• Computer Lab
• Damon Wischik
• Network Performance
• Reading

Further reading

Articles mentioned in the course

• Using the TCP fixed point equations to calculate throughputs:
  • Fixed-point models for the end-to-end performance analysis of IP networks, Gibbens et al., 2000.
  • Fixed Point Approximation for TCP behavior in an AQM Network, T.Bu and D.Towsley; 2001.
• Buffer size and TCP:
  • Sizing router buffers, Guido Appenzeller, Isaac Keslassy, Nick McKeown, 2004 [pdf]
  • Buffer size for core routers, D.Wischik and N.McKeown, 2005.
• Models for a self-managed Internet, F.Kelly, 1999.
• Traffic engineering versus content distribution: a game theoretic perspective, D.DiPalantino and R.Johari, 2009
• A Study of Networks Simulation Efficiency: Fluid Simulation vs. Packet-level Simulation Benyuan Liu, Daniel R. Figueiredo, Yang Guo, Jim Kurose, Don Towsley [pdf]
• The fourth quadrant: a map of the limits of statistics, Nassim Taleb. Edge
• The mathematics of traffic in networks, F. Kelly. Princeton companion to mathematics.
• SybilGuard: defending against Sybil attacks via social networks, H. Yu, M. Kaminsky, P. B. Gibbons, A. Flaxman. SIGCOMM 2006. See also the public review.
• A Brief History of Generative Models for Power Law and Lognormal Distributions, M.Mitzenmacher, Internet Mathematics 2004.
• Wide-area traffic: the failure of Poisson modeling, V. Paxson and S. Floyd. IEEE/ACM Transactions on Networking, 1995.
• An empirical study of operating systems errors, A. Chou, J. Yang, B. Chelf, S. Hallem and D. Engler, Symposium on Operating Systems Principles, 2001.
• The anatomy of a large-scale hypertextual web search engine, S. Brin and L. Page. WWW7 / Computer Networks, 1998.
• Inside PageRank, Monica Bianchini, Marco Gori, Franco Scarselli. ACM Transactions on Internet Technology, 2005.
• Loss Networks, Frank Kelly. Annals of Applied Probability, 1991.
• Characteristics of WWW client-based traces, C.A. Cunha, A. Bestavros, M.E. Crovella. Technical report TR-95-010, Boston University Dept of CS, 1995.
• Congestion avoidance and control, Van Jacobson, 1988.

Related books and courses

Some courses and books which cover similar material to this course, though usually with more mathematics:

	Network Performance lecture notes from 2010–2011 [pdf], in which I taught Markov models in more detail
	Stochastic Networks, a Cambridge Part III lecture course taught by Frank Kelly
	Communication Network Analysis course, taught by Bruce Hajek at UIUC
	Analytical performance modeling for computer systems, Y.C. Tay (Morgan Claypool),
	Operations research: an introduction, Hamdy A. Taha, [amazon]
	Simulation modeling and analysis, Law and Kelton, 2000.

An brilliant guide to how to think about visualizing data:

The visual display of quantitative information, E. Tufte, [many copies in libraries].

Books from which to learn probability:

	A modern introduction to probability and statistics: understanding why and how, F.M.Dekking, C.Kraaikamp, H.P.Lopuhaa, L.E.Meester (Springer). [1 copy in science library] [1 copy borrowable from DJW] [amazon]. Very clear presentation; chapters 1—9 all relevant.
	Probability and computing: randomized algorithms and probabilistic analysis, M.Mitzenmacher and E.Upfal (Cambridge) [amazon]. Chapters 1,2,7 are a brisk and well-written introduction to probability. The rest of the book is fascinating and very relevant to computer scientists.
	Probability via expectation, P.Whittle (Springer). [3 copies in science library] [amazon]. Idiosyncratic and very thoughtful. Very readable introduction—see pages 1–20, 39–60.
	Probability and statistics by example: basic probability and statistics, Y.Suhov and M.Kelbert (Cambridge) [amazon]. Thorough and dense to learn from, but does have a wealth of good exercises.
	Introduction to probability and statistics, published by Schaum's Outlines, ISBN 978-0070380844 [amazon] [1 copy in science library]. An introduction to probability suitable for first-year undergraduates.
	Probability Demystified by Allan G. Bluman, published by McGraw-Hill, ISBN 978-0071445498 [amazon]. A good introduction to the basics with plenty of worked questions.
	Complete Advanced Level Mathematics—Statistics, published by Nelson Thornes, ISBN 978-0748735600 [amazon]. A clear and straightforward guide to A-level probability and statistics.

Books from which to revise calculus:

	Beginning Calculus by Elliott Mendelson, published by Schaum's Outlines, ISBN 978-0071635356 [amazon]. A slightly more sophisticated introduction to calculus, well written, somewhat dense.
	Calculus for Dummies by Mark Ryan, published by Wiley, ISBN 978-0764524981 [amazon]. Sometimes too wordy, but clear enough.
	AS Use of Maths—Calculus, published by Nelson Thornes, ISBN 978-0748769780 [amazon]. A clear and straightforward guide to A-level calculus.