Big Queues

2004
ISBN: 978-3-540-20912-6
Verlag: Springer Berlin Heidelberg

Buch, Englisch, Band 1838, 260 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 417 g

Reihe: Lecture Notes in Mathematics

Big Queues aims to give a simple and elegant account of how large deviations theory can be applied to queueing problems. Large deviations theory is a collection of powerful results and general techniques for studying rare events, and has been applied to queueing problems in a variety of ways. The strengths of large deviations theory are these: it is powerful enough that one can answer many questions which are hard to answer otherwise, and it is general enough that one can draw broad conclusions without relying on special case calculations.

Zielgruppe

Research

Autoren/Hrsg.

Ganesh, Ayalvadi J.

Wischik, Damon J.

O'Connell, Neil

Fachgebiete

• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Angewandte Mathematik, Mathematische Modelle
• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung
• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Mathematik | Informatik Mathematik Mathematische Analysis Moderne Anwendungen der Analysis

Inhaltsverzeichnis

The single server queue.- Large deviations in Euclidean spaces.- More on the single server queue.- Introduction to abstract large deviations.- Continuous queueing maps.- Large-buffer scalings.- May-flows scalings.- Long range dependence.- Moderate deviations scalings.- Interpretations.- Bibliography.- Index of notation.- Index.

Über Autor(innen)

A. Ganesh: I graduated from the Indian Institute of Technology, Madras, in 1988. I received my MS and PhD in Electrical Engineering from Cornell University in 1991 and 1995 respectively. My PhD thesis was on the use of large deviation techniques in queueing theory. I worked at Edinburgh University, Birkbeck College, London and Hewlett-Packard's Basic Research Institute in Mathematical Sciences (BRIMS) before joining Microsoft Research in March 1999. I am a Fellow of King's College, Cambridge.

Neil O'Connell: BA (Gold Medal) (1989) and MSc in Statistics (1990) from Trinity College Dublin. PhD in Statistics (1993) from University of California, Berkeley. Postdocs at Edinburgh University and Dublin Institure for Advanced Studies, then a University Lecturer in Statistics at Trinity College Dublin, then a visiting professor at Dublin Institute for Advanced Studies. Lead researcher at BRIMS (Basic Research Institute in the Mathematical Sciences, at Hewkett-Packard Labs in Bristol) from its inception (1994-2000). Now a lecturer at Warwick University. Neil has received three EPSRC CASE awards, and an HP patent award.

Damon Wischik: BA (1995) in Mathematics at Cambridge, followed by a PhD (1999). Currently a Research Fellow at Trinity College, Cambridge. Spent a year as a postdoc in the Electrical Engineering department at Stanford University.