WEEKS 1-3:

- Chpt 3 (probability review) -- do this for as long as needed. There are plenty of exercises in the book, but you can also contact me for an additional 100 problems on chpt 3 material.

- Chpt 1 (motivating examples)
- Chpt 2 (queueing notation)

WEEK 5:

- Chpt 4 (generating random variables for simulation)
- Skim Chpt 5 (time averages versus ensemble averages) just to get some words down like "convergence", "time average" and "ensemble average" which come up later in the text. The math is not needed here -- just a high-level idea.

WEEK 6:

- Chpt 6 (operational laws)
- Chpt 7 (operational laws -- "what if" analysis)

WEEKS 7:

- Chpt 8 (Discrete-time Markov Chains)
- Lighly skim Chpt 9 (Ergodicity Theory)-- just so that they know a little about the theorems that are proved. It's OK to skip Chpt 9 entirely.

WEEK 8:

- Chpt 10.1
- Chpt 11 (Exponential & Poisson)

Week 9:

- Chpt 12 (Converting from Discrete-time Markov Chains to Continuous-time MCs)
- Chpt 13 (M/M/1)

Week 10:

- Chpt 14 (M/M/k and M/M/k/k)
- Skim Chpt 15 (Capacity Provisioning).

WEEKS 11-12:

- Chpt 20 (Heavy tailed workloads)
- Chpt 23 (M/G/1)
- Chpt 24 (Task Assignment in Server Farms)

WEEK 13-14:

- Chpt 27 (Power Management) -- Do this without transforms
- Chpt 28 (Scheduling in M/G/1)-- Do this without transforms
- Chpt 29 (Scheduling in M/G/1)-- Do this without transforms

I recommend assigning weekly homework, since there are a lot of concepts being covered. I am available at all times to help out instructors. If you are teaching this class, please send me email: harchol@cs.cmu.edu.

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