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General

Additionally, it is often necessary to build new random variables using other random variables and mathematical expressions. For example, to denote that the response time is 5 times slower, we would like to simply multiply a random variable for a response time by 5 and assign the result to a new random variable. For this reason, our specification language supports some basic mathematical operations ($ *$,$ -$,$ +$,$ /$,...) as well as some logical operations for boolean type expressions ($ ==$,$ >$,$ <$,and,or,...).

To give an example, the distribution of a random variable $ N$ is depicted in figure 2.14. The variable could model some characterisation of the size of a parameter of a component service.

Figure 2.13: A Distribution of a Discrete Random Variable N

Image PMF_filesizes

To determine the time consumption of the method body which depends on the characterisation $ N$ it is known that the amount of CPU instructions needed to execute the method is three times $ N$. The resulting distribution function is shown in figure 2.14.

Figure 2.14: A Distribution of N * 3
Image PMF_cpuops


next up previous contents index
Next: Differences btw. discrete and Up: Functional random variables Previous: Functional random variables   Contents   Index
Snowball 2007-03-16