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Index
Lessons
Numerical
methods for markov chains
Queueing
Networks and Mobile Communications
Partial
Evaluation and Automatic Program Optimisation
Models
for telecommunications
Location
Leçon
inaugurale: Telecommunication Modeling
Registration
Lessons
Numerical
methods for Markov chains
16-23 Febuary, 2 March 1999
Solvay Auditorium, 10-12 a.m.,
2-4 p.m.
Dr.
Beatrice Meini
Department of Mathematics,
University of Pisa
One
of the main problems related to the numerical solution of
Markov chains is the computation of the probability invariant
vector. The aim of these lectures is to introduce both the
fundamental numerical methods and the more advanced
techniques for finite as well as infinite Markov chains with
M/G/1 structure, which are of particular interest for
telecommunication modeling. In the finite case we recall the
known direct methods based on matrix factorizations and the
iterative methods based on regular splittings. In the
infinite case we have more specific computational issues,
like the solution of a nonlinear matrix equation. We analyze
the classical functional iteration methods and present new
strategies for improving the convergence rate, based on
Toeplitz matrix computations, on doubling techniques and on
cyclic reduction.
Beatrice
Meini received her degree cum laude in Mathematics in
1993, and her PhD degree in 1998 at the University of Pisa,
Italy. Then, she obtained a senior fellowship from INDAM (the
Institute of High Mathematics), and a post doctoral
fellowship from CNR (the National Research Council). Now she
has a permanent position, as researcher, in the Department of
Mathematics of the University of Pisa. Her main research
activity is in the field of the design and analysis of
numerical algorithms for the solution of problems of large
dimension and with a strong structure; particular interest is
devoted to computational issues related to the solution of
structured Markov chains.
Queueing
Networks and Mobile Communications
9-16-23-30
March 1999
Solvay
Auditorium, 10-12 a.m., 2-4 p.m.
Prof.
Dr. Rudolf Mathar
Aachen University of Technology
Markov chains in discrete and
continuous time are a main modeling tool. In particular,
solving the balance equations for transition probabilities
and intensities allows to describe the corresponding systems
in equilibrium; for reversible chains the balance equations
can be easily solved, and in Markovian tandem networks all
intermediate arrival and departure processes are recognized
as Poissonian. Open and closed Jackson Networks are another
general model. By applying reversibility and truncation, the
product form of the steady state distribution is preserved
even in very general cases. The lectures will conclude with
some interesting applications of queueing networks in mobile
communication modeling, optimal register location strategies
and optimal channel allocation in cellular radio networks.
Rudolf Mathar received his Dipl.-Math. and his
Dr. Rer. Nat. degree in mathematics from the Aachen
University of Technology, Germany, in 1978 and 1981,
respectively. From 1986 to 1988, he worked as a lecturer in
computer science at the European Business School and in an
optimization research group at the University of Augsburg. He
is currently a Professor of Stochastics at the Aachen
University of Technology. He is a cofounder of the Center of
Network Optimization (CNO), and a cofounder and manager of
Telecommunications Network Consulting ltd. His research
interests include applications to mobile communication
systems through performance analysis and optimization of
stochastic networks.
Partial
Evaluation and Automatic Program Optimisation
20-27 April, 4-11 May 1999
Solvay Auditorium, 10-12 a.m.,
2-4 p.m.
Dr.
Michael Leuschel
Department of Electronics and
Computer Science,
University of Southampton
Because of their simplicity and
purity, declarative (e.g., functional and logic) programming
languages are particularly amenable to reasoning and
automatic transformation techniques. The idea often is to
automatically transform an elegant (but inefficient) program
into an efficient (but inelegant) program. Partial evaluation
is an automatic transformation technique that has received
much attention. In this course we shall also study a number
of more aggressive automatic transformation techniques,
yielding both greater speedups and more difficulty in
controlling the transformation process. These latter
difficulties pose many interesting problems which we will
study in the course.
Michael Leuschel received a degree in Computer
Science from the Université Libre de Bruxelles in 1990
and a Master of Artificial Intelligence from the Katholieke
Universiteit Leuven in 1993, where he also received his Ph.D
in 1997. Then he obtained a post-doctoral fellowship of the
Belgian Fund for Scientific Research. He is currently a
lecturer at the Department of Electronics and Computer
Science of the University of Southampton. His research
focuses on program analysis, transformation, and
specialisation of declarative languages (mainly logic and
functional programming). He is also interested in
metaprogramming, termination, deductive databases, and formal
methods.
Models for
telecommunications
8-25 May, 1 June 1999
Solvay Auditorium, 10-12 a.m.,
2-4 p.m.
Dr.
Peter Taylor
Teletraffic Research Centre,
University of Adelaide
A loss network consists of a set of
resources accessed by customers, in such a way that if the
set of needed resources is not available, the customer is
blocked and lost from the system. For instance, in a
packet-switched broadband network such as an ATM network, one
may regard each connection as requiring an amount of
bandwidth from the links that it traverses. If the
required bandwidth is available on all links of a route
between a connection's origin and destination then that
connection is accepted onto the network, if not the
connection is lost. Loss networks can also be used to model
cellular phone systems, digital packet switched integrated
services networks and database access problems. In these
talks we shall discuss some properties of loss networks,
giving particular emphasis to performance analysis,
management of these networks and paradoxical behaviour that
can occur.
Peter Taylor received a B.Sc. in 1980 and a
Ph.D. In applied mathematics in 1987 at the University of
Adelaide, where he is now an associate professor in the
Department of Applied Mathematics. He also worked three years
for the Australian Public Service in Canberra. His research
interests are in stochastic processes and applied
probability, with particular emphasis on teletraffic and
biological applications. He is currently a Co-Director of the
Teletraffic Research Centre at the University of Adelaide and
has recently been appointed an associate editor of Queueing
Systems.
Location
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IBM
International Chair
