachenkov U. Yechiali Abstract We consider systems of tandem blocking queues having a common retrial queue. The model represents dynamics of short
More informationExact Statistics of a Markov Chain trhough Reduction in Number of States: Marco Aurelio Alzate Monroy Universidad Distrital Francisco José de Caldas
Exact Statistics of a Markov Chain trhough Reduction in Number of States: A Satellite On-board Switching Example Marco Aurelio Alzate Monroy Universidad Distrital Francisco José de Caldas The general setting
More informationCOMP9334 Capacity Planning for Computer Systems and Networks
COMP9334 Capacity Planning for Computer Systems and Networks Week 2: Operational Analysis and Workload Characterisation COMP9334 1 Last lecture Modelling of computer systems using Queueing Networks Open
More informationNote special lecture series by Emmanuel Candes on compressed sensing Monday and Tuesday 4-5 PM (room information on rpinfo)
Formulation of Finite State Markov Chains Friday, September 23, 2011 2:04 PM Note special lecture series by Emmanuel Candes on compressed sensing Monday and Tuesday 4-5 PM (room information on rpinfo)
More informationLogistics. All the course-related information regarding
Logistics All the course-related information regarding - grading - office hours - handouts, announcements - class project: this is required for 384Y is posted on the class website Please take a look at
More informationMarkov Chains. X(t) is a Markov Process if, for arbitrary times t 1 < t 2 <... < t k < t k+1. If X(t) is discrete-valued. If X(t) is continuous-valued
Markov Chains X(t) is a Markov Process if, for arbitrary times t 1 < t 2
More informationReadings: Finish Section 5.2
LECTURE 19 Readings: Finish Section 5.2 Lecture outline Markov Processes I Checkout counter example. Markov process: definition. -step transition probabilities. Classification of states. Example: Checkout
More informationOn Tandem Blocking Queues with a Common Retrial Queue
On Tandem Blocking Queues with a Common Retrial Queue K. Avrachenkov U. Yechiali Abstract We consider systems of tandem blocking queues having a common retrial queue, for which explicit analytic results
More informationRecap. Probability, stochastic processes, Markov chains. ELEC-C7210 Modeling and analysis of communication networks
Recap Probability, stochastic processes, Markov chains ELEC-C7210 Modeling and analysis of communication networks 1 Recap: Probability theory important distributions Discrete distributions Geometric distribution
More informationA Two-Queue Polling Model with Two Priority Levels in the First Queue
A Two-Queue Polling Model with Two Priority Levels in the First Queue arxiv:1408.0110v1 [math.pr] 1 Aug 2014 M.A.A. Boon marko@win.tue.nl I.J.B.F. Adan iadan@win.tue.nl May, 2008 Abstract O.J. Boxma boxma@win.tue.nl
More informationA.Piunovskiy. University of Liverpool Fluid Approximation to Controlled Markov. Chains with Local Transitions. A.Piunovskiy.
