Diffusion Approximation of State-Dependent G-Networks Under Heavy Traffic
نویسندگان
چکیده
منابع مشابه
Multiscale Diffusion Approximations for Stochastic Networks in Heavy Traffic∗
Stochastic networks with time varying arrival and service rates and routing structure are studied. Time variations are governed, in addition to the state of the system, by two independent finite state Markov processes X and Y . Transition times of X are significantly smaller than typical inter-arrival and processing times whereas the reverse is true for the Markov process Y . By introducing a s...
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Consider a single server queue with renewal arrivals and i.i.d. service times in which the server operates under a processor sharing service discipline. To describe the evolution of this system, we use a measure valued process that keeps track of the residual service times of all jobs in the system at any given time. From this measure valued process, one can recover the traditional performance ...
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We provide a complete large and moderate deviations asymptotic for the steady-state waiting time of a class of subexponential M/G/1 queues under heavy traffic. The asymptotic is uniform over the positive axis, and reduces to heavy-traffic asymptotics and heavy-tail asymptotics on two ends, both of which are known to be valid over restricted asymptotic regimes. The link between these two well-kn...
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ژورنال
عنوان ژورنال: Journal of Applied Probability
سال: 2008
ISSN: 0021-9002,1475-6072
DOI: 10.1239/jap/1214950352