9.1. Performance Models9.2. Queueing9.2.1. Queueing Economics9.2.2. Queueing Visualized9.3. Queueing Theory9.3.1. Model Input and Output Values9.3.1.1. Arrivals and completions9.3.1.2. Service channels, utilization, and stability9.3.1.3. Service time and service rate9.3.1.4. Queueing delay and response time9.3.1.5. Maximum effective throughput9.3.1.6. Cumulative distribution function (CDF) of response
time9.3.2. Random Variables9.3.2.1. Expected value9.3.2.2. Probability density function (pdf)9.3.2.3. Using the pdf9.3.2.4. Why understanding distribution is important9.3.3. Queueing Theory Versus the “Wait Interface”9.3.3.1. Oracle wait times9.3.3.2. Differences in queueing theory notation9.4. The M/M/m Queueing Model9.4.1. M/M/m Systems9.4.2. Non-M/M/m Systems9.4.3. Exponential Distribution9.4.3.1. Poisson-exponential relationship9.4.3.2. Testing for fit to exponential distribution9.4.3.3. A program to test for exponential distribution9.4.4. Behavior of M/M/m Systems9.4.4.1. Multi-channel scalability9.4.4.2. The knee9.4.4.3. Response time fluctuations9.4.4.4. Parameter sensitivity9.4.5. Using M/M/m: Worked Example9.4.5.1. Suitability for modeling with M/M/m9.4.5.2. Computing the required number of CPUs9.4.5.3. What we can learn from an optimistic model9.4.5.4. Negotiating the negotiable parameters9.4.5.5. Using Goal Seek in Microsoft Excel9.4.5.6. Sensitivity analysis9.5. Perspective9.6. Exercises