Asymptotics of first passage times for random walk in an orthant
成果类型:
Article
署名作者:
McDonald, DR
署名单位:
University of Ottawa
刊物名称:
ANNALS OF APPLIED PROBABILITY
ISSN/ISSBN:
1050-5164
发表日期:
1999
页码:
110-145
关键词:
markov additive processes
large deviations
jump-processes
Rare events
networks
QUEUE
摘要:
We wish to describe how a chosen node in a network of queues overloads. The overloaded node may also drive other nodes into overload, but the remaining super stable nodes are only driven into a new steady state with stochastically larger queues. We model this network of queues as a Markov additive chain with a boundary. The customers at the super stable nodes are described by a Markov chain, while the other nodes are described by an additive chain. We use the existence of a harmonic function h for a Markov additive chain provided by Ney and Nummelin and the asymptotic theory for Markov additive processes to prove asymptotic results on the mean time for a specified additive component to hit a high level l. We give the limiting distribution of the super stable nodes at this hitting time. We also give the steady-state distribution of the super stable nodes when the specified component equals l, The emphasis here is on sharp asymptotics, not rough asymptotics as in large deviation theory. Moreover, the limiting distributions are for the unsealed process, not for the fluid limit as in large deviation theory.