From nobody Tue May 9 19:53:34 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 4585712EBB6 for ; Tue, 9 May 2017 19:53:33 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -4.221 X-Spam-Level: X-Spam-Status: No, score=-4.221 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, RP_MATCHES_RCVD=-0.001, 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 rUNFtWLuapkK for ; Tue, 9 May 2017 19:53:32 -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 7B78B129494 for ; Tue, 9 May 2017 19:53:31 -0700 (PDT) Received: from 172.18.7.190 (EHLO lhreml709-cah.china.huawei.com) ([172.18.7.190]) by lhrrg02-dlp.huawei.com (MOS 4.3.7-GA FastPath queued) with ESMTP id DGH43648; Wed, 10 May 2017 02:53:29 +0000 (GMT) Received: from NKGEML412-HUB.china.huawei.com (10.98.56.73) by lhreml709-cah.china.huawei.com (10.201.108.32) with Microsoft SMTP Server (TLS) id 14.3.301.0; Wed, 10 May 2017 03:53:28 +0100 Received: from NKGEML515-MBS.china.huawei.com ([169.254.5.200]) by nkgeml412-hub.china.huawei.com ([10.98.56.73]) with mapi id 14.03.0235.001; Wed, 10 May 2017 10:53:20 +0800 From: Sheng Jiang To: "idnet@ietf.org" Thread-Topic: Benefits of Introducing AI into Network Thread-Index: AdLJOFtrTGXqFLUbRgO5S4jI02SJ/g== Date: Wed, 10 May 2017 02:53:20 +0000 Message-ID: <5D36713D8A4E7348A7E10DF7437A4B927CD7DC87@NKGEML515-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: multipart/alternative; boundary="_000_5D36713D8A4E7348A7E10DF7437A4B927CD7DC87NKGEML515MBSchi_" MIME-Version: 1.0 X-CFilter-Loop: Reflected X-Mirapoint-Virus-RAPID-Raw: score=unknown(0), refid=str=0001.0A020205.591280A9.00C1, ss=1, re=0.000, recu=0.000, reip=0.000, cl=1, cld=1, fgs=0, ip=169.254.5.200, so=2013-06-18 04:22:30, dmn=2013-03-21 17:37:32 X-Mirapoint-Loop-Id: efef2dc39a99b1a897973c2a549b26de Archived-At: Subject: [Idnet] Benefits of Introducing AI into Network 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, 10 May 2017 02:53:33 -0000 --_000_5D36713D8A4E7348A7E10DF7437A4B927CD7DC87NKGEML515MBSchi_ Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: quoted-printable In ETSI NGP ISP, we have an Work Item for IDN (Intelligence-Defined Network= ). In one of the general sections, We briefly describes the benefits of int= roducing AI into network, as below. - Towards Fully Autonomic Network - Ability of Handling Complex Issues - More Adaptive and Flex - Predictive - Potential Self-Evolving Ability - Potential Decision Efficiency If there are major benefits that we have not covered, we would like to incl= ude. Regards, Sheng --_000_5D36713D8A4E7348A7E10DF7437A4B927CD7DC87NKGEML515MBSchi_ Content-Type: text/html; charset="us-ascii" Content-Transfer-Encoding: quoted-printable

In ETSI NGP ISP, we have an Wor= k Item for IDN (Intelligence-Defined Network). In one of the general sectio= ns, We briefly describes the benefits of introducing AI into network, as be= low.

 

-=    &n= bsp;      Towards Fully Autonomic= Network

-=    &n= bsp;      Ability of Handling Com= plex Issues

-=    &n= bsp;      More Adaptive and Flex<= o:p>

-=    &n= bsp;      Predictive

-=    &n= bsp;      Potential Self-Evolving= Ability

-=    &n= bsp;      Potential Decision Effi= ciency

 

If there are major benefits tha= t we have not covered, we would like to include.

