Large Deviations For Performance Analysis

Originally published in 1995, Large Deviations For Performance Analysis develops the theory of large deviations from the beginning through recent results on the theory for processes with boundaries and looks at a collection of applications developed at Bell Laboratories.

Alan Weiss, Adam Shwartz

What this Book Is, and What It Is Not 1. Large Deviations of Random Variables 2. General Principles 3. Random Walks, Branching Processes 4. Poisson and Related Processes 5. Large Deviations for Processes 6. Freidlin-Wentzell Theory 7. Applications and Extensions 8. Boundary Theory Applications 9. Allocating Independent Subtasks 10. Parallel Algorithms: Rollback 11. The M/M/1 Queue 12. Erlang's Mode 13. The Anick-Mitra-Sondhi Model 14. Aloha 15. Priority Queues 16. The Flatto-Hahn-Wright model A. Analysis and Probability B. Discrete-Space Markov Processes C. Calculus of Variations D. Large Deviations Techniques References Index