This is a note for reviewing the MAP554 and some points about network.
M/M/1, M/M/∞∞, birth and death
The basic model of queue theory. M/M/1 has just one server and has an invariant measure like geometric law,
π(n)=pn(1−p),p=λμπ(n)=pn(1−p),p=λμ
M/M/∞∞ has infinite server and Poisson law
π(n)=e−ppnn!,p=λμπ(n)=e−ppnn!,p=λμ
where λλ is the rate of arrival and μμ the rate of waiting. A more general case can be done like change of power.
π(n)=pn(1−p),p=λμπ(n)=pn(1−p),p=λμ
M/M/∞∞ has infinite server and Poisson law
π(n)=e−ppnn!,p=λμπ(n)=e−ppnn!,p=λμ
where λλ is the rate of arrival and μμ the rate of waiting. A more general case can be done like change of power.
Erlang network:
This is just an application for truncated technique. That is if we have already a network with reversible invariant measure, we can generate a new by changing the power of that part. That is
˜q(x,y)=Cq(x,y),∀x∈A,y∈S−A˜q(x,y)=q(x,y), otherwise Then the new invariant measure becomes
˜π(x)=Kπ(x),∀x∈A˜π(y)=KCπ(y),∀y∈S−AK=1π(A)+π(S−A)
The application is that we make C=0 then the network is defined in just the part A. For example, in the network of route with restriction R, we can just do the case without restriction to get π, which is just the case of several M/M/1 independent, then we do restriction and normalization.
˜π(x)=Kπ(x),∀x∈A,K=1∑x∈Rπ(x)
Jackson network
A more general model of network is like that. Each station has rate λi of arrival and ϕi(ni)μi rate to tackling the service. Here ϕi(ni) can be considered as the power of server, in the case M/M/1 it is always 1 and M/M/∞ it is always ϕi(ni)=ni. However, the difference is that after each service of station i, it has possibility rij to go to the station jThe key is to find a equivalent ˜λi which satisfies that
˜λi=λi+∑j˜λjrji
then the station looks like independent and has the invariant measure
π(n)=Πi˜pniiΠnim=1ϕi(m),˜pi=˜λiμi
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