Re: [Idnet] Applying AI into network management//FW: [nmrg] 45th NMRG meeting: Call for Contributions
yanshen <yanshen@huawei.com> Tue, 19 September 2017 07:43 UTC
Return-Path: <yanshen@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 F0D4313208E for <idnet@ietfa.amsl.com>; Tue, 19 Sep 2017 00:43:36 -0700 (PDT)
X-Virus-Scanned: amavisd-new at amsl.com
X-Spam-Flag: NO
X-Spam-Score: -4.22
X-Spam-Level:
X-Spam-Status: No, score=-4.22 tagged_above=-999 required=5 tests=[BAYES_00=-1.9, RCVD_IN_DNSWL_MED=-2.3, RCVD_IN_MSPIKE_H3=-0.01, RCVD_IN_MSPIKE_WL=-0.01, SPF_PASS=-0.001, URIBL_BLOCKED=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 3Avuy1F_Ne3P for <idnet@ietfa.amsl.com>; Tue, 19 Sep 2017 00:43:34 -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 EF120126DFE for <idnet@ietf.org>; Tue, 19 Sep 2017 00:43:33 -0700 (PDT)
Received: from 172.18.7.190 (EHLO LHREML712-CAH.china.huawei.com) ([172.18.7.190]) by lhrrg01-dlp.huawei.com (MOS 4.3.7-GA FastPath queued) with ESMTP id DVT05681; Tue, 19 Sep 2017 07:43:31 +0000 (GMT)
Received: from DGGEMM404-HUB.china.huawei.com (10.3.20.212) by LHREML712-CAH.china.huawei.com (10.201.108.35) with Microsoft SMTP Server (TLS) id 14.3.301.0; Tue, 19 Sep 2017 08:43:30 +0100
Received: from DGGEMM505-MBX.china.huawei.com ([169.254.1.237]) by DGGEMM404-HUB.china.huawei.com ([10.3.20.212]) with mapi id 14.03.0301.000; Tue, 19 Sep 2017 15:41:47 +0800
From: yanshen <yanshen@huawei.com>
To: "Ciavaglia, Laurent (Nokia - FR/Nozay)" <laurent.ciavaglia@nokia-bell-labs.com>, Sheng Jiang <jiangsheng@huawei.com>, "idnet@ietf.org" <idnet@ietf.org>
Thread-Topic: Applying AI into network management//FW: [nmrg] 45th NMRG meeting: Call for Contributions
Thread-Index: AdMsmrntJhqPpIrCTTyzoU5Pp27WrAEdz9xgAAHVMtAAAFGo8A==
Date: Tue, 19 Sep 2017 07:41:46 +0000
Message-ID: <6AE399511121AB42A34ACEF7BF25B4D2999C90@DGGEMM505-MBX.china.huawei.com>
References: <5D36713D8A4E7348A7E10DF7437A4B927CE8D980@NKGEML515-MBX.china.huawei.com> <6AE399511121AB42A34ACEF7BF25B4D2999C19@DGGEMM505-MBX.china.huawei.com> <HE1PR0701MB22036184FE053D4598352DB6E8600@HE1PR0701MB2203.eurprd07.prod.outlook.com>
In-Reply-To: <HE1PR0701MB22036184FE053D4598352DB6E8600@HE1PR0701MB2203.eurprd07.prod.outlook.com>
Accept-Language: zh-CN, en-US
Content-Language: zh-CN
X-MS-Has-Attach:
X-MS-TNEF-Correlator:
x-originating-ip: [10.130.179.89]
Content-Type: text/plain; charset="us-ascii"
Content-Transfer-Encoding: quoted-printable
MIME-Version: 1.0
X-CFilter-Loop: Reflected
X-Mirapoint-Virus-RAPID-Raw: score=unknown(0), refid=str=0001.0A020203.59C0CAA4.005D, ss=1, re=0.000, recu=0.000, reip=0.000, cl=1, cld=1, fgs=0, ip=169.254.1.237, so=2013-06-18 04:22:30, dmn=2013-03-21 17:37:32
X-Mirapoint-Loop-Id: 0861a0ca866d4d0aada492a9c88cb69a
Archived-At: <https://mailarchive.ietf.org/arch/msg/idnet/CLPhdOzzQXxooSM_aWss18NGIp0>
Subject: Re: [Idnet] Applying AI into network management//FW: [nmrg] 45th NMRG meeting: Call for Contributions
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: Tue, 19 Sep 2017 07:43:37 -0000
Dear Laurent, Thanks for your answer. Yansen > -----Original Message----- > From: Ciavaglia, Laurent (Nokia - FR/Nozay) > [mailto:laurent.ciavaglia@nokia-bell-labs.com] > Sent: Tuesday, September 19, 2017 3:34 PM > To: yanshen <yanshen@huawei.com>; Sheng Jiang <jiangsheng@huawei.com>; > idnet@ietf.org > Subject: RE: Applying AI into network management//FW: [nmrg] 45th NMRG > meeting: Call for Contributions > > Dear Yansen, all, > > We (NMRG chairs) will coordinate with Sheng/IDNET for defining the agenda. > Please send your proposal to either lists. > > Thanks, Laurent. > > > -----Original Message----- > From: IDNET [mailto:idnet-bounces@ietf.org] On Behalf Of yanshen > Sent: Tuesday, September 19, 2017 8:48 AM > To: Sheng Jiang <jiangsheng@huawei.com>; idnet@ietf.org > Subject: Re: [Idnet] Applying AI into network management//FW: [nmrg] 45th > NMRG meeting: Call for Contributions > > Hi Sheng, > > I would like to have a short presentation about the Use case of Traffic > Prediction/QoS Model. > > My question is how to "register"? I directly send Email to the NMRG chair or > we have a pre-registration in IDNet ? > > I attach the brief summary of use cases in the end. Hope it helpful. > > Yansen > > > ========================================== > 1. Gap and Requirement