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Steady-State Workload for a Compound-Poisson-Process (Lévy-Driven-Queue)


Lévy measure of a pure jump processDoes $mathbbE(|X_t|) = O(t)$ hold for a Lévy process $(X_t)_t geq 0$?bound on compound poisson processCharacteristic function of compound Poisson processDistribution of the increments of a Compound Poisson processCompound poisson process invariant measureNumber of arrivals of a compound Poisson process?Calculate $mathbbE[N(E) e^-rE]$ for Compound Poisson $(N(t))_t$ and exponential $E$.













1












$begingroup$


Suppose that $X in mathbbCP(r, lambda, b(cdot))$ with the jumps being distributed exponentially with mean $frac1vartheta$. (Hence we are in a special case of compound Poisson input: an $M/G/1$ queue.) The distribution of the jobs is denoted with $B$. Let $Q$ be the corresponding stationary workload for which holds
$$
beginalign
mathbbP=(Q leq x)= mathbbP bigg( sum_n=1^N B_n^res leq x bigg) qquad (1)
endalign
$$

where $mathbbP(N=n)= big( 1-fraclambda mathbbEr big) big( fraclambda mathbbEr big)^n$ and $B_1^res, B_2^res,...$ are i.i.d. samples from the residual lifetime distribution of $B$ defined by
$$
mathbbP big(B^res leq xbig) = frac1mathbbE[B] int_0^x mathbbP (b > y) dy
$$

with $mathbbE[B] = int_0^infty mathbbP (b > y) dy$.



The Questions:



  1. What is the explizit expression for $mathbbE[Q]$ and $mathbbV[B]$?


  2. Find the distribution of $N$ and $B_1^res$ in (1).


I am thankful for any answer or idea!










share|cite|improve this question







New contributor




Christina is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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$endgroup$











  • $begingroup$
    1. Have you tried using the GPK formula? I.e., if you have $kappa(alpha)=log E[e^-alpha Q]=fracalphavarphi'(0)varphi(alpha)$ then $E[Q]=-kappa'(0)$? 2. You already wrote down the distributions of the residual service time and the the Geometric distribution of $N$.
    $endgroup$
    – QQQ
    Mar 14 at 11:05
















1












$begingroup$


Suppose that $X in mathbbCP(r, lambda, b(cdot))$ with the jumps being distributed exponentially with mean $frac1vartheta$. (Hence we are in a special case of compound Poisson input: an $M/G/1$ queue.) The distribution of the jobs is denoted with $B$. Let $Q$ be the corresponding stationary workload for which holds
$$
beginalign
mathbbP=(Q leq x)= mathbbP bigg( sum_n=1^N B_n^res leq x bigg) qquad (1)
endalign
$$

where $mathbbP(N=n)= big( 1-fraclambda mathbbEr big) big( fraclambda mathbbEr big)^n$ and $B_1^res, B_2^res,...$ are i.i.d. samples from the residual lifetime distribution of $B$ defined by
$$
mathbbP big(B^res leq xbig) = frac1mathbbE[B] int_0^x mathbbP (b > y) dy
$$

with $mathbbE[B] = int_0^infty mathbbP (b > y) dy$.



The Questions:



  1. What is the explizit expression for $mathbbE[Q]$ and $mathbbV[B]$?


  2. Find the distribution of $N$ and $B_1^res$ in (1).


I am thankful for any answer or idea!










share|cite|improve this question







New contributor




Christina is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.







$endgroup$











  • $begingroup$
    1. Have you tried using the GPK formula? I.e., if you have $kappa(alpha)=log E[e^-alpha Q]=fracalphavarphi'(0)varphi(alpha)$ then $E[Q]=-kappa'(0)$? 2. You already wrote down the distributions of the residual service time and the the Geometric distribution of $N$.
    $endgroup$
    – QQQ
    Mar 14 at 11:05














