Proving the expectation of a stochastic process

28 Views Asked by At

Problem

Information packets arrive at a server with a poisson process having rate $\lambda = 2$ per hour.

The server processing time for a packet follows the distribution : $f(x) = 1, 0\leq x\leq1$

The status of the server is busy if it is processing a packet, otherwise it is waiting. If a packet arrives while the server is busy, that packet is lost.

Let $t_B$ denote the length of one busy period, $t_I$ denote the length of one idle period. Find the distrubutions of $t_B$ & $t_I$.

Let $N$ denote the total number of lost packets, $T_B$ denote the total busy time of the server up until time $T=10$ hours.

Show that : $$ \begin{align} E[N] = \lambda E[T_B] \end{align} $$

My attempt :

$t_B$ is simply the time taken for the server to process a packet, so its distribution is also $f(x) = 1, 0 \leq x \leq 1$

$t_I$ is the inter-arrival time between two packets which follows an $Exp(\lambda = 2)$ distribution, using the relation between poisson & exponential rv's.

In trying to prove the equation, this is what I have so far :

N = total no. of lost packets = no. of packets arriving during $T_B$(while the server is busy)

$$ \begin{align} E[N] &= E[\textrm{No. of arrivals during }T_B] \\ &=E[\textrm{No. of arrivals per unit time}]\cdot E[T_B] \\ &=\lambda E[T_B]~\textrm{(Shown)} \end{align} $$

Am I going about this the right way? If so is there a proper way to express this in math notation? Thank you!