Analysis > 1.1 Network Management requirement > 1.2 TBD > 2. Use Cases > 2.1 Traffic Prediction > Proposed by: yanshen@huawei.com > Track: > https://www.ietf.org/mail-archive/web/idnet/current/msg00131.html > Abstract: Collect the history traffic data and external data which may > influence the traffic. Predict the traffic in short/long/specific term. Avoid the > congestion or risk in previously. > > 2.2 QoS Management > Proposed by: yanshen@huawei.com > Track: > https://www.ietf.org/mail-archive/web/idnet/current/msg00131.html > Abstract: Use multiple paths to distribute the traffic flows. Adjust the > percentages. Avoid congestion and ensure QoS. > > 2.3 Application (and/or DDoS) detection > Proposed by: aydinulas@gmx.net > Track: > https://www.ietf.org/mail-archive/web/idnet/current/msg00133.html > Abstract: Detect the application (or attack) from network packets > (HTTPS or plain) Collect the history traffic data and identify a service or attack > (ex: Skype, Viber, DDoS attack etc.) > > 2.4 QoE Management > Proposed by: albert.cabellos@gmail.com > Track: > https://www.ietf.org/mail-archive/web/idnet/current/msg00137.html > Abstract: Collect low-level metrics (SNR, latency, jitter, losses, etc) > and measure QoE. Then use ML to understand what is the relation between > satisfactory QoE and the low-level metrics. As an example learn that when > delay>N then QoE is degraded, but when M<delay<N then QoE is satisfactory > for the customers (please note that QoE cannot be measured directly over your > network). This is useful to understand how the network must be operated to > provide satisfactory QoE. > > 2.5 (Encrypted) Traffic Classification > Proposed by: jerome.francois@inria.fr; mskim16@etri.re.kr > Track: [Jerome] > https://www.ietf.org/mail-archive/web/idnet/current/msg00141.html ; > [Min-Suk Kim] > https://www.ietf.org/mail-archive/web/idnet/current/msg00153.html > Abstract: > [Jerome] collect flow-level traffic metrics such as protocol > information but also meta metrics such as distribution of packet sizes, > inter-arrival times... Then use such information to label the traffic with the > underlying application assuming that the granularity of classification may vary > (type of application, exact application name, version...) > [Min-Suk Kim]continuously collect packet data, then applying > learning process for traffic classification with generating application using deep > learning models such as CNN (convolutional neural network) and RNN > (recurrent neural network). Data-set to apply into the models are generated by > precessing with features of information from flow in packet data. > > 2.6 Anomaly Detection > Proposed by: steniofernandes@gmail.com > Track: > https://www.ietf.org/mail-archive/web/idnet/current/msg00186.html > Abstract: > [Jerome] collect flow-level traffic metrics such as protocol > information but also meta metrics such as distribution of packet sizes, > inter-arrival times... Then use such information to label the traffic with the > underlying application assuming that the granularity of classification may vary > (type of application, exact application name, version...) > [Min-Suk Kim]continuously collect packet data, then applying > learning process for traffic classification with generating application using deep > learning models such as CNN (convolutional neural network) and RNN > (recurrent neural network). Data-set to apply into the models are generated by > precessing with features of information from flow in packet data. > > 3. Data Focus > 3.1 Data attribute > 3.2 Data format > 3.3 TBD > > 4. Support Technologies > 4.1 Benchmarking Framework > Proposed by: pedro@nict.go.jp > Track: > https://www.ietf.org/mail-archive/web/idnet/current/msg00146.html > Abstract: A proper benchmarking framework comprises a set of > reference procedures, methods, and models that can (or better *must*) be > followed to assess the quality of an AI mechanism proposed to be applied to > the network management/control area. Moreover, and much more specific to > the IDNET topics, is the inclusion, dependency, or just the general relation of a > standard format enforced to the data that is used (input) and produced (output) > by the framework, so a kind of "data market" can arise without requiring to > transform the data. The initial scope of