 

Regards,

 

Sheng

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charset="windows-1252"; format=flowed Content-Transfer-Encoding: 7bit Is it possible to give a brief (or detail) description of each o the topic? On 10/05/2017 04:53, Sheng Jiang wrote: > > In ETSI NGP ISP, we have an Work Item for IDN (Intelligence-Defined > Network). In one of the general sections, We briefly describes the > benefits of introducing AI into network, as below. > > -Towards Fully Autonomic Network > > -Ability of Handling Complex Issues > > -More Adaptive and Flex > > -Predictive > > -Potential Self-Evolving Ability > > -Potential Decision Efficiency > > If there are major benefits that we have not covered, we would like to > include. > > Regards, > > Sheng > > > > _______________________________________________ > IDNET mailing list > IDNET@ietf.org > https://www.ietf.org/mailman/listinfo/idnet --------------7B9A47AD3D6EB5668957459B Content-Type: text/html; charset="windows-1252" Content-Transfer-Encoding: 8bit Is it possible to give a brief (or detail) description of each o the topic?

On 10/05/2017 04:53, Sheng Jiang wrote:

In ETSI NGP ISP, we have an Work Item for IDN (Intelligence-Defined Network). In one of the general sections, We briefly describes the benefits of introducing AI into network, as below.

 

-          Towards Fully Autonomic Network

-          Ability of Handling Complex Issues

-          More Adaptive and Flex

-          Predictive

-          Potential Self-Evolving Ability

-          Potential Decision Efficiency

 

If there are major benefits that we have not covered, we would like to include.

 

Regards,

 

Sheng



_______________________________________________
IDNET mailing list
IDNET@ietf.org
https://www.ietf.org/mailman/listinfo/idnet

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<05c9c525-eb0d-dc93-a654-c9bef27c520a@nokia-bell-labs.com> References: <5D36713D8A4E7348A7E10DF7437A4B927CD7DC87@NKGEML515-MBS.china.huawei.com> <05c9c525-eb0d-dc93-a654-c9bef27c520a@nokia-bell-labs.com> From: Manav Bhatia Date: Wed, 10 May 2017 11:58:50 +0530 Message-ID: To: Ing-Jyh Tsang Cc: Sheng Jiang , "idnet@ietf.org" Content-Type: multipart/alternative; boundary=001a113e22b8ea3fcc054f25954c Archived-At: X-Mailman-Approved-At: Wed, 10 May 2017 00:04:56 -0700 Subject: Re: [Idnet] Benefits of Introducing AI into Network 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, 10 May 2017 06:28:53 -0000 --001a113e22b8ea3fcc054f25954c Content-Type: text/plain; charset=UTF-8 I agree, since the benefits listed are quite generic and appears to give the impression that AI is the panacea to all the problems, which it clearly is not. One problem that I have with all such discussions is that these are quite vague and we tend to talk from a 20,000 feet distance. The devil is in the details. I agree that AI can help us with being able to predict events. What i dont know is even at a high level how one gets there. Can we spend some time discussing that as well? Thanks, Manav On Wed, May 10, 2017 at 11:53 AM, Ing-Jyh Tsang < ing-jyh.tsang@nokia-bell-labs.com> wrote: > Is it possible to give a brief (or detail) description of each o the > topic? > > On 10/05/2017 04:53, Sheng Jiang wrote: > > In ETSI NGP ISP, we have an Work Item for IDN (Intelligence-Defined > Network). In one of the general sections, We briefly describes the benefits > of introducing AI into network, as below. > > > > - Towards Fully Autonomic Network > > - Ability of Handling Complex Issues > > - More Adaptive and Flex > > - Predictive > > - Potential Self-Evolving Ability > > - Potential Decision Efficiency > > > > If there are major benefits that we have not covered, we would like to > include. > > > > Regards, > > > > Sheng > > > _______________________________________________ > IDNET mailing listIDNET@ietf.orghttps://www.ietf.org/mailman/listinfo/idnet > > > > _______________________________________________ > IDNET mailing list > IDNET@ietf.org > https://www.ietf.org/mailman/listinfo/idnet > > --001a113e22b8ea3fcc054f25954c Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable
I agree, since the benefits listed are quite generic and a= ppears to give the impression that AI is the panacea to all the problems, w= hich it clearly is not. One problem that I have with all such discussions i= s that these are quite vague and we tend to talk from a 20,000 feet distanc= e. The devil is in the details. I agree that AI can help us with being able= to predict events. What i dont know is even at a high level how one gets t= here. Can we spend some time discussing that as well?

Th= anks, Manav

On= Wed, May 10, 2017 at 11:53 AM, Ing-Jyh Tsang <ing-jyh.tsa= ng@nokia-bell-labs.com> wrote:
=20 =20 =20
Is it possible to give a brief (or detail) description of each o the topic?

