Re: [Idnet] IDN dedicated session call for case
Albert Cabellos <albert.cabellos@gmail.com> Wed, 09 August 2017 02:44 UTC
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From: Albert Cabellos <albert.cabellos@gmail.com>
Date: Wed, 09 Aug 2017 11:44:21 +0900
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To: yanshen <yanshen@huawei.com>
Cc: "idnet@ietf.org" <idnet@ietf.org>, Özgü Alay <ozgu@simula.no>
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Subject: Re: [Idnet] IDN dedicated session call for case
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Hi Yanshen In my view they are not the same use-case - QoS use-case: As far as I understand here you aim to configure the routing/switching infrastructure to achieve QoS for flows. - QoE use-case: Here the idea is that QoE can not typically be measured directly over the network, it has to be measured either over the application (e.g., buffering in on-demand video services) or by polling the human users. Thus, measuring QoE is expensive. What can be measured are the low-level network metrics (delay, jitter, SNR, etc). Then the question is, which is the relation between low-level metrics and QoE metrics? The idea is to create a data-set containing low-level and QoE metrics. Then and thanks to ML we model the relation between low-level and QoE metrics, this means that we understand that when delay<N, jitter<M and SNR>K QoE levels are satisfactory. With this, operators know what low-level performance they need to target to offer good QoE. A nice relation is that once you establish the target performance of low-level metrics to achieve QoE, you can then use the 'QoS use-case' (or similar) to operate the network. Albert On Tue, Aug 8, 2017 at 7:02 PM, yanshen <yanshen@huawei.com> wrote: > Dear Albert, > > > > At least two supporters you have : ) > > > > I think that the QoS and QoE is just similar with my opinion mentioned > before that is the data can be divided into subjective and objective. This > will be related with the data format and the way of obtaining. And your > case build up a bridge between the subjective and objective. > > > > Yansen > > > > > > *From:* Özgü Alay [mailto:ozgu@simula.no] > *Sent:* Tuesday, August 08, 2017 2:02 PM > *To:* Albert Cabellos <albert.cabellos@gmail.com> > *Cc:* yanshen <yanshen@huawei.com>; idnet@ietf.org > *Subject:* Re: [Idnet] IDN dedicated session call for case > > > > Dear Albert, > > We are interested in this use case and will support the activities in this > area. > > Best Regards, > > Özgü > > > > On 8 August 2017 at 06:52, Albert Cabellos <albert.cabellos@gmail.com> > wrote: > > 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 > > >
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- Re: [Idnet] 答复: IDN dedicated session call for ca… yanshen
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- Re: [Idnet] 答复: IDN dedicated session call for ca… 김민석