## Network Congestion Control, M. Welzl, Wiley 2005. (A Book Review)

Posted by David Mayer on August 31, 2007

* Network Congestion Control: Managing Internet Traffic* — Michael Welzl (Wiley Series on Communications Networking & Distributed Systems 2005).

The control of Internet congestion is a field entangling numerous research, engineering and economic topics, each of which, on itself, offers only a limited perspective on the problem. Some books on this topic treat it as a part of a broader field of network communications, others provide a narrow formal mathematical exposition. Michael Welzl’s book is an exception. It exposes congestion control in several facets, always succinctly explaining the principles and anticipating reader’s questions. Aimed mainly at starting PhD students and interested networking people outside the research community, it avoids formal mathematics and builds up the material through common sense. But it is far from trivial: the author provides a profound overview of the principles, problems and solutions and manages to cover a vast number of diverse topics, focusing on underlying principles, practicality, drawbacks. The author co-chairs the Internet Congestion Control Research Group and works at the University of Innsbruck in Austria.

Essential introduction into the problematics is developed in chapter 2, in which the less informed reader becomes familiar with the basic concepts such as control feedback, stability, queue management, scalability, incentives, fairness. Present technology is the topic of chapter 3, 70% of which takes a fairly detailed description of TCP. The exposition is incremental and problem-motivated. The rest of this chapter briefly describes SCTP, RED and ATM’s Available Bit Service.

The main value of the book I see in its latter part. Chapter 4 is an excellent exposition of very recent experimental enhancements to congestion control. Most of this chapter is dedicated to TCP enhancements and active queue management enhancements. About 10 recent queue management techniques are presented, including such specialities as RED with Preferential Dropping and Stochastic Fair BLUE. A view from the Internet provider’s side is briefly treated in chapter 5. The topics here share one property: they operate on a much larger timescale than those of other chapters. They include Traffic Engineering, MPLS and QoS architectures. Although the level of detail here is much lower than in other chapters, the chapter puts the others into a perspective. The last chapter makes for an exciting read: it presents a mixture of open problems waiting for the hungry PhD mind. It also contains the author’s personal view on the subject. It could be characterised as common-sense reflections of a well-informed pragmatic.

Two appendices conclude the book. Appendix A shows some practical teaching techniques, Appendix B introduces the workings of the IETF.

As great as the book seems, I spotted a few over-simplifications:

Section 2.17.3 describes the concept of proportional fairness. The author states here that the maximization of total utility maximises financial gain. I think this is quite misleading because the term financial gain remains undefined and it is not clear from the text where the revenue comes from. Even if the reader knew it is here meant to come from congestion prices, this would be still problematic. It is true that revenue is maximised if prices charged equal to the congestion prices corresponding to the utility maximisation, but congestion prices are typically not meant to generate revenue as they serve as a control mechanism.

Further the author states that the maximisation of utility functions can be seen as an “optimisation (linear programming)”. But only the constraints are linear and the objective function is non-linear, concave, hence the optimization problem is *nonlinear*.

In section 5.1 the author explains long-range dependence of Internet traffic. It is here stated that Poisson process’s distribution flattens out as the timescale grows. Surely it is meant that the autocorrelation function flattens out. (As opposed to that of self-similar Internet traffic.) **[Update: See comments below by the book’s author. ]**

A word of warning for PhD students

This book is a very good one but I think one should be cautious about using some of the open problems as a basis of one’s PhD. The problems border with engineering rather than research and in some colleges solving these problems cannot satisfy PhD requirements by definition. Ideally, solutions to these problems will come about as a byproduct of a more fundamental framework called the thesis. Perhaps these problems can motivate and trigger a PhD topic, but they should not constitute it.

Any alternative books out there?

A book treating congestion control in detail is The Mathematics of Internet Congestion Control by R. Srikant, 2004, Birkhäuser, but be aware: the exposition is quite straightforward and very formal. Another adept is High Performance TCP/IP Networking by M. Hassan and R. Jain, 2003, Prentice Hall, which is limited to TCP and focuses on performance evaluation.

In summary, the material in this unique book is excellently exposed, a good balance between depth and clarity is kept throughout and the book should be keenly received by its audience.

## Michael Welzl said

So here I am, caught googling my own book 🙂 Which I of course *never* do… well…

First of all, let me thank you very much for your kind words. It’s a great pleasure for me to see that you read and generally liked my book! but now of course I can’t stop myself from answering your comments:

* Proportional Fairness: I agree that this may be an over-simplification. I wasn’t thinking of congestion pricing (with its underlying dynamics) when I wrote this, though, but rather the fact that a utility function can be interpreted as expressing a customer’s willingness to pay for a certain good. So, if you would allocate rates in your network in a way that will maximize the utility functions of all users, you would maximize your income. That was the (arguably simplistic) thought behind this statement.

* I say “linear programming” when it’s in fact a nonlinear optimization problem: that’s obviously a mistake, thanks a lot for pointing it out! I’ll put this in the errata list on my accompanying homepage.

* regarding the Poisson-flattening bit, what I wrote here is: “if Internet traffic would follow a Poisson process and you would look at a traffic trace of, say, five minutes and compare it with a trace of an hour or a day, you would notice that the distribution flattens as the timescale grows.” and I meant it like that – indeed such a traffic trace flattens with growing timescales, as it approaches the mean. See for example figure 2 of this paper (which is one of the references in the (Paxson and Floyd 1995) reference).

* regarding your warning for Ph.D. students, I couldn’t agree more! Maybe I should have explicitly said that in the book – of course you can’t take any of these ideas and simply turn them into a Ph.D. thesis. These are just proposals, with the intention of provoking people to come up with their own, hopefully better, ideas.

Let me thank you again for writing this review! I’m only getting very little feedback, mainly from my students (who of course tell me that they like it, but they would also say so if they hated it 🙂 ), so it’s always nice for me to see that someone else actually read and liked it.

## Hayder said

please I need this book in my study, thank you.

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