On 10/05/2017 04:5= 3, Sheng Jiang wrote:
=20 =20 =20

In ETSI NGP ISP, we hav= e an Work Item for IDN (Intelligence-Defined Network). In one of the general sections, We briefly describes the benefits of introducing AI into network, as below.<= /p>

=C2=A0

-=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 Towards Fully Autonomic Network

-=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 Ability of Handling Complex Issues

-=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 More Adaptive and Flex

-=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 Predictive

-=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 Potential Self-Evolving Ability

-=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 Potential Decision Efficiency

=C2=A0

If there are major benefits that we have not covered, we would like to include.=

=C2=A0

Regards,<= /span>

=C2=A0

Sheng



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ailman/listinfo/idnet


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Dear In= g-Jyh Tsang and all,

&n= bsp;

There i= s some personal thought of these topics. Comments and suggestions are most = welcome!

&n= bsp;

--Towar= ds Fully Autonomic Network

&n= bsp;

 &= nbsp;      The advantage (or say aim) of a fully a= utonomic network is implementing the close-ring of =A1=B0Sensing-Analysis-D= ecision=A1=B1, which will minimize the input of manual labor in the pure op= erating actions (without analysis). In current, the process of sensing, analysis a= nd decision are independent to each other and the cooperation of these is d= epend on manual work. The shortage is caused by the lack of analysis abilit= y of network, which is exactly AI technology is good at.

&n= bsp;

--Abili= ty of Handling Complex Issues

&n= bsp;

 &= nbsp;      The machine learning (ML) method is one= of the best way to solve the complex problems, such as classifying problem= s and optimal decision problems. In network area, the problems that related to resource management and route decision are typically complex. The intro= ducing of AI method essentially build up a centralized analysis system whic= h may provide a global view solution for the network, which cannot (or diff= icult) be implemented with the current highly distributed architecture. A centralized architecture may not solve = all problems but it is indeed a good supplement for nowadays network.<= /o:p>

 &= nbsp;     

--More = Adaptive and Flex

&n= bsp;

 &= nbsp;     The ML model can output different policies ac= cording to the input training data. Each domain of network may own differen= t characters (e.g. different traffic character). It is possible to provide adaptive solution for different situation via uniform train model.

&n= bsp;

--Predi= ctive

&n= bsp;

 &= nbsp;      Prediction is one of the most important= attribute that AI technology brings. On one hand, the prediction (e.g. tra= ffic prediction or failure prediction) that produced by AI algorithm can make the network manager preventing the risky failure and nip the problem = in the bud. It will reduce the risk of network fault so that the cost of re= covering from the failure. On the other hand, the prediction can be also us= ed to evaluate the reliability of network policy. For example, to evaluate what is the probability of a VPN = route is faced with congestion.

&n= bsp;

--Poten= tial Self-Evolving Ability

&n= bsp;

 &= nbsp;      The ML method is self-evolving, which m= ay provide same attribute to network. According to training the network dec= ision model continuously, the network can match the change of service and traffic. Actually, the optimization is just the process that modifying the= network parameters to match the requirement. The self-evolving feature of = ML method may bring the same ability to the network.

&n= bsp;

--Poten= tial Decision Efficiency

&n= bsp;

 &= nbsp;      The machine learning algorithm can solv= e the decision problems which has been verified in other area (e.g. AlphaGo= ). It will be valuable to train a decision model of network that input the current state and output corresponding policies (e.g. device configuration= parameters). This model may configure the network device directly when nec= essary or provide probable configurations as choices when doubt. Both of th= em will save the time and cost and make the decision process toward efficient.

&n= bsp;

Yansen

Huawei Technologies Co., Ltd.

3D"Company_logo"

Cellphone =A3=BA= +86-13488809882
Email =A3=BA<= /span>yanshen@huawei.com


This e-mail and its attachments contain confidential information from HUAWE= I, which
is intended only for the person or entity whose address is listed above. An= y use of the
information contained herein in any way (including, but not limited to, tot= al or partial
disclosure, reproduction, or dissemination) by persons other than the inten= ded
recipient(s) is prohibited. If you receive this e-mail in error, please not= ify the sender by
phone or email immediately and delete it!

