Performance Modeling and Design of Computer Systems

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  • Format: Hardcover
  • Copyright: 2013-02-18
  • Publisher: Cambridge Univ Pr
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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.

Table of Contents

Introduction to Queueing
Motivating examples
Queueing theory terminology
Necessary Probability Background
Probability review
Generating random variables
Sample paths, convergence, and averages
The Predictive Power of Simple Operational Laws: 'What If' Questions and Answers
Operational laws
Modification analysis
From Markov Chains to Simple Queues
Discrete-time Markov Chains
Ergodicity theory
Real-world examples: Google, Aloha
Generating functions for Markov Chains
Exponential distributions and Poisson Process
Transition to continuous-time Markov Chains
M/M/1 and PASTA
Server Farms and Networks: Multi-server, Multi-queue Systems
Server farms: M/M/k and M/M/k/k
Capacity provisioning for server farms
Time-reversibility and Burke's Theorem
Jackson network of queues
Classed network of queues
Closed networks of queues
Real-World Workloads: High-Variability and Heavy Tails
Tales of tails: real-world workloads
Phase-type workloads and matrix-analytic
Networks of time-sharing (PS) servers
M/G/I queue and inspection paradox
Task assignment for server farms
Transform analysis
M/G/I transform analysis
Power optimization application
Smart Scheduling
Performance metrics
Non-preemptive, non-size-based policies
Preemptive, non-size-based policies
Non-preemptive, size-based policies
Preemptive, size-based policies
Scheduling: SRPT and fairness
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