Performance Modeling and Design of Computer Systems: Queueing Theory in Action

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Cambridge University Press, Feb 18, 2013 - Computers - 548 pages
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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.
 

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Contents

Queueing Theory Terminology
13
Necessary Probability Background
29
Generating Random Variables for Simulation
70
Sample Paths Convergence and Averages
79
WhatIf
93
WhatIf for Closed Systems
114
From Markov Chains to Simple Queues
127
Ergodicity Theory
148
High Variability and Heavy Tails
347
PhaseType Distributions and MatrixAnalytic Methods
359
Networks With TimeSharing PS Servers BCMP
380
The MIG1 Queue and the Inspection Paradox
395
Task Assignment Policies for Server Farms
408
Transform Analysis
433
MIG1 Transform Analysis
450
Power Optimization Application
457

Google Aloha and Harder Chains
190
Exponential Distribution and the Poisson Process
206
Transition to ContinuousTime Markov Chains
225
Multiserver Multiqueue Systems
251
Capacity Provisioning for Server Farms
269
TimeReversibility and Burkes Theorem
282
Networks of Queues and Jackson Product Form
297
Classed Network of Queues
311
Closed Networks of Queues
331
Smart Scheduling in the MGl
471
NonPreemptive NonSizeBased Policies
478
NonPreemptive SizeBased Policies
499
Preemptive SizeBased Policies
508
SRPT and Fairness
518
Bibliography
531
Index
541
Copyright

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About the author (2013)

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.