&n= bsp;

=B7=A2=BC=FE=C8=CB:<= /span> IDNET [mailto:idnet-bounces@ietf.org] =B4=FA=B1=ED Ing-Jyh Tsang<= br> =B7=A2=CB=CD=CA=B1=BC=E4: 2017=C4=EA5=D4=C210=C8=D5 14:24
=CA=D5=BC=FE=C8=CB: Sheng Jiang <jiangsheng@huawei.com>; idnet@ietf.org
=D6=F7=CC=E2: Re: [Idnet] Benefits of Introducing AI into Network

 

Is it possible to give a brief (or detail) d= escription of each o the topic?

On 10/05/2017 04:53, Sheng Jian= g wrote:

In ETSI NGP ISP, we have an Wor= k Item for IDN (Intelligence-Defined Network). In one of the general sectio= ns, We briefly describes the benefits of introducing AI into network, as be= low.

 

-=    &n= bsp;      Towards Fully Autonomic= Network

-=    &n= bsp;      Ability of Handling Com= plex Issues

-=    &n= bsp;      More Adaptive and Flex<= o:p>

-=    &n= bsp;      Predictive

-=    &n= bsp;      Potential Self-Evolving= Ability

-=    &n= bsp;      Potential Decision Effi= ciency

 

If there are major benefits tha= t we have not covered, we would like to include.

 

Regards,

 

