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Sample Path Large Deviations Principles for Poisson Shot Noise Processes and Applications


 
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1. Title Title of document Sample Path Large Deviations Principles for Poisson Shot Noise Processes and Applications
 
2. Creator Author's name, affiliation, country Ayalvadi Ganesh; Microsoft Research
 
2. Creator Author's name, affiliation, country Claudio Macci; Universita degli Studi di Roma
 
2. Creator Author's name, affiliation, country Giovanni Luca Torrisi; Istituto per le Applicazioni del Calcolo
 
3. Subject Discipline(s)
 
3. Subject Keyword(s) Poisson shot noise; large deviations; sample paths; queues; risk
 
3. Subject Subject classification 60F10, 60F17,60K25
 
4. Description Abstract This paper concerns sample path large deviations for Poisson shot noise processes, and applications in queueing theory. We first show that, under an exponential tail condition, Poisson shot noise processes satisfy a sample path large deviations principle with respect to the topology of pointwise convergence. Under a stronger superexponential tail condition, we extend this result to the topology of uniform convergence. We also give applications of this result to determining the most likely path to overflow in a single server queue, and to finding tail asymptotics for the queue lengths at priority queues.
 
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7. Date (YYYY-MM-DD) 2005-08-03
 
8. Type Status & genre Peer-reviewed Article
 
8. Type Type
 
9. Format File format PDF
 
10. Identifier Uniform Resource Identifier http://ejp.ejpecp.org/article/view/273
 
10. Identifier Digital Object Identifier 10.1214/EJP.v10-273
 
11. Source Journal/conference title; vol., no. (year) Electronic Journal of Probability; Vol 10
 
12. Language English=en
 
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