2 September, 2001J. Hagstrom, U. of Illinois1 Queuing Systems Jane Hagstrom.

Slides:



Advertisements
Similar presentations
Waiting Line Management
Advertisements

Lecture 3 Concepts of Discrete-Event Simulation. 2 Discrete Event Model  In the discrete approach to system simulation, state changes in the physical.
1 ELEN 602 Lecture 8 Review of Last lecture –HDLC, PPP –TDM, FDM Today’s lecture –Wavelength Division Multiplexing –Statistical Multiplexing –Preliminary.
Model Antrian By : Render, ect. Outline  Characteristics of a Waiting-Line System.  Arrival characteristics.  Waiting-Line characteristics.  Service.
#11 QUEUEING THEORY Systems Fall 2000 Instructor: Peter M. Hahn
Queuing Systems Chapter 17.
1 Performance Evaluation of Computer Networks Objectives  Introduction to Queuing Theory  Little’s Theorem  Standard Notation of Queuing Systems  Poisson.
Lecture 11 Queueing Models. 2 Queueing System  Queueing System:  A system in which items (or customers) arrive at a station, wait in a line (or queue),
1 Queueing Theory H Plan: –Introduce basics of Queueing Theory –Define notation and terminology used –Discuss properties of queuing models –Show examples.
Management of Waiting Lines
Queueing Network Model. Single Class Model Open - Infinite stream of arriving customers Closed - Finite population eg Intranet users Indistinguishable.
Queueing Theory Professor Stephen Lawrence Leeds School of Business University of Colorado Boulder, CO
7/3/2015© 2007 Raymond P. Jefferis III1 Queuing Systems.
Lecture 4 Mathematical and Statistical Models in Simulation.
Internet Queuing Delay Introduction How many packets in the queue? How long a packet takes to go through?
WAITING LINES The study of waiting lines, called queuing theory, is one of the most widely used and oldest management science techniques. The three basic.
Queuing Networks. Input source Queue Service mechanism arriving customers exiting customers Structure of Single Queuing Systems Note: 1.Customers need.
Introduction to Management Science
A bit on Queueing Theory: M/M/1, M/G/1, GI/G/1 Yoni Nazarathy * EURANDOM, Eindhoven University of Technology, The Netherlands. (As of Dec 1: Swinburne.
8/22/01J. Hagstrom, U. of Illinois1 Processing Systems Jane Hagstrom.
McGraw-Hill/Irwin Copyright © 2008 by The McGraw-Hill Companies, Inc. All rights reserved. Service Processes CHAPTER 5.
Copyright ©: Nahrstedt, Angrave, Abdelzaher, Caccamo1 Queueing Systems.
Queuing models Basic definitions, assumptions, and identities Operational laws Little’s law Queuing networks and Jackson’s theorem The importance of think.
Queuing Models. © 2002 Prentice-Hall, IncCh 9-2 Stay in Queue: Short Video &feature=related
Introduction to Operations Research
McGraw-Hill/Irwin © 2006 The McGraw-Hill Companies, Inc., All Rights Reserved. 1.
Chapter 20 Queuing Theory to accompany Operations Research: Applications and Algorithms 4th edition by Wayne L. Winston Copyright (c) 2004 Brooks/Cole,
Queuing Theory Basic properties, Markovian models, Networks of queues, General service time distributions, Finite source models, Multiserver queues Chapter.
Queueing Theory What is a queue? Examples of queues: Grocery store checkout Fast food (McDonalds – vs- Wendy’s) Hospital Emergency rooms Machines waiting.
TexPoint fonts used in EMF.
SIMULATION EXAMPLES QUEUEING SYSTEMS.
Modeling and Simulation Queuing theory
Chapter 20 Queuing Theory to accompany Operations Research: Applications and Algorithms 4th edition by Wayne L. Winston Copyright (c) 2004 Brooks/Cole,
M/M/1 Queues Customers arrive according to a Poisson process with rate. There is only one server. Service time is exponential with rate  j-1 jj+1...
CS352 - Introduction to Queuing Theory Rutgers University.
Maciej Stasiak, Mariusz Głąbowski Arkadiusz Wiśniewski, Piotr Zwierzykowski Model of the Nodes in the Packet Network Chapter 10.
1 Ardavan Asef-Vaziri Sep-09Operations Management: Waiting Lines3 Example: The arrival rate to a GAP store is 6 customers per hour and has Poisson distribution.
(C) J. M. Garrido1 Objects in a Simulation Model There are several objects in a simulation model The activate objects are instances of the classes that.
Introduction Definition M/M queues M/M/1 M/M/S M/M/infinity M/M/S/K.
Delays  Deterministic Assumes “error free” type case Delay only when demand (known) exceeds capacity (known)  Stochastic Delay may occur any time Random.
Queuing Theory.  Queuing Theory deals with systems of the following type:  Typically we are interested in how much queuing occurs or in the delays at.
SIMULATION EXAMPLES. Monte-Carlo (Static) Simulation Estimating profit on a sale promotion Estimating profit on a sale promotion Estimating profit on.
Basic Queuing Insights Nico M. van Dijk “Why queuing never vanishes” European Journal of Operational Research 99 (1997)
Mohammad Khalily Islamic Azad University.  Usually buffer size is finite  Interarrival time and service times are independent  State of the system.
Simple Queueing Theory: Page 5.1 CPE Systems Modelling & Simulation Techniques Topic 5: Simple Queueing Theory  Queueing Models  Kendall notation.
QUEUING THEORY 1.  - means the number of arrivals per second   - service rate of a device  T - mean service time for each arrival   = ( ) Utilization,
Modeling and Simulation
Managerial Decision Making Chapter 13 Queuing Models.
Queuing Theory. Model Customers arrive randomly in accordance with some arrival time distribution. One server services customers in order of arrival.
© 2006 Prentice Hall, Inc.D – 1 Operations Management Module D – Waiting-Line Models © 2006 Prentice Hall, Inc. PowerPoint presentation to accompany Heizer/Render.
McGraw-Hill/Irwin Copyright © 2009 by The McGraw-Hill Companies, Inc. All rights reserved.
Modeling and Simulation (An Introduction)
McGraw-Hill/Irwin ©2009 The McGraw-Hill Companies, All Rights Reserved
Discrete Event Simulation
Internet Queuing Delay Introduction
Demo on Queuing Concepts
SIMULATION EXAMPLES QUEUEING SYSTEMS.
ECE 358 Examples #1 Xuemin (Sherman) Shen Office: EIT 4155
Internet Queuing Delay Introduction
Queuing models Basic definitions, assumptions, and identities
Chapter 20 Queuing Theory
More Explanation of an example in chapter4
Queuing models Basic definitions, assumptions, and identities
TexPoint fonts used in EMF.
SIMULATION EXAMPLES QUEUEING SYSTEMS.
Queuing Theory By: Brian Murphy.
Mitchell Jareo MAT4340 – Operations Research Dr. Bauldry
Concepts In Discrete-Event Simulation
Queueing networks.
SIMULATION EXAMPLES QUEUEING SYSTEMS.
Presentation transcript:

2 September, 2001J. Hagstrom, U. of Illinois1 Queuing Systems Jane Hagstrom

2 September, 2001J. Hagstrom, U. of Illinois2 What is a Queuing System? A queuing system consists of one or more servers together with queues where entities can await service. A complex queuing system is described as a queuing network. Usually, travel times between servers are not of interest in a queuing system.

2 September, 2001J. Hagstrom, U. of Illinois3 Simple Queuing System Has one or more identical servers, any of which can provide the same service Has a single queue with unlimited capacity Entities arrive singly into the system There is an unlimited supply of entities Entities are taken out of the queue for service on a First-In First-Out basis

2 September, 2001J. Hagstrom, U. of Illinois4 Examples of Simple Queuing Systems Ticket-taking at the movie theater Checkout system at storefront grocery Teller system at bank

2 September, 2001J. Hagstrom, U. of Illinois5 Terminology Concerning Time Duration – a length of time –Example: They remained in Pearl Harbor for the duration of the war Epoch – a moment in time –Example: A significant epoch in the history of the U.S. was the day of Victory in Japan

2 September, 2001J. Hagstrom, U. of Illinois6 Basic Queuing System Terminology Server gives service over a period of time called the service duration. An arrival arrives requiring service from the server. The time between arrivals is the interarrival duration. If an arrival arrives at an epoch when the server(s) is busy taking care of previous arrivals, the arrival waits in a queue.

2 September, 2001J. Hagstrom, U. of Illinois7 Simple Queuing System Arrival at Queue Server Departure

2 September, 2001J. Hagstrom, U. of Illinois8 Notation for Simple Queuing System ( arrival distribution )/( service distribution )/ number of servers Examples: –M/M/1 Interarrival duration is distributed according to an exponential distribution; service duration is distributed according to an exponential distribution; number of servers is 1. –D/T/3 Interarrival duration is deterministic; service duration is distributed according to a triangular distribution; number of servers is 3.

2 September, 2001J. Hagstrom, U. of Illinois9 Manufacturing System Server is machining center Arrival is unit of Product Queue holds units of product awaiting service at the machining center

2 September, 2001J. Hagstrom, U. of Illinois10