input/output data would be the > datasets, but also the new knowledge items that are stated as a result of > applying the benchmarking procedures defined by the framework, which can be > collected together to build a database of benchmark results, or just contrasted > with other existing entries in the database to know the position of the solution > just evaluated. This increases the usefulness of IDNET. > > 4.2 TBD > > ========================================= > > > -----Original Message----- > > From: IDNET [mailto:idnet-bounces@ietf.org] On Behalf Of Sheng Jiang > > Sent: Wednesday, September 13, 2017 10:20 PM > > To: idnet@ietf.org > > Subject: [Idnet] Applying AI into network management//FW: [nmrg] 45th > > NMRG > > meeting: Call for Contributions > > > > Hi, IDNet, > > > > After coordinating with NMRG chairs, a Call for Contributions message > > (see > > below) has been sent by them to the NMRG mailing list regarding to the > > topic of applying AI into network management. This is in line with our > > earlier discussion to have a session on this in NMRG, Singapore. You > > could send email to volunteer for presentations in either NMRG or > > IDNet mailing list (I will bridge to NMRG chairs in the IDNet case) or cross > post. > > > > Looking forward for your contributions and good discussion in Singapore. > > > > Best regards, > > > > Sheng > > > > -----Original Message----- > > From: nmrg [mailto:nmrg-bounces@irtf.org] On Behalf Of Lisandro > > Zambenedetti Granville > > Sent: Wednesday, September 13, 2017 9:57 PM > > To: nmrg@irtf.org > > Subject: [nmrg] 45th NMRG meeting: Call for Contributions > > > > Call for Contributions > > 45th NMRG meeting at IETF 100 > > > > In the next IETF100/Singapore we will be organizing the 45th NMRG meeting. > > We would like to center the upcoming meeting around the use of > > artificial intelligence (AI) for network management, including related > > topics as diverse as machine-learning and intelligent-defined networks, for > example. > > > > AI for network management is not a new topic, as can be easily > > observed in the literature produced by the network management community > already years ago. > > On the other hand, AI has matured a lot, finding applications is several areas. > > People interested in the subject also formed communities that can > > contribute too. As such, revisiting AI for network management is not > > only appropriate but also timely. > > > > In this Call for Contributions we would like to receive proposals of > > presentations/discussions for the upcoming 45th NMRG meeting. That > > includes, for example: > > > > - Use cases where AI could/should be used in network management > > - Real-life experiments, results, and findings on AI for network > > management > > - Disruptive and/or new management paradigms based on AI > > - Potential standard requirements for applying AI for network > > management > > - Both preliminary and mature approaches > > > > Please contribute and feel free to distribute this call to other > > mailing lists whose members you believe would be interested and could > contribute too. > > > > Best regards, Lisandro and Laurent. > > _______________________________________________ > > nmrg mailing list > > nmrg@irtf.org > > https://www.irtf.org/mailman/listinfo/nmrg > > _______________________________________________ > > IDNET mailing list > > IDNET@ietf.org > > https://www.ietf.org/mailman/listinfo/idnet > > _______________________________________________ > IDNET mailing list > IDNET@ietf.org > https://www.ietf.org/mailman/listinfo/idnet
- [Idnet] Applying AI into network management//FW: … Sheng Jiang
- Re: [Idnet] Applying AI into network management//… yanshen
- Re: [Idnet] Applying AI into network management//… Ciavaglia, Laurent (Nokia - FR/Nozay)
- Re: [Idnet] Applying AI into network management//… yanshen
- Re: [Idnet] Applying AI into network management//… Diego R. Lopez
- Re: [Idnet] Applying AI into network management//… Sheng Jiang
- Re: [Idnet] Applying AI into network management//… Albert Cabellos
- Re: [Idnet] Applying AI into network management//… Alex Galis
- Re: [Idnet] Applying AI into network management//… Sheng Jiang
- Re: [Idnet] Applying AI into network management//… Albert Cabellos
- Re: [Idnet] Applying AI into network management//… stephane.senecal