Quantifying Performance Models. Chapter 3. Outline. Introduction Stochastic Modeling vs. Operational Analysis Basic Performance Results Utilization Law Service Demand Law The Forced Flow Law Little's Law Interactive Response Time Law Bounds on Performance Using QN Models
Quantifying Performance Models
are discussed here in more precise terms.
OA made analytic modeling accessible to capacity planners in large computing environments.
operational laws between operational variables.
Ui = Sixi.
1,500 bytes/packet x 8 bits/byte = 12,000 bits/packet.
Table 3.1. Data for Example 3.2
Figure 3.1. Closed QN model of a database server.
Table 3.2. Service times in msec for six requests.
Each transactions performs three I/Os on a disk.
Service demand on this disk due to the workload generated by the six transactions. (33+41+36+32+36+39)/6=36.2 msec.
= Bi /C0 = (Cix Si )/C0
= (Ci /C0) x Si = Vix Si).
Figure 3.2. Little's Law.
Ni = Rix Xi
Figure 3.3. Single server.
Figure 3.4. Interactive computer system.
X0max= 1/Ddisk3= 1/0.142 = 7.04 tps.
Table 3.3. Service Demands, Arrival Rates, and Performance Metrics for Ex. 3.12
What is the average time spent by a job in the system once it is in the multiprogramming mix (i.e., the average time spent by the job in the system once it is memory resident)?