[Tccc] Learning for Networking, Sigmetrics Workshop 2009, call for paper

Call for papers: Learning for Networking, Workshop

Learning for Networking
Held in conjunction with SIGMETRICS/Performance 2009
June 15, 2009 - Seattle, WA

Goal: Communication and computer networks are becoming increasingly
complex in their architecture and control features to accommodate growing
diversity of services. For example, heterogeneity arises from the
different types of networks and technologies and leads to high dimensional
models with inter-dependent variables. The scalability challenge arises as
networks serve increasing numbers of users and communities and are
required to offer wider arrays of computations and services.

More and more automated and intelligent approaches have been applied to
networking to tackle these challenges. Adaptive learning provides a
theoretical and algorithmic foundation to those intelligent approaches.
But the potential of learning in networking is yet to be explored. For
example, it will require combining techniques from adaptive learning with
new architectural concepts in networking to make the network self-aware
and self-managing.

Scope: This workshop hopes to stimulate further interest in the
interdisciplinary area of learning for networking by facilitating sharing
of lessons learned and exploring potential future directions. This
workshop is organized for the first time at Sigmetrics, combining
knowledge in both learning and networking. The workshop encourages
original contributions that address how adaptive learning contributes to
the science and applications of networking. In particular, the submissions
may address the following, but not limited to, topics:

* Networking models, mechanisms and protocols which facilitate and
utilize learning to
enhance performance.
* Approaches for acquiring and modeling the knowledge needed for
control and management of heterogeneous and large networks.
* Learning approaches for network control and management.
* Learning approaches for analyzing network performance.
* Learning approaches for extracting information from large amount of
heterogeneous network data.

The workshop also intends to provide a forum for active discussions among
speakers and participants.

Submission Guidelines

Authors are welcome to submit a 4-page abstract in the standard ACM format
to EDAS by the below deadline. The extended abstract will be reviewed by
the Workshop TPC. Accepted abstracts will be published by Performance
Evaluation for distribution in the community. Authors of high quality
selected abstracts will be encouraged to submit extended papers to a
potential special issue at an IEEE Journal.

Important Dates

* Abstract submission : May 5, 2009
* Author notification: May 20, 2009
* Final abstract due: May 30, 2009
* Workshop: June 15, 2009

Organization

* Program Committee:
Timothy Brown, Univ. of Colorado
Ritu Chadha, Telcordia
Mark Coates, McGill University
Tin-Kan Ho, Bell-labs Alcatel-Lucent
Chuanyi Ji, Georgia Tech (Workshop Co-Chair)
Vladimir Marbukh, NIST
Craig Partridge, BBN
Guy Pujolle, Pierre et Marie Curie University
Chris Ramming, Intel
Fei Sha, USC
Johnathan Smith, Univ. of Pennsylvania
Pravin Varaiya, UC Berkeley
Akshaya K. Vashist, Telcordia
Anwar Walid, Bell-Labs Alcatel-Lucent (Workshop Co-Chair)

Learning for Networking Workshop Sponsors:

Microsoft Research, Sigmetrics

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