Re: [Idnet] IDN dedicated session call for case

Sheng Jiang <jiangsheng@huawei.com> Tue, 08 August 2017 01:23 UTC

Return-Path: <jiangsheng@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 9AFAD124207 for <idnet@ietfa.amsl.com>; Mon, 7 Aug 2017 18:23:16 -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=unavailable 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 qbgQxtoGGC0z for <idnet@ietfa.amsl.com>; Mon, 7 Aug 2017 18:23:15 -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 2BB50124B09 for <idnet@ietf.org>; Mon, 7 Aug 2017 18:23:15 -0700 (PDT)
Received: from 172.18.7.190 (EHLO lhreml701-cah.china.huawei.com) ([172.18.7.190]) by lhrrg02-dlp.huawei.com (MOS 4.3.7-GA FastPath queued) with ESMTP id DMD74974; Tue, 08 Aug 2017 01:23:12 +0000 (GMT)
Received: from NKGEML412-HUB.china.huawei.com (10.98.56.73) by lhreml701-cah.china.huawei.com (10.201.108.42) with Microsoft SMTP Server (TLS) id 14.3.301.0; Tue, 8 Aug 2017 02:23:11 +0100
Received: from NKGEML515-MBX.china.huawei.com ([fe80::a54a:89d2:c471:ff]) by nkgeml412-hub.china.huawei.com ([10.98.56.73]) with mapi id 14.03.0235.001; Tue, 8 Aug 2017 09:23:03 +0800
From: Sheng Jiang <jiangsheng@huawei.com>
To: yanshen <yanshen@huawei.com>, "idnet@ietf.org" <idnet@ietf.org>, "nmrg@irtf.org" <nmrg@irtf.org>
Thread-Topic: IDN dedicated session call for case
Thread-Index: AdMLcu+vuWBrdNuZQwG6l2oQPpJcKAEb70gw
Date: Tue, 8 Aug 2017 01:23:03 +0000
Message-ID: <5D36713D8A4E7348A7E10DF7437A4B927CE408E8@NKGEML515-MBX.china.huawei.com>
References: <6AE399511121AB42A34ACEF7BF25B4D297A34A@DGGEMM505-MBS.china.huawei.com>
In-Reply-To: <6AE399511121AB42A34ACEF7BF25B4D297A34A@DGGEMM505-MBS.china.huawei.com>
Accept-Language: en-GB, zh-CN, en-US
Content-Language: zh-CN
X-MS-Has-Attach:
X-MS-TNEF-Correlator:
x-originating-ip: [10.111.185.119]
Content-Type: text/plain; charset="utf-8"
Content-Transfer-Encoding: base64
MIME-Version: 1.0
X-CFilter-Loop: Reflected
X-Mirapoint-Virus-RAPID-Raw: score=unknown(0), refid=str=0001.0A020206.59891281.00A4, ss=1, re=0.000, recu=0.000, reip=0.000, cl=1, cld=1, fgs=0, ip=0.0.0.0, so=2013-06-18 04:22:30, dmn=2013-03-21 17:37:32
X-Mirapoint-Loop-Id: fa10d073f6b88e98bcce9a64cf28278c
Archived-At: <https://mailarchive.ietf.org/arch/msg/idnet/zbq0A9JKm6LHUAj9pEdz4negkN8>
Subject: Re: [Idnet] IDN dedicated session call for case
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, 08 Aug 2017 01:23:16 -0000

Hi IDneter, especially the contributors, 

(copied to NMRG mail list for coordination between two groups)

It is our intention to organize a dedicated IDNet session for applying AI into network management in NMRG in IETF100, Singapore. It will depend on whether we could converge and organize good content/presentations. So far, we are actually in the stage of calling interests, use cases and contributors. We need to keep discussing and converge to specific use cases soon so that we could form a good proposal for the potential session.

Shen's work has given a constructive thought that may lead to converged content. It is welcome to everybody contribute more valuable user cases. After refining and abstracting the general element from various use cases, the potential standard points will become more and more clear. And maybe, after several round of discussion and convergence, we could understand the essential of applying AI into network management more so that we could have a good foundation to form an IETF working group for standardization work.

Regards,

Sheng

> -----Original Message-----
> From: IDNET [mailto:idnet-bounces@ietf.org] On Behalf Of yanshen
> Sent: Wednesday, August 02, 2017 6:12 PM
> To: idnet@ietf.org
> Subject: [Idnet] IDN dedicated session call for case
> 
> 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