Queueing Networks and Markov Chains (PDF)

Preface to the Second Edition. Preface to the First Edition. 1. Introduction. 1.1 Motivation. 1.2 Methodological Background. 1.3 Basics of Probability and Statistics. 2. Markov Chains. 2.1 Markov Processes. 2.2 Performance Measures. 2.3 Generation Methods. 3. Steady-State Solutions of Markov Chains. 3.1 Solution for a Birth Death Process. 3.2 Matrix-Geometric Method: Quasi-Birth-Death Process. 3.3 Hessenberg Matrix: Non-Markovian Queues. 3.4 Numerical Solution: Direct Methods. 3.5 Numerical Solution: Iterative Methods. 3.6 Comparison of Numerical Solution Methods. 4. Steady-State Aggregation/Disaggregation Methods. 4.1 Courtois' Approximate Method. 4.2 Takahashi's Iterative Method. 5. Transient Solution of Markov Chains. 5.1 Transient Analysis Using Exact Methods. 5.2 Aggregation of Stiff Markov Chains. 6. Single Station Queueing Systems. 6.1 Notation. 6.2 Markovian Queues. 6.3 Non-Markovian Queues. 6.4 Priority Queues. 6.5 Asymmetric Queues. 6.6 Queues with Batch Service and Batch Arrivals. 6.7 Retrial Queues. 6.8 Special Classes of Point Arrival Processes. 7. Queueing Networks. 7.1 Definitions and Notation. 7.2 Performance Measures. 7.3 Product-Form Queueing Networks. 8. Algorithms for Product-Form Networks. 8.1 The Convolution Algorithm. 8.2 The Mean Value Analysis. 8.3 Flow Equivalent Server Method. 8.4 Summary. 9. Approximation Algorithms for Product-Form Networks. 9.1 Approximations Based on the MVA. 9.2 Summation Method. 9.3 Bottapprox Method. 9.4 Bounds Analysis. 9.5 Summary. 10. Algorithms for Non-Product-Form Networks. 10.1 Nonexponential Distributions. 10.2 Different Service Times at FCFS Nodes. 10.3 Priority Networks. 10.4 Simultaneous Resource Possession. 10.5 Prograrns with Internal Concurrency. 10.6 Parallel Processing. 10.7 Networks with Asymmetric Nodes. 10.8 Networks with Blocking. 10.9 Networks with Batch Service. 11. Discrete-Event Simulation. 11.1 Introduction to Simulation. 11.2 Simulative or Analytic Solution? 11.3 Classification of

GUNTER BOLCH, PhD, is Academic Director in the Department of
Computer Science, University of Erlangen. He is a coauthor of
MOSEL, a powerful specification language based on Markov chains.He
has published five textbooks and more than 130 articles on
performance modeling of computer and communication systems and
applications.

STEFAN GREINER, PhD, is Researcher at the DaimlerChrysler
AG. He is coauthor of MOSEL and the recipient of the best paper
award at the ESS94conference.

HERMANN de MEER, PhD, is Professor in the Faculty of
Mathematicsand Computer Science, University of Passau. He holds a
chair in the Computer Networking and Communications Department; has
published more than eighty peer-reviewed articles on performance
modeling, computer networking, self-organization, quality of
service, and peer-to-peer systems; and holds several international
patents on related topics.

KISHOR S. TRIVEDI, PhD, is Chaired Professor in the
Department of Electrical and Computer Engineering and the
Department of Computer Science, Duke University. A Fellow of IEEE,
he is the author of the bestselling textbook Probability and
Statistics with Reliability, Queueing, and Computer Science
Applications, Second Edition, published by Wiley.

Dieses eBook können Sie uneingeschränkt auf allen Geräten der tolino Familie lesen. Zum Lesen auf sonstigen eReadern und am PC benötigen Sie eine Adobe ID.