From nobody Wed Dec 6 02:00:21 2017 Return-Path: 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 576A3127241 for ; Wed, 6 Dec 2017 02:00:20 -0800 (PST) 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, HTML_MESSAGE=0.001, RCVD_IN_DNSWL_MED=-2.3, RCVD_IN_MSPIKE_H3=-0.01, RCVD_IN_MSPIKE_WL=-0.01, SPF_PASS=-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 sT8yP4WGthvG for ; Wed, 6 Dec 2017 02:00:11 -0800 (PST) Received: from huawei.com (lhrrgout.huawei.com [194.213.3.17]) (using TLSv1.2 with cipher ECDHE-RSA-AES256-GCM-SHA384 (256/256 bits)) (No client certificate requested) by ietfa.amsl.com (Postfix) with ESMTPS id 99927126D05 for ; Wed, 6 Dec 2017 02:00:11 -0800 (PST) Received: from LHREML710-CAH.china.huawei.com (unknown [172.18.7.107]) by Forcepoint Email with ESMTP id AD8AC7F7DFB7B for ; Wed, 6 Dec 2017 10:00:07 +0000 (GMT) Received: from DGGEMM406-HUB.china.huawei.com (10.3.20.214) by LHREML710-CAH.china.huawei.com (10.201.108.33) with Microsoft SMTP Server (TLS) id 14.3.361.1; Wed, 6 Dec 2017 10:00:09 +0000 Received: from DGGEMM505-MBS.china.huawei.com ([169.254.2.114]) by DGGEMM406-HUB.china.huawei.com ([10.3.20.214]) with mapi id 14.03.0361.001; Wed, 6 Dec 2017 18:00:03 +0800 From: yanshen To: "idnet@ietf.org" Thread-Topic: A mini note for IETF-100 close door meeting Thread-Index: AdNudM6WU+wFsmSGQz2kNumbJrM4PQ== Date: Wed, 6 Dec 2017 10:00:03 +0000 Message-ID: <6AE399511121AB42A34ACEF7BF25B4D20E575DFC@DGGEMM505-MBS.china.huawei.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: multipart/alternative; boundary="_000_6AE399511121AB42A34ACEF7BF25B4D20E575DFCDGGEMM505MBSchi_" MIME-Version: 1.0 X-CFilter-Loop: Reflected Archived-At: Subject: [Idnet] A mini note for IETF-100 close door meeting X-BeenThere: idnet@ietf.org X-Mailman-Version: 2.1.22 Precedence: list List-Id: "The IDNet \(Intelligence-Defined Network\) " List-Unsubscribe: , List-Archive: List-Post: List-Help: List-Subscribe: , X-List-Received-Date: Wed, 06 Dec 2017 10:00:20 -0000 --_000_6AE399511121AB42A34ACEF7BF25B4D20E575DFCDGGEMM505MBSchi_ Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: quoted-printable Hi all, During IETF-100, we had a short close door meeting in Singapore and had a d= iscussion about the standard work next step. I have uploaded the whiteboard picture at: https://github.com/Yarchmage/idn= et/blob/master/ietf100idnetclosedoormeeting.jpg A mini note as following: 1. Request input for ML vs dataset and policy. Which one is better fo= r standard work? 2. Description of output. How to "translate" the numeric output of al= gorithm into network configuration/parameters/... ? 3. Evaluation. E.g. how to define the intent "low delay" from the vie= w of network? So that we can deal with the input and output. 4. Dataset. A unification/transition of data? YANG model? Do you have thoughts about these questions? Yansen --_000_6AE399511121AB42A34ACEF7BF25B4D20E575DFCDGGEMM505MBSchi_ Content-Type: text/html; charset="us-ascii" Content-Transfer-Encoding: quoted-printable

Hi all,

 

During IETF-100, we had a short= close door meeting in Singapore and had a discussion about the standard wo= rk next step.

 

I have uploaded the whiteboard = picture at: https://github.com/Yarchmage/idnet/blob/master/ietf100idnetclosedoormeeting= .jpg

 

A mini note as following:<= /o:p>

 

1= .   &= nbsp;   Request input for ML vs= dataset and policy. Which one is better for standard work?

2= .   &= nbsp;   Description of output. = How to “translate” the numeric output of algorithm into network= configuration/parameters/… ?

3= .   &= nbsp;   Evaluation. E.g. how to= define the intent “low delay” from the view of network? So tha= t we can deal with the input and output.

4= .   &= nbsp;   Dataset. A unification/= transition of data? YANG model?

 

 

Do you have thoughts about thes= e questions?

 

Yansen

 

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