Network Algorithmics. An Interdisciplinary Approach to Designing Fast Networked Devices. Edition No. 2

Table of Contents

Part I: Rules of the Game 1. Introducing Network Algorithmics 2. Network Implementation Models 3. Fifteen Implementation Principles 4. Principles in Action

Part II: Playing with Endnodes 5. Copying Data 6. Transferring Control 7. Maintaining Timers 8. Demultiplexing 9. Protocol Processing

Part III: Playing with Routers 10. Exact-Match Lookups 11. Prefix-Match Lookups 12. Packet Classification 13. Switching 14. Scheduling Packets 15. Routers as Distributed Systems

Part IV: Endgame 16. Measuring Network Traffic 17. Network Security 18. Conclusions

Appendix: Detailed Models

Authors

George Varghese Jonathan B. Postel Professor of Networking, University of California, Los Angeles, California, USA. George Varghese is a widely recognized authority on the art of network protocol implementation. Currently he holds the Jonathan B. Postel Chair of Networking at the University of California, Los Angeles. Earlier he was a Partner at Microsoft Research, and served as a professor in the departments of Computer Science at UC-San Diego and Washington University. He was elected to American Academy of Arts and Sciences in 2022, to the Internet Hall of Fame in 2021, to the National Academy of Inventors in 2020, to the National Academy of Engineering in 2017, and as a Fellow of the ACM in 2002. He co-founded a startup called NetSift in 2004 that was acquired by Cisco in 2005. With colleagues, he holds 26 patents in the general field of network algorithmics. Several algorithms that he helped develop have found their way into commercial systems, including Linux (timing wheels), the Cisco GSR (DRR), and MS Windows (IP lookups). Varghese has written more than 100 papers on networking, computer architecture, genomics, and databases. Jun Xu Professor in the School of Computer Science at Georgia Institute of Technology, Atlanta, Georgia, USA. Jun Xu has been a Professor in the School of Computer Science at Georgia Tech since 2000. He has worked on the design and analysis of network algorithmics for over two decades. He was instrumental in introducing randomization to the design of network algorithmics. His network algorithmics research jointly with his former students has garnered Best Student Paper Awards in conferences such as ACM Sigmetrics. In the past three years, he has ventured into an emerging research field called big data algorithmics that includes topics such as locality sensitive hashing (LSH) techniques for supporting similarity search in database and machine learning applications, and follows the same guiding principle of network algorithmics: combining algorithmic thinking with systems thinking. He has been an ACM Distinguished Scientist since 2010.