William A. Massey, Department of Operations Research and Financial En

Location :

à l’ENS
en salle de réunion de l'équipe TREC
escalier de direction, 2ème étage du bâtiment principal
45 rue d’Ulm
75005 Paris
http://www.di.ens.fr/~trec/Plan%20acces%20DIENS.pdf

Abstract :

Talk 1: 

Title : Dynamic Pricing  to Control Loss Systems with Quality of Service Targets

Abstract : 

Multi-server queueing loss models capture important features of real time
services. Arriving customers make their decision to join the system based on
the availability of resources as well as the current service price. Given a
fixed number resources, the manager can use price as a mechanism to control the
utilization of the system. A major objective for the manager is then to find a
pricing policy that maximizes total revenue while meeting the quality of
service targets desired by the customers.  

Using variational calculus techniques, we solve a dynamic optimal control
problem by approximating the loss model as a constrained offered load model. We
then use customer demand forecasts to anticipate future service congestion and
implement a congestion pricing algorithm. 

(This is joint work with Robert C. Hampshire of Carnegie Mellon University and Qiong Wang of Bell Labs).

 
Talk 2:

Title : Dynamical Queueing Systems

Abstract : 

Queueing theory was invented in the first half of the 20th century to model and
design the voice communication network known as telephone system. In the second
half of the 20th century, queueing theory contributed to the design of data
communication networks that became the Internet of today. Both types of voice
and data queueing models made significant use of the steady state theory for
continuous time Markov chains.

This talk presents a new type of dynamical queueing theory that analyzes the
transient behavior of such systems with time-varying rates. Using these methods
we can capture more of the time-varying behavior that would otherwise be washed
out by steady state analysis.

Through the use of scaling techniques to do an asymptotic analysis at the
sample path level, we can approximate many of these queueing processes by
dynamical systems. This enables us to apply the dynamic optimization techniques
of classical mechanics towards the strategic design of communication systems
and services.

Host :

Ecole Normale Supérieure