Provides the mathematical, stochastic and graph theoretic methods to analyse the performance and robustness of complex networks and systems.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Piet Van Mieghem is a Professor at the Delft University of Technology with a chair in telecommunication networks, and chairman of the Network Architectures and Services (NAS) section. His main research interests lie in the modeling and analysis of complex networks (such as biological, brain, social, infrastructural, and so on) and in new Internet-like architectures and algorithms for future communications networks.
Inhaltsangabe
1. Introduction Part I. Probability Theory: 2. Random variables 3. Basic distributions 4. Correlation 5. Inequalities 6. Limit laws Part II. Stochastic Processes: 7. The Poisson process 8. Renewal theory 9. Discrete-time Markov chains 10. Continuous-time Markov chains 11. Applications of Markov chains 12. Branching processes 13. General queueing theory 14. Queueing models Part III. Network Science: 15. General characteristics of graphs 16. The shortest path problem 17. Epidemics in networks 18. The efficiency of multicast 19. The hopcount and weight to an anycast group Appendix A. A summary of matrix theory Appendix B. Solutions to problems.
1. Introduction Part I. Probability Theory: 2. Random variables 3. Basic distributions 4. Correlation 5. Inequalities 6. Limit laws Part II. Stochastic Processes: 7. The Poisson process 8. Renewal theory 9. Discrete-time Markov chains 10. Continuous-time Markov chains 11. Applications of Markov chains 12. Branching processes 13. General queueing theory 14. Queueing models Part III. Network Science: 15. General characteristics of graphs 16. The shortest path problem 17. Epidemics in networks 18. The efficiency of multicast 19. The hopcount and weight to an anycast group Appendix A. A summary of matrix theory Appendix B. Solutions to problems.
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