Sheng




_______________________________________________
IDNET mailing list
IDNET@ietf.org<=
/a>
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h=x-gm-message-state:mime-version:in-reply-to:references:from:date :message-id:subject:to:cc; bh=WJ8FRp8maJtvhsPr7n1wferQM5JwhnMztMxBpHGGKhk=; b=KWGoucl7msZ+1kD3QQwTL4HRoShL7pgCC5/mMs77m8P8YdpmR0tv2uj5GZZUSFIZhB 7rLne6MC61qTpSClvpkUulndACxfiFXLiIcZ/3xbO6iOLeTrSEAo9lPP3e4XCh1yY2GM U32fmebe3ae6PlIs6XOnoZAyQSAQlYjUFtdO0Fkt9/Vi/9WVwtJfeBQlWD36U/RNp6Xt rnAtZwNZFiGXDqwO3DzUTVtMxFfq4abtPEAI50a8gmzy0MxkPSl+BnbsyWVs9ilLaweQ QgfTgKgOqG9d92Fr/y4YDpfYzx5x+J2tdxszN1d+wMCSKcDL5NkocG1zODU3xfOsNQKP AY2w== X-Gm-Message-State: AODbwcCssyyE2GvCtnzXaKWG4DL69DNn+t9Pe3faWawJk9PqQyrd9x2r LDHRr04fY5v/H7cip0jjE61ftTmHmA== X-Received: by 10.159.52.214 with SMTP id b22mr2568714uac.93.1494419661430; Wed, 10 May 2017 05:34:21 -0700 (PDT) MIME-Version: 1.0 Received: by 10.176.9.6 with HTTP; Wed, 10 May 2017 05:34:20 -0700 (PDT) X-Originating-IP: [64.134.240.2] In-Reply-To: <6AE399511121AB42A34ACEF7BF25B4D293636E@DGGEMM505-MBS.china.huawei.com> References: <5D36713D8A4E7348A7E10DF7437A4B927CD7DC87@NKGEML515-MBS.china.huawei.com> <05c9c525-eb0d-dc93-a654-c9bef27c520a@nokia-bell-labs.com> <6AE399511121AB42A34ACEF7BF25B4D293636E@DGGEMM505-MBS.china.huawei.com> From: David Meyer Date: Wed, 10 May 2017 05:34:20 -0700 Message-ID: To: yanshen Cc: Ing-Jyh Tsang , "idnet@ietf.org" Content-Type: multipart/related; boundary=f403045e797610f0ff054f2ab18e Archived-At: Subject: Re: [Idnet] =?utf-8?b?562U5aSNOiBCZW5lZml0cyBvZiBJbnRyb2R1Y2luZyBB?= =?utf-8?q?I_into_Network?= 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, 10 May 2017 12:34:26 -0000 --f403045e797610f0ff054f2ab18e Content-Type: multipart/alternative; boundary=f403045e797610f0fb054f2ab18d --f403045e797610f0fb054f2ab18d Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: quoted-printable Folks, I would encourage people to ask the question: How does actually work? where are claims being made about AI and what it might do. If we can't answer this basic question then we're off on the wrong foot. We need to understand the technical details of how different techniques work in order to be successful. This has been proven out time and time again in both the research community and in industry. More specifically, falling prey to the ML hype machine won't serve anyone's purposes. So when we make wish-lists about what ML might do for us, let's remember to ask the important questions, such as: what data sets to we have (and what are their properties), what assumptions are we making, what models are appropriate, and what are their computation properties (both in training and inference), to name a few. For example, in the case of something as simple as PCA (or if you like single hidden layer linear auto-encoder), we assume linearity, that mean and variance are sufficient statistics, that large variances have important structure, and that the principle components (rows of P) are orthogonal. All, some or none of these may be true for a given network data set. BTW, even the term AI is being used in inconsistent ways. For the most part it seems like people are talking about Machine Learning (weak or narrow AI) as opposed to something like AGI (strong AI). While the problems are related (weak vs. strong AI, an AGI might use ML techniques), they are in very different stages of development and have very different properties. It will serve us well to be precise about what we're talking about. Dave On Wed, May 10, 2017 at 5:04 AM, yanshen wrote: > Dear Ing-Jyh Tsang and all, > > > > There is some personal thought of these topics. Comments and suggestions > are most welcome! > > > > --Towards Fully Autonomic Network > > > > The advantage (or say aim) of a fully autonomic network is > implementing the close-ring of =E2=80=9CSensing-Analysis-Decision=E2=80= =9D, which will > minimize the input of manual labor in the pure operating actions (without > analysis). In current, the process of sensing, analysis and decision are > independent to each other and the cooperation of these is depend on manua= l > work. The shortage is caused by the lack of analysis ability of network, > which is exactly AI technology is good at. > > > > --Ability of Handling Complex Issues > > > > The machine learning (ML) method is one of the best way to solve > the complex problems, such as classifying problems and optimal decision > problems. In network area, the problems that related to resource manageme= nt > and route decision are typically complex. The introducing of AI method > essentially build up a centralized analysis system which may provide a > global view solution for the network, which cannot (or difficult) be > implemented with the current highly distributed architecture. A centraliz= ed > architecture may not solve all problems but it is indeed a good supplemen= t > for nowadays network. > > > > --More Adaptive and Flex > > > > The ML model can output different policies according to the input > training data. Each domain of network may own different characters (e.g. > different traffic character). It is possible to provide adaptive solution > for different situation via uniform train model. > > > > --Predictive > > > > Prediction is one of the most important attribute that AI > technology brings. On one hand, the prediction (e.g. traffic prediction o= r > failure prediction) that produced by AI algorithm can make the network > manager preventing the risky failure and nip the problem in the bud. It > will reduce the risk of network fault so that the cost of recovering from > the failure. On the other hand, the prediction can be also used to evalua= te > the reliability of network policy. For example, to evaluate what is the > probability of a VPN route is faced with congestion. > > > > --Potential Self-Evolving Ability > > > > The ML method is self-evolving, which may provide same attribute > to network. According to training the network decision model continuously= , > the network can match the change of service and traffic. Actually, the > optimization is just the process that modifying the network parameters to > match the requirement. The self-evolving feature of ML method may bring t= he > same ability to the network. > > > > --Potential Decision Efficiency > > > > The machine learning algorithm can solve the decision problems > which has been verified in other area (e.g. AlphaGo). It will be valuable > to train a decision model of network that input the current state and > output corresponding policies (e.g. device configuration parameters). Thi= s > model may configure the network device directly when necessary or provide > probable configurations as choices when doubt. Both of them will save the > time and cost and make the decision process toward efficient. > > > > Yansen > > Huawei Technologies Co., Ltd. > > [image: Company_logo] > > Cellphone =EF=BC=9A+86-13488809882 <+86%20134%208880%209882> > Email =EF=BC=9Ayanshen@huawei.com > ------------------------------ > > > This e-mail and its attachments contain confidential information from > HUAWEI, which > is intended only for the person or entity whose address is listed above. > Any use of the > information contained herein in any way (including, but not limited to, > total or partial > disclosure, reproduction, or dissemination) by persons other than the > intended > recipient(s) is prohibited. If you receive this e-mail in error, please > notify the sender by > phone or email immediately and delete it! > > > > *=E5=8F=91=E4=BB=B6=E4=BA=BA:* IDNET [mailto:idnet-bounces@ietf.org] *=E4= =BB=A3=E8=A1=A8 *Ing-Jyh Tsang > *=E5=8F=91=E9=80=81=E6=97=B6=E9=97=B4:* 2017=E5=B9=B45=E6=9C=8810=E6=97= =A5 14:24 > *=E6=94=B6=E4=BB=B6=E4=BA=BA:* Sheng Jiang ; idnet= @ietf.org > *=E4=B8=BB=E9=A2=98:* Re: [Idnet] Benefits of Introducing AI into Network > > > > Is it possible to give a brief (or detail) description of each o the > topic? > > On 10/05/2017 04:53, Sheng Jiang wrote: > > In ETSI NGP ISP, we have an Work Item for IDN (Intelligence-Defined > Network). In one of the general sections, We briefly describes the benefi= ts > of introducing AI into network, as below. > > > > - Towards Fully Autonomic Network > > - Ability of Handling Complex Issues > > - More Adaptive and Flex > > - Predictive > > - Potential Self-Evolving Ability > > - Potential Decision Efficiency > > > > If there are major benefits that we have not covered, we would like to > include. > > > > Regards, > > > > Sheng > > > > > _______________________________________________ > > 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 > > --f403045e797610f0fb054f2ab18d Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable
Folks,=C2=A0

