[Idnet] Calll for participation - "Learning Methods for Control of Communication Networks"

Trimponias Georgios <g.trimponias@huawei.com> Thu, 27 April 2017 02:47 UTC

Return-Path: <g.trimponias@huawei.com>
X-Original-To: idnet@ietfa.amsl.com
Delivered-To: idnet@ietfa.amsl.com
Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 42016129443 for <idnet@ietfa.amsl.com>; Wed, 26 Apr 2017 19:47:11 -0700 (PDT)
X-Virus-Scanned: amavisd-new at amsl.com
X-Spam-Flag: NO
X-Spam-Score: -4.221
X-Spam-Level:
X-Spam-Status: No, score=-4.221 tagged_above=-999 required=5 tests=[BAYES_00=-1.9, HTML_MESSAGE=0.001, RCVD_IN_DNSWL_MED=-2.3, RCVD_IN_MSPIKE_H3=-0.01, RCVD_IN_MSPIKE_WL=-0.01, RP_MATCHES_RCVD=-0.001, SPF_PASS=-0.001] autolearn=ham autolearn_force=no
Received: from mail.ietf.org ([4.31.198.44]) by localhost (ietfa.amsl.com [127.0.0.1]) (amavisd-new, port 10024) with ESMTP id rCGuZgC55yxg for <idnet@ietfa.amsl.com>; Wed, 26 Apr 2017 19:47:09 -0700 (PDT)
Received: from lhrrgout.huawei.com (lhrrgout.huawei.com [194.213.3.17]) (using TLSv1 with cipher RC4-SHA (128/128 bits)) (No client certificate requested) by ietfa.amsl.com (Postfix) with ESMTPS id 712A01294D3 for <idnet@ietf.org>; Wed, 26 Apr 2017 19:47:08 -0700 (PDT)
Received: from 172.18.7.190 (EHLO lhreml704-cah.china.huawei.com) ([172.18.7.190]) by lhrrg01-dlp.huawei.com (MOS 4.3.7-GA FastPath queued) with ESMTP id DLV25730; Thu, 27 Apr 2017 02:47:05 +0000 (GMT)
Received: from SZXEMI404-HUB.china.huawei.com (10.82.75.40) by lhreml704-cah.china.huawei.com (10.201.108.45) with Microsoft SMTP Server (TLS) id 14.3.301.0; Thu, 27 Apr 2017 03:47:04 +0100
Received: from SZXEMI501-MBS.china.huawei.com ([169.254.2.140]) by SZXEMI404-HUB.china.huawei.com ([10.82.75.40]) with mapi id 14.03.0235.001; Thu, 27 Apr 2017 10:47:00 +0800
From: Trimponias Georgios <g.trimponias@huawei.com>
To: "idnet@ietf.org" <idnet@ietf.org>
Thread-Topic: Calll for participation - "Learning Methods for Control of Communication Networks"
Thread-Index: AdK/AInox9N03HgsTV63/jgx6S0Jdg==
Date: Thu, 27 Apr 2017 02:46:59 +0000
Message-ID: <DEA98144A94CBB4D86A91B80AC73FB9648D2481E@SZXEMI501-MBS.china.huawei.com>
Accept-Language: en-US
Content-Language: en-US
X-MS-Has-Attach:
X-MS-TNEF-Correlator:
x-originating-ip: [10.194.153.192]
Content-Type: multipart/alternative; boundary="_000_DEA98144A94CBB4D86A91B80AC73FB9648D2481ESZXEMI501MBSchi_"
MIME-Version: 1.0
X-CFilter-Loop: Reflected
X-Mirapoint-Virus-RAPID-Raw: score=unknown(0), refid=str=0001.0A020201.59015BAA.0017, ss=1, re=0.000, recu=0.000, reip=0.000, cl=1, cld=1, fgs=0, ip=169.254.2.140, so=2013-06-18 04:22:30, dmn=2013-03-21 17:37:32
X-Mirapoint-Loop-Id: 536eb6ba5d4ffa237d8a47980fa6b701
Archived-At: <https://mailarchive.ietf.org/arch/msg/idnet/6VFt3MzQO9YtfLhl2Zqxb4hCStE>
X-Mailman-Approved-At: Wed, 26 Apr 2017 19:58:29 -0700
Subject: [Idnet] Calll for participation - "Learning Methods for Control of Communication Networks"
X-BeenThere: idnet@ietf.org
X-Mailman-Version: 2.1.22
Precedence: list
List-Id: "The IDNet \(Intelligence-Defined Network\) " <idnet.ietf.org>
List-Unsubscribe: <https://www.ietf.org/mailman/options/idnet>, <mailto:idnet-request@ietf.org?subject=unsubscribe>
List-Archive: <https://mailarchive.ietf.org/arch/browse/idnet/>
List-Post: <mailto:idnet@ietf.org>
List-Help: <mailto:idnet-request@ietf.org?subject=help>
List-Subscribe: <https://www.ietf.org/mailman/listinfo/idnet>, <mailto:idnet-request@ietf.org?subject=subscribe>
X-List-Received-Date: Thu, 27 Apr 2017 02:54:46 -0000

Call for Participation
Learning Methods for Control of Communications Networks
RLDM Satellite Meeting
June 14-15 2017
University of Michigan, Ann Arbor

Learning methods have been successfully applied to various control problems in communications networks for more than four decades. Nevertheless, there has yet to be a concerted effort to systematically explore the potential performance benefits to be reaped by using learning methods in this domain. Given the continued growth in the size and dynamics of communications networks, in the number and location of communicating devices, and in the volume of traffic to be transported and the types of applications to be supported, the algorithms for controlling the behavior of a network should scale accordingly yet do so under uncertainty about the current state of the entire network. Learning methods hold promise for enabling large dynamic communications networks to effectively, efficiently, and autonomously accommodate increasing and varied user demand. Communications networks also offer in return a rich experimental domain for research on learning and decision making.

The goal of this meeting is to foster collaboration between the communications networks and learning communities, bringing to bear powerful learning algorithms for control of communications networks and exposing a complex domain for research on learning methods. We welcome submissions of original research describing theoretical or empirical results using learning methods for network control. Here, the term 'network control' encompasses decision making at all time scales, ranging from processing individual packets and flows to network planning and design. Learning methods that require neither a detailed model of the network nor supervisory input to make appropriate decisions are of particular interest for this meeting.

To participate in the meeting, you must prepare an extended abstract of at most four pages, inclusive of figures and references, and must submit the abstract directly to the organizers by 12 May 2017. Abstracts will be used to determine the speakers and the discussion topics for the meeting. Each participant's abstract will be made available electronically as part of the record of the meeting, provided the participant explicitly grants permission to do so.

Abstract formatting:
LaTex template: rldmsubmit.sty
LaTex example: rldm.tex
Abstract samples: rldm.pdf, rldm.rtf

Organizers:
Martha Steenstrup, Stow Research L.L.C.
George Trimponias, Huawei Technologies Co., Ltd.