-------- Original Message -------- Subject: [Tccc] SIGMETRICS 2005 - CFP Date: Tue, 25 Jan 2005 15:13:47 -0200 (BRDT) From: Jussara Marques de Almeida jussara@dcc.ufmg.br To: tccc@cs.columbia.edu

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CALL FOR PAPERS

LSNI Workshop 2005 Sigmetrics '05 Workshop on Large Scale Network Inference (LSNI): Methods, Validation, and Applications

In recent years, large scale network inference has attracted significant interest within the research community. On one front, considerable progress has been made on traffic matrix estimation. Solutions have been proposed to estimate the amount of traffic flowing between any pair of ingress and egress points within an IP network simply based on the total amount of traffic recorded over IP links. On another front, efforts are being made to detect the state of the network from end to end measurements using inference techniques or to infer the traffic workload by exploiting application behavior. In essence, the full instrumentation of the state of an IP network is still considered a cost prohibitive task and inference may be the only tool we have to understand the behavior of such large scale systems. The potential benefits of the proposed estimation techniques can be great. Accurate measurement of an IP traffic matrix is essential for network design and planning. Moreover, accurate estimation of the network state can facilitate troubleshooting and performance evaluation.

The focus of this workshop will be on the state of the art of large-scale network inference techniques in these areas and their potential applications. More specifically, we will solicit papers on the evaluation of the proposed techniques and their possible shortcomings. Of particular interest are papers that address the impact of estimation errors on the applications making use of traffic matrices and network tomography techniques. Lastly, we are interested in understanding the future of this area and its impact on network design and management.

We solicit 6-page long papers that present work in progress related to the following topics: traffic matrix estimation techniques passive and active network tomography techniques validation methods scalability, robustness, sensitivity issues in large scale inference adaptive and continuous network inference practical applications and operational experience impact of sampling errors on estimation accuracy

The accepted papers will be published in the workshop proceedings, while an extended abstract of the submitted paper will be available in a special issue of Performance Evaluation Review (PER), which is sent to all Sigmetrics members and appears in the ACM digital library.

Important dates: Submission: March 25th, 2005 Author Notification: May 5th, 2005 Camera ready due: May 27th, 2005 Workshop: June 6th, 2005 (tentative)

Technical Program Committee Mark Coates Dept. Electrical and Computer Engineering, McGill University, Canada Mark Crovella Computer Science Department, Boston University, U.S.A. Nick Duffield AT&T Research, U.S.A. Mikael Johansson Royal Institute of Technology, Sweden Antonio NucciSprint Advanced Technology Labs, U.S.A. Konstantina Papagiannaki Intel Research Cambridge, U.K. Matt Roughan University of Adelaide, Australia Don Towsley University of Massachusetts, U.S.A. Darryl Veitch University of Melbourne/National ICT Australia (NICTA), Australia Bin Yu Department of Statistics, University of California Berkeley, U.S.A. Yin Zhang University of Texas, U.S.A.

Workshop organizing chairs:

Dina Papagiannaki, Intel Research Cambridge, Yin Zhang, Computer Science Department, University of Texas

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