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Performance Modeling and Design of Computer Systems: Queueing Theory in Action, by Mor Harchol-Balter
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Computer systems design is full of conundrums: •Given a choice between a single machine with speed s, or n machines each with speed s/n, which should we choose?
•If both the arrival rate and service rate double, will the mean response time stay the same?
•Should systems really aim to balance load, or is this a convenient myth? •If a scheduling policy favors one set of jobs, does it necessarily hurt some other jobs, or are these "conservation laws" being misinterpreted?
•Do greedy, shortest-delay, routing strategies make sense in a server farm, or is what's good for the individual disastrous for the system as a whole?
•How do high job size variability and heavy-tailed workloads affect the choice of a scheduling policy?
•How should one trade off energy and delay in designing a computer system?
•If 12 servers are needed to meet delay guarantees when the arrival rate is 9 jobs/sec, will we need 12,000 servers when the arrival rate is 9,000 jobs/sec?
Tackling the questions that systems designers care about, this book brings queueing theory decisively back to computer science. The book is written with computer scientists and engineers in mind and is full of examples from computer systems, as well as manufacturing and operations research. Fun and readable, the book is highly approachable, even for undergraduates, while still being thoroughly rigorous and also covering a much wider span of topics than many queueing books. Readers benefit from a lively mix of motivation and intuition, with illustrations, examples, and more than 300 exercises - all while acquiring the skills needed to model, analyze, and design large-scale systems with good performance and low cost. The exercises are an important feature, teaching research-level counterintuitive lessons in the design of computer systems. The goal is to train readers not only to customize existing analyses but also to invent their own.
- Sales Rank: #72640 in Books
- Brand: Harchol-balter, Mor
- Published on: 2013-02-18
- Original language: English
- Number of items: 1
- Dimensions: 9.96" h x 1.26" w x 6.97" l, 2.30 pounds
- Binding: Hardcover
- 576 pages
- Used Book in Good Condition
About the Author
Mor Harchol-Balter is an Associate Professor in the Computer Science Department at Carnegie Mellon University. She is a recipient of the McCandless Chair, the NSF CAREER award, the NSF Postdoctoral Fellowship in the Mathematical Sciences, multiple best paper awards and several teaching awards, including the Herbert A. Simon Award for Teaching Excellence and the campus-wide Teaching Effectiveness Award. She is a leader in the ACM SIGMETRICS/Performance community, for which she recently served as Technical Program Chair, and has served on the Technical Program Committee twelve times. Harchol-Balter's work integrates queueing theoretic analysis with low-level computer systems implementation. Her research is on designing new resource allocation policies (load balancing policies, power management policies and scheduling policies) for server farms and distributed systems in general, where she emphasizes integrating measured workload distributions into the problem solution.
Most helpful customer reviews
9 of 11 people found the following review helpful.
Excellent yet difficult book
By Computer Science Graduate Student
Unlike many of the other reviewers of this book, I am not a seasoned queueing professional, professor, or a student of Mor's. I used this book for a course last semester (Spring 2014). It was my first year in the PhD program. I came from a liberal arts school where I double majored in CS and Math (unfortunately a bit lacking). Just so you get a sense for my background.
Make no mistake: this is an excellent book. On many topics, the book is an abundantly clear source. The problems are challenging, and most of them fair. We made it through the first 23 chapters in our opening semester -- and could have gotten through a few more, had we started out the semester properly. The other reviews cover the great aspects of the book, so I won't say more on this. It really is a great book though.
So why four stars then? I have some reservations about the book. First is the initial organization of the book. The overall organization is just fine. But the Introduction to Queueing section (Chapters 1 and 2) feels sorely misplaced. The book should start with the Necessary Probability Background section, then the Introduction to Queueing, and then the actual queueing chapters. Why? Because Chapter 2 provides good intuition for the rest of the book, and by the time you've made it through the probability review, it is not on the forefront of your mind. Similarly, in some of the problems, you'll need "Slowdown", which is only briefly defined in Chapter 2 and not again until Chapter 28. To any future users of the book, I would recommend re-reading Chapter 2 as you continue past the probability review. Maybe a couple of times. It's an important one for mastering the concepts.
Second, the book makes many assumptions about the mathematical background of the audience. Admittedly, the probability review is skimpy (William J. Stewart provides ~8 chapters of probability in his book), but at least it's there. There are a few instances where it's assumed you'll recognize you need to use the limit definition of e^x and the taylor expansion of e^x. There are some derivations where a few steps are omitted that are necessary for clarity -- for example, the steps between the last two lines of the derivation at the bottom of page 220. If you get confused at points, I would recommend trying to fill in the steps on your own in the textbook. Just be forewarned, if you're mortal, you will feel lost at places.
Third, I felt that there were some interesting pieces of queueing theory that were not emphasized in Mor's book. Fortunately, these blurbs were well substituted by Adan & Resing, which is for free online (legally). On pages 38 and 39, Adan and Resign have great coverage of "Busy Periods," a topic that seems to only appear in exercises in Mor's book. Particularly, the equations in 4.6.1 are incredibly easy yet crucial for understanding queueing systems. Additionally, Mor was also quite skimpy on what she calls the "Resource Requirement" (defined on page 273). Adan & Resing don't even acknowledge that they provide insight on the resource requirement. However, I implore you to do Exercise 25 in Adan & Resing and then look at the solution. Part (ii) of the question provides an interesting insight on how you can use the resource requirement. Or at least I, a non-expert, think its interesting. To be completely clear though, Mor's book is better in nearly every way than Adan & Resings.