University of Liverpool piunov@liv.ac.uk The Markov Decision Process under consideration is defined by the following elements X = {0, 1, 2,...} is the state space; A is the action space (Borel); p(z x,
More informationLinear Model Predictive Control for Queueing Networks in Manufacturing and Road Traffic
Linear Model Predictive Control for ueueing Networks in Manufacturing and Road Traffic Yoni Nazarathy Swinburne University of Technology, Melbourne. Joint work with: Erjen Lefeber (manufacturing), Hai
More informationM/G/1 and Priority Queueing
M/G/1 and Priority Queueing Richard T. B. Ma School of Computing National University of Singapore CS 5229: Advanced Compute Networks Outline PASTA M/G/1 Workload and FIFO Delay Pollaczek Khinchine Formula
More informationSTABILIZATION OF AN OVERLOADED QUEUEING NETWORK USING MEASUREMENT-BASED ADMISSION CONTROL
Helsinki University of Technology Institute of Mathematics Research Reports Teknillisen korkeakoulun matematiikan laitoksen tutkimusraporttisarja Espoo 2004 A470 STABILIZATION OF AN OVERLOADED QUEUEING
More informationON THE NON-EXISTENCE OF PRODUCT-FORM SOLUTIONS FOR QUEUEING NETWORKS WITH RETRIALS
ON THE NON-EXISTENCE OF PRODUCT-FORM SOLUTIONS FOR QUEUEING NETWORKS WITH RETRIALS J.R. ARTALEJO, Department of Statistics and Operations Research, Faculty of Mathematics, Complutense University of Madrid,
More information18.440: Lecture 33 Markov Chains
18.440: Lecture 33 Markov Chains Scott Sheffield MIT 1 Outline Markov chains Examples Ergodicity and stationarity 2 Outline Markov chains Examples Ergodicity and stationarity 3 Markov chains Consider a
More informationPart I Stochastic variables and Markov chains
Part I Stochastic variables and Markov chains Random variables describe the behaviour of a phenomenon independent of any specific sample space Distribution function (cdf, cumulative distribution function)
More informationComp 204: Computer Systems and Their Implementation. Lecture 11: Scheduling cont d
Comp 204: Computer Systems and Their Implementation Lecture 11: Scheduling cont d 1 Today Scheduling algorithms continued Shortest remaining time first (SRTF) Priority scheduling Round robin (RR) Multilevel
More informationLecture 10: Semi-Markov Type Processes
Lecture 1: Semi-Markov Type Processes 1. Semi-Markov processes (SMP) 1.1 Definition of SMP 1.2 Transition probabilities for SMP 1.3 Hitting times and semi-markov renewal equations 2. Processes with semi-markov
More informationStrategic Dynamic Jockeying Between Two Parallel Queues
Strategic Dynamic Jockeying Between Two Parallel Queues Amin Dehghanian 1 and Jeffrey P. Kharoufeh 2 Department of Industrial Engineering University of Pittsburgh 1048 Benedum Hall 3700 O Hara Street Pittsburgh,
More informationRare Events in Random Walks and Queueing Networks in the Presence of Heavy-Tailed Distributions
Rare Events in Random Walks and Queueing Networks in the Presence of Heavy-Tailed Distributions Sergey Foss Heriot-Watt University, Edinburgh and Institute of Mathematics, Novosibirsk The University of
More informationLECTURE #6 BIRTH-DEATH PROCESS
LECTURE #6 BIRTH-DEATH PROCESS 204528 Queueing Theory and Applications in Networks Assoc. Prof., Ph.D. (รศ.ดร. อน นต ผลเพ ม) Computer Engineering Department, Kasetsart University Outline 2 Birth-Death
More information8. Statistical Equilibrium and Classification of States: Discrete Time Markov Chains
8. Statistical Equilibrium and Classification of States: Discrete Time Markov Chains 8.1 Review 8.2 Statistical Equilibrium 8.3 Two-State Markov Chain 8.4 Existence of P ( ) 8.5 Classification of States
More informationBranching-type polling systems with large setups
Branching-type polling systems with large setups E.M.M. Winands 1,2 1 Department of Mathematics and Computer cience 2 Department of Technology Management Technische Universiteit Eindhoven P.O. Box 513,
More informationMarkov Chain Model for ALOHA protocol
Markov Chain Model for ALOHA protocol Laila Daniel and Krishnan Narayanan April 22, 2012 Outline of the talk A Markov chain (MC) model for Slotted ALOHA Basic properties of Discrete-time Markov Chain Stability
More informationStochastic Processes
Stochastic Processes 8.445 MIT, fall 20 Mid Term Exam Solutions October 27, 20 Your Name: Alberto De Sole Exercise Max Grade Grade 5 5 2 5 5 3 5 5 4 5 5 5 5 5 6 5 5 Total 30 30 Problem :. True / False
More informationStability and Asymptotic Optimality of h-maxweight Policies
Stability and Asymptotic Optimality of h-maxweight Policies - A. Rybko, 2006 Sean Meyn Department of Electrical and Computer Engineering University of Illinois & the Coordinated Science Laboratory NSF
More informationNetworking = Plumbing. Queueing Analysis: I. Last Lecture. Lecture Outline. Jeremiah Deng. 29 July 2013
Networking = Plumbing TELE302 Lecture 7 Queueing Analysis: I Jeremiah Deng University of Otago 29 July 2013 Jeremiah Deng (University of Otago) TELE302 Lecture 7 29 July 2013 1 / 33 Lecture Outline Jeremiah
More informationQueueing networks: rare events and fast simulations
Queueing networks: rare events and fast simulations Denis Miretskiy Graduation committee Chairman prof.dr.ir. A.J. Mouthaan Promoters prof.dr. M.R.H. Mandjes prof.dr. R.J. Boucherie Co-promoter dr.ir.
