Finite-Source Queueing Systems and their Applications
Finite-Source Queueing Systems and their Applications
Finite-Source Queueing Systems and their Applications
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János Sztrik 2001/08/05<br />
M Exponential distribution (Markovian or memoryless property)<br />
Ek Erlang distribution with k phases<br />
Hk Hyperexponential distribution with k phases<br />
Ck Cox distribution with k phases<br />
D Deterministic distribution, i.e., the interarrival time<br />
or service time is constant<br />
G General distribution<br />
GI General distribution with independent interarrival times<br />
However, due to the complexity of high-speed networks, there is considerable<br />
interest in traffic arrival processes where successive arrivals are correlated.<br />
Such non-GI arrival processes include Markov-modulated Poisson process<br />
(MMPP) , or batch Markovian arrival process (BMAP), [16, 24, 33, 40, 49].<br />
The queueing discipline or service strategy determines which job is selected<br />
from the queue for processing when a server becomes available. Some<br />
commonly used queueing disciplines are:<br />
FCFS (First-Come-First-Served): If no queueing discipline is given in the<br />
<strong>Finite</strong>-<strong>Source</strong> <strong>Queueing</strong> <strong>Systems</strong> <strong>and</strong> <strong>their</strong> <strong>Applications</strong>
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