Re: [Idnet] Applying AI into network management//FW: [nmrg] 45th NMRG meeting: Call for Contributions
Sheng Jiang <jiangsheng@huawei.com> Wed, 20 September 2017 03:29 UTC
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From: Sheng Jiang <jiangsheng@huawei.com>
To: "Diego R. Lopez" <diego.r.lopez@telefonica.com>, "Ciavaglia, Laurent (Nokia - FR/Nozay)" <laurent.ciavaglia@nokia-bell-labs.com>, yanshen <yanshen@huawei.com>, "idnet@ietf.org" <idnet@ietf.org>
Thread-Topic: [Idnet] Applying AI into network management//FW: [nmrg] 45th NMRG meeting: Call for Contributions
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Date: Wed, 20 Sep 2017 03:28:52 +0000
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Subject: Re: [Idnet] Applying AI into network management//FW: [nmrg] 45th NMRG meeting: Call for Contributions
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Thanks, Diego & Shen, for your volunteer & contribution. Your presentations have been counted in. We are waiting for more volunteers & presentations. Hopefully, we would be able to work out a agenda before the end of this month. Best regards, Sheng > -----Original Message----- > From: Diego R. Lopez [mailto:diego.r.lopez@telefonica.com] > Sent: Wednesday, September 20, 2017 3:06 AM > To: Ciavaglia, Laurent (Nokia - FR/Nozay); yanshen; Sheng Jiang; > idnet@ietf.org > Subject: Re: [Idnet] Applying AI into network management//FW: [nmrg] > 45th NMRG meeting: Call for Contributions > > Hi, > > I'd like to propose a presentation on the results of the COGNET project, > including the double closed loop we have been devising as main > architecture, and the results on dataset generation. > > Be goode, > > -- > "Esta vez no fallaremos, Doctor Infierno" > > Dr Diego R. Lopez > Telefonica I+D > http://people.tid.es/diego.lopez/ > > e-mail: diego.r.lopez@telefonica.com > Tel: +34 913 129 041 > Mobile: +34 682 051 091 > ---------------------------------- > > > On 19/9/2017, 09:34 , "IDNET on behalf of Ciavaglia, Laurent (Nokia - > FR/Nozay)" <idnet-bounces@ietf.org on behalf of > laurent.ciavaglia@nokia-bell-labs.com> wrote: > > 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 mailing list > IDNET@ietf.org > https://www.ietf.org/mailman/listinfo/idnet > > > > ________________________________ > > Este mensaje y sus adjuntos se dirigen exclusivamente a su destinatario, > puede contener información privilegiada o confidencial y es para uso > exclusivo de la persona o entidad de destino. Si no es usted. el > destinatario indicado, queda notificado de que la lectura, utilización, > divulgación y/o copia sin autorización puede estar prohibida en virtud de > la legislación vigente. Si ha recibido este mensaje por error, le rogamos > que nos lo comunique inmediatamente por esta misma vía y proceda a > su destrucción. > > The information contained in this transmission is privileged and > confidential information intended only for the use of the individual or > entity named above. If the reader of this message is not the intended > recipient, you are hereby notified that any dissemination, distribution or > copying of this communication is strictly prohibited. If you have received > this transmission in error, do not read it. Please immediately reply to the > sender that you have received this communication in error and then > delete it. > > Esta mensagem e seus anexos se dirigem exclusivamente ao seu > destinatário, pode conter informação privilegiada ou confidencial e é > para uso exclusivo da pessoa ou entidade de destino. Se não é vossa > senhoria o destinatário indicado, fica notificado de que a leitura, > utilização, divulgação e/ou cópia sem autorização pode estar proibida > em virtude da legislação vigente. Se recebeu esta mensagem por erro, > rogamos-lhe que nos o comunique imediatamente por esta mesma via e > proceda a sua destruição
- [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