I would encourage people t= o ask the question: How does <this> actually work?=C2=A0
where <this> are claims being made about AI and what it = might do. If we can't answer this basic question then we're off on = the wrong foot. We need to understand the technical details of how differen= t techniques work in order to be successful. This has been proven out time = and time again in both the research community and in industry.=C2=A0 More s= pecifically, falling prey to the ML hype machine won't serve anyone'= ;s purposes. =C2=A0

So when we make wish-lists abo= ut what ML might do for us, let's remember to ask the important questio= ns, such as: what data sets to we have (and what are their properties), wha= t assumptions are we making, what models are appropriate, and what are thei= r computation properties (both in training and inference), to name a few. F= or example, in the case of something as simple as PCA (or if you like singl= e hidden layer linear auto-encoder), we assume linearity, that mean and var= iance are sufficient statistics, that large variances have important struct= ure, and that the principle components (rows of P) are orthogonal. All, som= e or none of these may be true for a given network data set.

=
BTW, even the term AI is being used in inconsistent ways. For th= e most part it seems like people are talking about Machine Learning (weak o= r narrow AI) as opposed to something like AGI (strong AI). While the proble= ms are related (weak vs. strong AI, an AGI might use ML techniques), they a= re in very different stages of development and have very different properti= es.=C2=A0

It will serve us well to be precise abou= t what we're talking about.

Dave

On Wed, Ma= y 10, 2017 at 5:04 AM, yanshen <yanshen@huawei.com> wrote:<= br>

= Dear Ing-Jyh Tsang and all,

= =C2=A0

= There is some personal thought of these topics. Comments and suggestions ar= e most welcome!

= =C2=A0

= --Towards Fully Autonomic Network

= =C2=A0

= =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 The advantage (or say aim) of a = fully autonomic network is implementing the close-ring of =E2=80=9CSensing-= Analysis-Decision=E2=80=9D, which will minimize the input of manual labor i= n the pure operating actions (without analysis). In current, the process of sensing, analysis a= nd decision are independent to each other and the cooperation of these is d= epend on manual work. The shortage is caused by the lack of analysis abilit= y of network, which is exactly AI technology is good at.

= =C2=A0

= --Ability of Handling Complex Issues

= =C2=A0

= =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 The machine learning (ML) method= is one of the best way to solve the complex problems, such as classifying = problems and optimal decision problems. In network area, the problems that = related to resource management and route decision are typically complex. The intro= ducing of AI method essentially build up a centralized analysis system whic= h may provide a global view solution for the network, which cannot (or diff= icult) be implemented with the current highly distributed architecture. A centralized architecture may not solve = all problems but it is indeed a good supplement for nowadays network.

= =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0

= --More Adaptive and Flex

= =C2=A0

= =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 The ML model can output different poli= cies according to the input training data. Each domain of network may own d= ifferent characters (e.g. different traffic character). It is possible to p= rovide adaptive solution for different situation via uniform train model.<= u>

= =C2=A0

= --Predictive

= =C2=A0

= =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 Prediction is one of the most im= portant attribute that AI technology brings. On one hand, the prediction (e= .g. traffic prediction or failure prediction) that produced by AI algorithm= can make the network manager preventing the risky failure and nip the problem = in the bud. It will reduce the risk of network fault so that the cost of re= covering from the failure. On the other hand, the prediction can be also us= ed to evaluate the reliability of network policy. For example, to evaluate what is the probability of a VPN = route is faced with congestion.