More informationM.Sc. (MATHEMATICS WITH APPLICATIONS IN COMPUTER SCIENCE) M.Sc. (MACS)
No. of Printed Pages : 6 MMT-008 M.Sc. (MATHEMATICS WITH APPLICATIONS IN COMPUTER SCIENCE) M.Sc. (MACS) Term-End Examination 0064 December, 202 MMT-008 : PROBABILITY AND STATISTICS Time : 3 hours Maximum
More informationARTIFICIAL INTELLIGENCE MODELLING OF STOCHASTIC PROCESSES IN DIGITAL COMMUNICATION NETWORKS
Journal of ELECTRICAL ENGINEERING, VOL. 54, NO. 9-, 23, 255 259 ARTIFICIAL INTELLIGENCE MODELLING OF STOCHASTIC PROCESSES IN DIGITAL COMMUNICATION NETWORKS Dimitar Radev Svetla Radeva The paper presents
More informationData analysis and stochastic modeling
Data analysis and stochastic modeling Lecture 7 An introduction to queueing theory Guillaume Gravier guillaume.gravier@irisa.fr with a lot of help from Paul Jensen s course http://www.me.utexas.edu/ jensen/ormm/instruction/powerpoint/or_models_09/14_queuing.ppt
More informationMulti Stage Queuing Model in Level Dependent Quasi Birth Death Process
International Journal of Statistics and Systems ISSN 973-2675 Volume 12, Number 2 (217, pp. 293-31 Research India Publications http://www.ripublication.com Multi Stage Queuing Model in Level Dependent
More informationModelling Complex Queuing Situations with Markov Processes
Modelling Complex Queuing Situations with Markov Processes Jason Randal Thorne, School of IT, Charles Sturt Uni, NSW 2795, Australia Abstract This article comments upon some new developments in the field
More information1/2 1/2 1/4 1/4 8 1/2 1/2 1/2 1/2 8 1/2 6 P =
/ 7 8 / / / /4 4 5 / /4 / 8 / 6 P = 0 0 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 4 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 Andrei Andreevich Markov (856 9) In Example. 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 P (n) = 0
More informationEnvironment (E) IBP IBP IBP 2 N 2 N. server. System (S) Adapter (A) ACV
The Adaptive Cross Validation Method - applied to polling schemes Anders Svensson and Johan M Karlsson Department of Communication Systems Lund Institute of Technology P. O. Box 118, 22100 Lund, Sweden
More informationTHE INTERCHANGEABILITY OF./M/1 QUEUES IN SERIES. 1. Introduction
THE INTERCHANGEABILITY OF./M/1 QUEUES IN SERIES J. Appl. Prob. 16, 690-695 (1979) Printed in Israel? Applied Probability Trust 1979 RICHARD R. WEBER,* University of Cambridge Abstract A series of queues
More informationINDEX. production, see Applications, manufacturing
INDEX Absorbing barriers, 103 Ample service, see Service, ample Analyticity, of generating functions, 100, 127 Anderson Darling (AD) test, 411 Aperiodic state, 37 Applications, 2, 3 aircraft, 3 airline
More informationLecture Notes 8
14.451 Lecture Notes 8 Guido Lorenzoni Fall 29 1 Stochastic dynamic programming: an example We no turn to analyze problems ith uncertainty, in discrete time. We begin ith an example that illustrates the
More informationA PARAMETRIC DECOMPOSITION BASED APPROACH FOR MULTI-CLASS CLOSED QUEUING NETWORKS WITH SYNCHRONIZATION STATIONS
A PARAMETRIC DECOMPOSITION BASED APPROACH FOR MULTI-CLASS CLOSED QUEUING NETWORKS WITH SYNCHRONIZATION STATIONS Kumar Satyam and Ananth Krishnamurthy Department of Decision Sciences and Engineering Systems,
More informationThe Israeli Queue with a general group-joining policy 60K25 90B22
DOI 0007/s0479-05-942-2 3 4 5 6 7 8 9 0 2 3 4 The Israeli Queue with a general group-joining policy Nir Perel,2 Uri Yechiali Springer Science+Business Media New York 205 Abstract We consider a single-server
