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How to calculate the $\mathbb P(\max_{i} W_{i}>x)$

Assume the $W_{i}$ are independent and identically distributed positive random variables with mean $\mu$ and variance $\sigma^{2}$.
How to calculate the $\mathbb P(\max_{i} W_{i}>x)$?

A:

This is a special case of a question from the area of queueing theory (also known as the $GI/GI/1$ queue).
Let $Q(t)$ be the number of customers at time $t$ in the $GI/GI/1$ queue. Then $Q(t)$ is either $0$ or $1$ and $Q(t)$ is distributed as an $M/M/1$ queue. This leads to the famous formula
$$\mathbb P(Q(t) > 0) = \frac{1}{1+\frac{\lambda}{\mu} \int_0^t e^{ -(t-s)}ds}.$$
Because $\mathbb P(W_i > x) = \mathbb P(W_1 > x)$ we may take $\lambda = \mu$ so that
$$\mathbb P(W_1 > x) = \frac{1}{1+\frac{\mu}{\mu} \int_0^x e^{ -(x-s)}ds}.$$

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