1












1








1





$begingroup$


Suppose that $X in mathbbCP(r, lambda, b(cdot))$ with the jumps being distributed exponentially with mean $frac1vartheta$. (Hence we are in a special case of compound Poisson input: an $M/G/1$ queue.) The distribution of the jobs is denoted with $B$. Let $Q$ be the corresponding stationary workload for which holds
$$
beginalign
mathbbP=(Q leq x)= mathbbP bigg( sum_n=1^N B_n^res leq x bigg) qquad (1)
endalign
$$

where $mathbbP(N=n)= big( 1-fraclambda mathbbEr big) big( fraclambda mathbbEr big)^n$ and $B_1^res, B_2^res,...$ are i.i.d. samples from the residual lifetime distribution of $B$ defined by
$$
mathbbP big(B^res leq xbig) = frac1mathbbE[B] int_0^x mathbbP (b > y) dy
$$

with $mathbbE[B] = int_0^infty mathbbP (b > y) dy$.



The Questions:



  1. What is the explizit expression for $mathbbE[Q]$ and $mathbbV[B]$?


  2. Find the distribution of $N$ and $B_1^res$ in (1).


I am thankful for any answer or idea!










share|cite|improve this question







New contributor




Christina is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.







$endgroup$




Suppose that $X in mathbbCP(r, lambda, b(cdot))$ with the jumps being distributed exponentially with mean $frac1vartheta$. (Hence we are in a special case of compound Poisson input: an $M/G/1$ queue.) The distribution of the jobs is denoted with $B$. Let $Q$ be the corresponding stationary workload for which holds
$$
beginalign
mathbbP=(Q leq x)= mathbbP bigg( sum_n=1^N B_n^res leq x bigg) qquad (1)
endalign
$$

where $mathbbP(N=n)= big( 1-fraclambda mathbbEr big) big( fraclambda mathbbEr big)^n$ and $B_1^res, B_2^res,...$ are i.i.d. samples from the residual lifetime distribution of $B$ defined by
$$
mathbbP big(B^res leq xbig) = frac1mathbbE[B] int_0^x mathbbP (b > y) dy
$$

with $mathbbE[B] = int_0^infty mathbbP (b > y) dy$.



The Questions:



  1. What is the explizit expression for $mathbbE[Q]$ and $mathbbV[B]$?


  2. Find the distribution of $N$ and $B_1^res$ in (1).


I am thankful for any answer or idea!







calculus stochastic-processes stochastic-calculus levy-processes






share|cite|improve this question







New contributor




Christina is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.











share|cite|improve this question







New contributor




Christina is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.









share|cite|improve this question




share|cite|improve this question






New contributor




Christina is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.









asked Mar 14 at 8:29









ChristinaChristina

234




234




New contributor




Christina is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.





New contributor





Christina is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.






Christina is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.











  • $begingroup$
    1. Have you tried using the GPK formula? I.e., if you have $kappa(alpha)=log E[e^-alpha Q]=fracalphavarphi'(0)varphi(alpha)$ then $E[Q]=-kappa'(0)$? 2. You already wrote down the distributions of the residual service time and the the Geometric distribution of $N$.
    $endgroup$
    – QQQ
    Mar 14 at 11:05

















  • $begingroup$
    1. Have you tried using the GPK formula? I.e., if you have $kappa(alpha)=log E[e^-alpha Q]=fracalphavarphi'(0)varphi(alpha)$ then $E[Q]=-kappa'(0)$? 2. You already wrote down the distributions of the residual service time and the the Geometric distribution of $N$.
    $endgroup$
    – QQQ
    Mar 14 at 11:05
















$begingroup$
1. Have you tried using the GPK formula? I.e., if you have $kappa(alpha)=log E[e^-alpha Q]=fracalphavarphi'(0)varphi(alpha)$ then $E[Q]=-kappa'(0)$? 2. You already wrote down the distributions of the residual service time and the the Geometric distribution of $N$.
$endgroup$
– QQQ
Mar 14 at 11:05





$begingroup$
1. Have you tried using the GPK formula? I.e., if you have $kappa(alpha)=log E[e^-alpha Q]=fracalphavarphi'(0)varphi(alpha)$ then $E[Q]=-kappa'(0)$? 2. You already wrote down the distributions of the residual service time and the the Geometric distribution of $N$.
$endgroup$
– QQQ
Mar 14 at 11:05











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