More informationContents LIST OF TABLES... LIST OF FIGURES... xvii. LIST OF LISTINGS... xxi PREFACE. ...xxiii
LIST OF TABLES... xv LIST OF FIGURES... xvii LIST OF LISTINGS... xxi PREFACE...xxiii CHAPTER 1. PERFORMANCE EVALUATION... 1 1.1. Performance evaluation... 1 1.2. Performance versus resources provisioning...
More informationSTOCHASTIC PROCESSES Basic notions
J. Virtamo 38.3143 Queueing Theory / Stochastic processes 1 STOCHASTIC PROCESSES Basic notions Often the systems we consider evolve in time and we are interested in their dynamic behaviour, usually involving
More information6.231 DYNAMIC PROGRAMMING LECTURE 7 LECTURE OUTLINE
6.231 DYNAMIC PROGRAMMING LECTURE 7 LECTURE OUTLINE DP for imperfect state info Sufficient statistics Conditional state distribution as a sufficient statistic Finite-state systems Examples 1 REVIEW: IMPERFECT
More informationMASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Electrical Engineering and Computer Science
MASSACHUSETTS INSTITUTE OF TECHNOLOGY Department of Electrical Engineering and Computer Science 6.262 Discrete Stochastic Processes Midterm Quiz April 6, 2010 There are 5 questions, each with several parts.
More informationPush and Pull Systems in a Dynamic Environment
Push and Pull Systems in a Dynamic Environment ichael Zazanis Dept. of IEOR University of assachusetts Amherst, A 0003 email: zazanis@ecs.umass.edu Abstract We examine Push and Pull production control
More informationMinicourse on: Markov Chain Monte Carlo: Simulation Techniques in Statistics
Minicourse on: Markov Chain Monte Carlo: Simulation Techniques in Statistics Eric Slud, Statistics Program Lecture 1: Metropolis-Hastings Algorithm, plus background in Simulation and Markov Chains. Lecture
More informationBuzen s algorithm. Cyclic network Extension of Jackson networks
Outline Buzen s algorithm Mean value analysis for Jackson networks Cyclic network Extension of Jackson networks BCMP network 1 Marginal Distributions based on Buzen s algorithm With Buzen s algorithm,
More informationarxiv: v1 [math.pr] 11 May 2018
FCFS Parallel Service Systems and Matching Models Ivo Adan a, Igor Kleiner b,, Rhonda Righter c, Gideon Weiss b,, a Eindhoven University of Technology b Department of Statistics, The University of Haifa,
More informationA NEW PROOF OF THE WIENER HOPF FACTORIZATION VIA BASU S THEOREM
J. Appl. Prob. 49, 876 882 (2012 Printed in England Applied Probability Trust 2012 A NEW PROOF OF THE WIENER HOPF FACTORIZATION VIA BASU S THEOREM BRIAN FRALIX and COLIN GALLAGHER, Clemson University Abstract
More informationA First Course in Stochastic Models. Henk C. Tijms Vrije Universiteit, Amsterdam, The Netherlands
A First Course in Stochastic Models Henk C. Tijms Vrije Universiteit, Amsterdam, The Netherlands A First Course in Stochastic Models A First Course in Stochastic Models Henk C. Tijms Vrije Universiteit,
More informationBatch Arrival Queuing Models with Periodic Review
Batch Arrival Queuing Models with Periodic Review R. Sivaraman Ph.D. Research Scholar in Mathematics Sri Satya Sai University of Technology and Medical Sciences Bhopal, Madhya Pradesh National Awardee
More informationSystem occupancy of a two-class batch-service queue with class-dependent variable server capacity
System occupancy of a two-class batch-service queue with class-dependent variable server capacity Jens Baetens 1, Bart Steyaert 1, Dieter Claeys 1,2, and Herwig Bruneel 1 1 SMACS Research Group, Dept.