= =C2=A0

= --Potential Self-Evolving Ability

= =C2=A0

= =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 The ML method is self-evolving, = which may provide same attribute to network. According to training the netw= ork decision model continuously, the network can match the change of servic= e and traffic. Actually, the optimization is just the process that modifying the= network parameters to match the requirement. The self-evolving feature of = ML method may bring the same ability to the network.

= =C2=A0

= --Potential Decision Efficiency

= =C2=A0

= =C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 The machine learning algorithm c= an solve the decision problems which has been verified in other area (e.g. = AlphaGo). It will be valuable to train a decision model of network that inp= ut the current state and output corresponding policies (e.g. device configuration= parameters). This model may configure the network device directly when nec= essary or provide probable configurations as choices when doubt. Both of th= em will save the time and cost and make the decision process toward efficient.

= =C2=A0

= Yansen

= Huawei Technologies Co., Ltd.

= 3D"Company_logo"

= Cellphone = =EF=BC=9A+86-13488809882
Email =EF=BC=9A<= a href=3D"mailto:yanshen@huawei.com" target=3D"_blank">yanshen@huawei.com


This e-mail and its attachments contain confidential information from HUAWE= I, which
is intended only for the person or entity whose address is listed above. An= y use of the
information contained herein in any way (including, but not limited to, tot= al or partial
disclosure, reproduction, or dissemination) by persons other than the inten= ded
recipient(s) is prohibited. If you receive this e-mail in error, please not= ify the sender by
phone or email immediately and delete it!

= =C2=A0

=E5=8F=91=E4=BB=B6=E4=BA=BA:<= /span> IDNET [mailto:= idnet-bounces@ietf.org] =E4=BB=A3=E8=A1=A8 Ing-Jyh Tsang =E5=8F=91=E9=80=81=E6=97=B6=E9= =97=B4: 2017=E5=B9=B4= 5=E6=9C=8810=E6=97= =A5 14:24
=E6=94=B6=E4=BB=B6=E4=BA=BA: Sheng Jiang <jiangsheng@huawei.com>; idnet@ietf.org
=E4=B8=BB=E9=A2=98: Re: [Idnet] Benefits of Introducing AI into Network

=C2=A0

Is it possible to give a brief (or detail) des= cription of each o the topic? <= /p>

On 10/05/2017 04:53, Sheng Jian= g wrote:

In ETSI NGP ISP, we have an Wor= k Item for IDN (Intelligence-Defined Network). In one of the general sectio= ns, We briefly describes the benefits of introducing AI into network, as be= low.

=C2=A0

-=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 Towards Fully Autonomic Ne= twork

-=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 Ability of Handling Comple= x Issues

-=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 More Adaptive and Flex<= /u>

-=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 Predictive

-=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 Potential Self-Evolving Ab= ility

-=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0=C2=A0 Potential Decision Efficie= ncy

=C2=A0

If there are major benefits tha= t we have not covered, we would like to include.

=C2=A0

Regards,

=C2=A0

Sheng




____________________________________________=
___
IDNET mailing list
IDNET@ietf.org
https://www.ietf.org/mailman/listinfo/idnet

=C2=A0


_______________________________________________
IDNET mailing list
IDNET@ietf.org
https://www.ietf.org/mailman/listinfo/idnet