Fourth, some of the problems are quite difficult. If you have a helpful TA or Prof then that should be okay. But be warned, if your TA and Prof are not helpful, AND you're assigned one of the deathly hard problems, you're absolutely screwed. This is not a fault of the book per say, but it should be known. On the other hand, I also found some of the problems did not pertain as well to the chapter as other ones, which is a bit annoying. I don't want to struggle through a hard problem, fully knowing I will get little out of it.
Last, I felt that there were some places the intuition was not highlighted very well. William J. Stewart spends quite a bit of time (and text) cultivating his reader's intuition for certain topics, whereas again, Mor throws it down quickly and expects you to get the whole picture. To be fair, this only happened a few times and I can't remember any specific examples right now, so take this blurb with a grain of salt.
Outside of these issues, I also wish the book had a few more things. The first is more programming assignments. Perhaps we just weren't assigned any of the good ones, but the few programming exercises we had were pretty trivial. There is much more potential for some simulation coverage. The second is case-studies at the end of every section. It would be nice to have a problem to pore over that integrates all of the topics in the past 5-8 chapters together. Essentially some mini hands-on experience that would be a decent representation of what an actual professional would do.
Now that we've finished my desiderata, I want to reiterate, this book is very good. I just wanted to explain my four star ranking and cover some details other reviews might not have captured.
21 of 28 people found the following review helpful.
CAUTION: Certainly Necessary But Not Sufficient
By Garrett A. Hughes
Having been involved in modeling and simulating complex hardware/software systems for twenty years or more, I thought it appropriate to comment on some of the author's remarks regarding the state of the art. I would like to add that had not Amazon, in all their marketing wisdom, chosen to send me an unsolicited ad describing Harchol-Balter's text, you probably wouldn't be reading this. But like Pandora, I couldn't resist a "Look Inside!"
In her opening remarks, Ms. Harchol-Balter states "Unfortunately, of the hundreds of books written on stochastic processes, almost none deal with computer systems." If you remove the term "unfortunately" from that statement, you could characterize it as having a basis in fact: given that the world is filled with stochastic processes (In fact, I tend to treat all real-world processes as stochastic). Seen in this light, the implied dearth of computer related texts can be attributed to proportion. Ms. Harchol-Balter goes on to say that those few remaining texts that do deal with the subject at hand "are not 'friendly' to computer scientists."
Ms. Harchol-Balter's statements pose a couple of problems that beg for resolution. First, why the dearth of books that approach computer performance from the standpoint of queueing theory? She reports that her own colleague gave an answer in a very Candide fashion: "The world doesn't look like an M/M/1 queue" - possibly the best of all possible answers. Trying to solve an N-body computer system analytically is equivalent to trying to solve the canonical N-body physics problem - it can't be done. One must resort to numerical methods in the N-body case, and in the case of computer systems, use stochastic discrete event modeling and simulation.
Regarding the second problem posed by the author, that of dealing with the social nature of the few remaining texts, I would say: "Choose your friends wisely." My first mentors were led by Edward D. Lazowska in their classic "Quantitative System Performance: Computer System Analysis Using Queueing Network Models." Following close on their heels was M.H. MacDougall in his user friendly "Simulating Computer Systems: Techniques and Tools," and finally Raj Jain in his tour-de-force "The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling."
My infatuation with queueing theory came to a grinding halt early in my professional career (thankfully), when I compared the results of an 802.3 performance analysis by Andrew S. Tanenbaum in his book "Computer Networks, 2nd ed."), with that of a simulation tool I was using at the time. Tanenbaum's results differed markedly from mine. As a good analyst, I knew not to trust the simulation implicitly, so I called some colleagues at a different firm who were using a different simulation tool (the competitor's) and asked them to run the same simulation. They got the same results that I had. Tanenbaum's results, using typical queueing theory analysis, were just plain wrong. And this was a very simple network.
As the years rolled by, the configurations that I modeled became extremely complex (hundreds if not thousands of components) and the analyses focused on system bottlenecks anywhere in the system. You just can't do that sort of analysis with queueing theory. And modern computers contain hundreds, if not thousands, of interconnected components.
What you can do with queueing theory is verify the results of a simulation by treating the entire system, or a small number of subsystems, as black boxes representing simple queues; make an educated guess at the arrival time distributions; and check to see if the results you calculate for throughput compare favorably with those of your simulation runs. It's a good reality check.
In the final analysis, not wishing to leave my readers queueless, I would recommend that anyone, who is foolish enough to tread these networks, take a course similar to the one described and taught by Ms. Harchol-Balter, using her book, which appears from the table of contents to be similar in focus to Raj Jain's, but much heavier on queueing theory. If you plan to specialize in performance analysis, rather than design however, Jain's is the better buy. But you will probably want both at some point. You will find the material in Harchol-Balter's text helpful for doing back-of-the-envelope throughput, utilization and residence time calculations, generating arrival time distributions for your sources, and impressing your colleagues with terms like M/M/k systems.
6 of 8 people found the following review helpful.
Excellent resource - happy to own a copy
By John T
I took Prof. Mor Harchol-Balter's Performance Modeling course as a Ph.D. student at Carnegie Mellon, and enjoyed it thoroughly. For those of you not fortunate enough to have been in Mor's class, you can now take advantage of her imparted knowledge in book form. What you will find are a series of short 10-page chapters, each focused around a particular topic or example. Mor's Socratic teaching style is evident in the book: There are many questions posed to the reader throughout the chapter to check your intuition, with well-presented answers and easy-to-follow derivations. This is a great book to read cover-to-cover. As Prof. Harchol-Balter describes in the foreword, this book is "Fun and readable, [... and] highly approachable, even for undergraduates, while still being thoroughly rigorous and also covering a much wider span of topics than many queueing books." I couldn't agree more.
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