Re: [Idnet] IDN dedicated session call for case
yanshen <yanshen@huawei.com> Mon, 14 August 2017 03:34 UTC
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From: yanshen <yanshen@huawei.com>
To: Stenio Fernandes <sflf@cin.ufpe.br>
CC: "idnet@ietf.org" <idnet@ietf.org>
Thread-Topic: [Idnet] IDN dedicated session call for case
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Date: Mon, 14 Aug 2017 03:34:03 +0000
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Subject: Re: [Idnet] IDN dedicated session call for case
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Hi Stenio, I'm looking forward to them! Yansen > -----Original Message----- > From: steniofernandes@gmail.com [mailto:steniofernandes@gmail.com] On > Behalf Of Stenio Fernandes > Sent: Tuesday, August 08, 2017 11:21 PM > To: Jérôme François <jerome.francois@inria.fr> > Cc: Diego R. Lopez <diego.r.lopez@telefonica.com>; Albert Cabellos > <albert.cabellos@gmail.com>; yanshen <yanshen@huawei.com>; > idnet@ietf.org > Subject: Re: [Idnet] IDN dedicated session call for case > > Hi Jerome, Diego, et al, > > Those are excellent use cases. I have some published work on applied machine > learning to computer networking problems, including flow-based traffic > classification. I think another use case would be applying unsupervised learning > techniques for anomaly detection. I can elaborate further on this. > > Stenio > > On Tue, Aug 8, 2017 at 10:59 AM, Jérôme François <jerome.francois@inria.fr> > wrote: > > 100% agree with you. I was far from being exhaustive as traffic > > features may depend on types of traffic (kin of sub use cases) > > > > jerome > > > > Le 08/08/2017 à 16:56, Diego R. Lopez a écrit : > > > > Hi Jerome, > > > > > > > > Agreed. This is a use case we are very much interested in, and > > actually working in it now. Just let me say we are trying to evaluate > > which are the significant features of the flow to perform a proper > > classification, depending on the flow nature (TLS, DTLS, QUIC, > > IPsec…), and that would define the concrete data to be exchanged or stored. > > > > > > > > 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 8/8/2017, 16:49 , "IDNET on behalf of Jérôme François" > > <idnet-bounces@ietf.org on behalf of jerome.francois@inria.fr> wrote: > > > > > > > > Hi all, > > > > Here is another use case about traffic classification. > > > > Use case N+3: (encrypted) traffic classification > > > > Description: 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 > > trafic with the underlying application assuming that the granularity > > of classification may vary (type of application, exact application name, > version...) > > Process: 1. collect packet information 2. flow reassembly (using > > directly flow format such as IPFIX might be possible but depends on > > the type of traffic, e.g. extracting the TLS application data is > > useful for encrypted > > traffic) 3. Collect application specific information (useful when > > targeting a single type of application) = out of network information > > 4. train the model 5. Online or offline testing 4. Apply application level > policies. > > Data Format: Time : [Start, End, Unit, Number of Value, Sampling > > Period] > > Position: [Device ID, Port ID] > > Direction: IN / OUT > > Flow level metric: packet size > > distributions, number of packets, inter-arrival time distribution, > > (+ application specific knowledge : > > payload > > parsing) > > > > Message : Request: ask for the data > > Reply: Data > > Notice: For notification or others > > Policy: Control policy > > > > > > Best regards, > > jerome > > > > > > Le 08/08/2017 à 06:52, Albert Cabellos a écrit : > > > > Hi all > > > > > > > > Here´s another use-case: > > > > > > > > Use case N+2: QoE > > Description: 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. > > Process: 1. Low-level data collection and QoE measurement ; 2. > > Training Model (input low-level metrics, output QoE); 3. Real-time > > data capture and input; 4. Predict QoE; 5. Operate network to meet > > target QoE requirement, go to 3. > > Data Format: Time : [Start, End, Unit, Number of Value, > Sampling > > Period] > > Position: [Device ID, Port ID] > > Direction: IN / OUT > > Low-level metric : SNR, Delay, Jitter, > > queue-size, etc > > > > > > Message : Request: ask for the data > > Reply: Data > > Notice: For notification or others > > Policy: Control policy > > > > > > > > Kind regards > > > > > > > > Albert > > > > > > > > On Wed, Aug 2, 2017 at 7:12 PM, yanshen <yanshen@huawei.com> wrote: > > > > Dear all, > > > > Since we plan to organize a dedicated session in NMRG, IETF100, for > > applying AI into network management (NM), I’d try to list some Use > > Cases and propose a roadmap and ToC before Nov. > > > > These might be rough. You are welcome to refine them and propose your > > focused use cases or ideas. > > > > Use case 1: Traffic Prediction > > Description: 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. > > Process: 1. Data collection (e.g. traffic sample of > > physical/logical port ); 2. Training Model; 3. Real-time data capture and input; > 4. > > Predication output; 5. Fix error and go back to 3. > > Data Format: Time : [Start, End, Unit, Number of Value, > Sampling > > Period] > > Position: [Device ID, Port ID] > > Direction: IN / OUT > > Route : [R1, R2, ..., RN] (might be > > useful for some scenarios) > > Service : [Service ID, Priority, ...] > > (Not clear how to use it but seems useful) > > Traffic: [T0, T1, T2, ..., TN] > > Message : Request: ask for the data > > Reply: Data > > Notice: For notification or others > > Policy: Control policy > > > > Use case 2: QoS Management > > Description: Use multiple paths to distribute the traffic flows. > > Adjust the percentages. Avoid congestion and ensure QoS. > > Process: 1. Data capture (e.g. traffic sample of > > physical/logical port ); 2. Training Model; 3. Real-time data capture > > and input; 4. Output percentages; 5. Fix error and go back to 3. > > Data Format: Time : [Timestamp, Value type (Delay/Packet > > Loss/...), Unit, Number of Value, Sampling Period] > > Position: [Link ID, Device ID] > > Value: [V0, V1, V2, ..., VN] > > Message : Request: ask for the data > > Reply: Data > > Notice: For notification or others > > Policy: Control policy > > > > Use case N: Waiting for your Ideas > > > > Also I suggest a roadmap before Nov if possible. > > > > ### Roadmap ### > > Aug. : Collecting the use cases (related with NM). Rough thoughts and > > requirements Sep. : Refining the cases and abstract the common > > elements Oct. : Deeply analysis. Especially on Data Format, control > > flow, or other key points > > Nov.: F2F discussions on IETF100 > > ### Roadmap End ### > > > > A rough ToC is listed in following. We may take it as a scope before Nov. > > Hope that the content could become the draft of draft. > > > > ###Table of Content### > > 1. Gap and Requirement Analysis > > 1.1 Network Management requirement > > 1.2 TBD > > 2. Use Cases > > 2.1 Traffic Prediction > > 2.2 QoS Management > > 3.3 TBD > > 3. Data Focus > > 3.1 Data attribute > > 3.2 Data format > > 3.3 TBD > > 4. Aims > > 4.1 Benchmarking Framework > > 4.2 TBD > > ###ToC End### > > > > > > Yansen > > > > _______________________________________________ > > 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 mailing list > > IDNET@ietf.org > > https://www.ietf.org/mailman/listinfo/idnet > > > > > > -- > Prof. Stenio Fernandes > CIn/UFPE > http://www.steniofernandes.com
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