More informationMATH 564/STAT 555 Applied Stochastic Processes Homework 2, September 18, 2015 Due September 30, 2015
ID NAME SCORE MATH 56/STAT 555 Applied Stochastic Processes Homework 2, September 8, 205 Due September 30, 205 The generating function of a sequence a n n 0 is defined as As : a ns n for all s 0 for which
More informationDynamic Control of a Tandem Queueing System with Abandonments
Dynamic Control of a Tandem Queueing System with Abandonments Gabriel Zayas-Cabán 1 Jungui Xie 2 Linda V. Green 3 Mark E. Lewis 1 1 Cornell University Ithaca, NY 2 University of Science and Technology
More informationDiscriminatory Processor Sharing Queues and the DREB Method
Lingnan University From the SelectedWorks of Prof. LIU Liming 2008 Discriminatory Processor Sharing Queues and the DREB Method Z. LIAN, University of Macau X. LIU, University of Macau Liming LIU, Hong
More informationNEW FRONTIERS IN APPLIED PROBABILITY
J. Appl. Prob. Spec. Vol. 48A, 209 213 (2011) Applied Probability Trust 2011 NEW FRONTIERS IN APPLIED PROBABILITY A Festschrift for SØREN ASMUSSEN Edited by P. GLYNN, T. MIKOSCH and T. ROLSKI Part 4. Simulation
More informationTU/e technische universiteit eindhoven
TU/e technische universiteit eindhoven SPaR-Report 24-10 A two node Jackson network with infinite supply of work LJ.B.F. Adan G. Weiss SPaR-Report Reports in Statistics, Probability and Operations Research
More informationOn a queueing model with service interruptions
On a queueing model with service interruptions Onno Boxma Michel Mandjes Offer Kella Abstract Single-server queues in which the server takes vacations arise naturally as models for a wide range of computer,
More informationSystem Time Distribution of Dynamic Traveling Repairman Problem under the PART-n-TSP Policy
System Time Distribution of Dynamic Traveling Repairman Problem under the PART-n-TSP Policy Jiangchuan Huang and Raja Sengupta Abstract We propose the PART-n-TSP policy for the Dynamic Traveling Repairman
More informationTime Reversibility and Burke s Theorem
Queuing Analysis: Time Reversibility and Burke s Theorem Hongwei Zhang http://www.cs.wayne.edu/~hzhang Acknowledgement: this lecture is partially based on the slides of Dr. Yannis A. Korilis. Outline Time-Reversal
More informationA product form solution to a system with multi-type jobs and multi-type servers Visschers, J.W.C.H.; Adan, I.J.B.F.; Weiss, G.
A product form solution to a system with multi-type jobs and multi-type servers Visschers, JWCH; Adan, IJBF; Weiss, G Published: 01/01/2011 Document Version Publisher s PDF, also known as Version of Record
More informationPITMAN S 2M X THEOREM FOR SKIP-FREE RANDOM WALKS WITH MARKOVIAN INCREMENTS
Elect. Comm. in Probab. 6 (2001) 73 77 ELECTRONIC COMMUNICATIONS in PROBABILITY PITMAN S 2M X THEOREM FOR SKIP-FREE RANDOM WALKS WITH MARKOVIAN INCREMENTS B.M. HAMBLY Mathematical Institute, University
More information