Call for Papers: Advances in Learning for Networking, Sigmetrics Workshop
June 15, 2009
Seattle, WA, USA

In conjunction with Sigmetrics/Performance Evaluation, 2009
Sponsored by ACM Sigmetrics
http://conferences.sigmetrics.org/sigmetrics/2009/workshops.shtml


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, 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 that model and learn the knowledge needed for control and 
management of
heterogeneous and large networks.
* Learning approaches that are used for analyzing the performance of networks.
* Learning approaches that extract information from a large amount of network 
data.

Submission:
May 5: Abstract due
May 20: Author notification
May 30: Final abstract due

Authors are welcome to submit a 4-page abstract in Sigmetrics format (
http://acm.org/sigs/publications/proceedings-templets) by the above 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. The workshop also intends to provide a forum for active discussions 
among speakers and
participants.

Workshop Organizers: Chuanyi Ji (Georgia Tech), Anwar Walid (Bell-labs, 
Alcatel-Lucent)

TPC members: TBA
----
[[ Petri Nets World:                                                ]]
[[              http://www.informatik.uni-hamburg.de/TGI/PetriNets/ ]]
[[ Mailing list FAQ:                                                ]]
[[ http://www.informatik.uni-hamburg.de/TGI/PetriNets/pnml/faq.html ]]
[[ Post messages/summary of replies:                                ]]
[[                               [email protected] ]]

Reply via email to