Online Algorithms

A rigorous and comprehensive introduction to online algorithms in a pedagogy-rich, readily accessible form for students.

Rahul Vaze (Author)

9781009349185, Cambridge University Press

Paperback / softback, published 16 November 2023

488 pages
23.7 x 18.3 x 2.3 cm, 0.71 kg

Online algorithms are a rich area of research with widespread applications in scheduling, combinatorial optimization, and resource allocation problems. This lucid textbook provides an easy but rigorous introduction to online algorithms for graduate and senior undergraduate students. In-depth coverage of most of the important topics is presented with special emphasis on elegant analysis. The book starts with classical online paradigms like the ski-rental, paging, list-accessing, bin packing, where performance of online algorithms is studied under the worst-case input and moves on to newer paradigms like 'beyond worst case', where online algorithms are augmented with predictions using machine learning algorithms. The book goes on to cover multiple applied problems such as routing in communication networks, server provisioning in cloud systems, communication with energy harvested from renewable sources, and sub-modular partitioning. Finally, a wide range of solved examples and practice exercises are included, allowing hands-on exposure to the concepts.

Preface
Acknowledgements
Notations
Chapter 1. Introduction
Chapter 2. Ski-Rental
Chapter 3. List Accessing
Chapter 4. Bin-Packing
Chapter 5. Paging
Chapter 6. Metrical Task System
Chapter 7. Secretary Problem
Chapter 8. Knapsack
Chapter 9. Bipartite Matching
Chapter 10. Primal–Dual Technique
Chapter 11. Facility Location and k-Means Clustering
Chapter 12. Load Balancing
Chapter 13. Scheduling to Minimize Flow Time (Delay)
Chapter 14. Scheduling with Speed Scaling
Chapter 15. Scheduling to Minimize Energy with Job Deadlines
Chapter 16. Travelling Salesman
Chapter 17. Convex Optimization (Server Provisioning in Cloud Computing)
Chapter 18. Multi-Commodity Flow Routing
Chapter 19. Resource Constrained Scheduling (Energy Harvesting Communication)
Chapter 20. Submodular Partitioning for Welfare Maximization
Appendix 1. Types of Adversaries and Their Relationships
Appendix 2. KKT Conditions for Convex Optimization Problems
Bibliography
Index.

Subject Areas: Algorithms & data structures [UMB]