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[111.69.230.173]) by smtp.gmail.com with ESMTPSA id b68sm232154pfa.127.2017.05.10.18.35.40 (version=TLS1_2 cipher=ECDHE-RSA-AES128-GCM-SHA256 bits=128/128); Wed, 10 May 2017 18:35:42 -0700 (PDT) To: "Fang, Luyuan" , Sheng Jiang , "idnet@ietf.org" References: From: Brian E Carpenter Organization: University of Auckland Message-ID: <3e15e008-f2ae-951d-7b2c-7ada800a075d@gmail.com> Date: Thu, 11 May 2017 13:35:47 +1200 User-Agent: Mozilla/5.0 (Windows NT 6.1; WOW64; rv:45.0) Gecko/20100101 Thunderbird/45.8.0 MIME-Version: 1.0 In-Reply-To: Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: quoted-printable Archived-At: Subject: Re: [Idnet] Benefits of Introducing AI into Network 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: Thu, 11 May 2017 01:35:46 -0000 On 10/05/2017 18:26, Fang, Luyuan wrote: > I think what is driving all these points is scale. Without intelligence= , very large scale networks simply become unmanageable,=20 I am not sure that statement is always true. It is safe to say that witho= ut *distributed solutions*, very large scale networks become unmanageable= , and AI technologies can be used to support distributed solutions. Let's take a specific example: the CASM work in the IETF. One approach to= massive scale support of address and prefix management is a massive cent= ralised database and an old-fashioned (NETCONF/YANG style) mechanism to p= ush allocations out into the network. Another approach is a large set of = distributed autonomic prefix managers that request new space from a distr= ibuted address pool when necessary. The second one is definitely a target= for machine learning, in order to set optimal parameters for the individ= ual prefix managers. > and cannot maintain service availability. Just adding work force would = not help. It will help where the problem can genuinely be tackled by "divide and co= nquer", for example where localised optimisation and localised repair can= help. But when localised solutions are inadequate and traditional centra= lised solutions do not scale, AI can be the answer. > I would suggest to add >=20 > - ability to manage network at scale (as 2nd point) >=20 > - potential self-healing (after =E2=80=9Cpredictive=E2=80=9D) Agreed. Brian >=20 > Thx, > Luyuan >=20 > From: IDNET on behalf of Sheng Jiang > Date: Tuesday, May 9, 2017 at 7:53 PM > To: "idnet@ietf.org" > Subject: [Idnet] Benefits of Introducing AI into Network >=20 > In ETSI NGP ISP, we have an Work Item for IDN (Intelligence-Defined Net= work). In one of the general sections, We briefly describes the benefits = of introducing AI into network, as below. >=20 >=20 > - Towards Fully Autonomic Network >=20 > - Ability of Handling Complex Issues >=20 > - More Adaptive and Flex >=20 > - Predictive >=20 > - Potential Self-Evolving Ability >=20 > - Potential Decision Efficiency >=20 > If there are major benefits that we have not covered, we would like to = include. >=20 > Regards, >=20 > Sheng >=20 >=20 >=20 > _______________________________________________ > IDNET mailing list > IDNET@ietf.org > https://www.ietf.org/mailman/listinfo/idnet >=20 From nobody Wed May 10 18:38:21 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 4CD6F12EB06 for ; Wed, 10 May 2017 18:38:19 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -2.011 X-Spam-Level: X-Spam-Status: No, score=-2.011 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Delivered-To: idnet@ietfa.amsl.com Received: from localhost (localhost [127.0.0.1]) by ietfa.amsl.com (Postfix) with ESMTP id 797C91293F3 for ; Wed, 10 May 2017 19:12:01 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -0.003 X-Spam-Level: X-Spam-Status: No, score=-0.003 tagged_above=-999 required=5 tests=[BAYES_20=-0.001, RP_MATCHES_RCVD=-0.001, 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 QFg92p0WCMjd for ; Wed, 10 May 2017 19:11:59 -0700 (PDT) Received: from ns2.nict.go.jp (ns2.nict.go.jp [IPv6:2001:df0:232:300::2]) by ietfa.amsl.com (Postfix) with ESMTP id 3DED0126E01 for ; Wed, 10 May 2017 19:11:59 -0700 (PDT) Received: from gw2.nict.go.jp (gw2.nict.go.jp [133.243.18.251]) by ns2.nict.go.jp with ESMTP id v4B2BpOe094504; Thu, 11 May 2017 11:11:51 +0900 (JST) Received: from mail2.nict.go.jp (mail2.nict.go.jp [133.243.18.15]) by gw2.nict.go.jp with ESMTP id v4B2BpYA094499; Thu, 11 May 2017 11:11:51 +0900 (JST) Received: from spectre (unknown [133.243.29.97]) (using TLSv1.2 with cipher DHE-RSA-AES256-GCM-SHA384 (256/256 bits)) (No client certificate requested) by mail2.nict.go.jp (NICT Mail Spool Server2) with ESMTPS id 34FA9AAD4; Thu, 11 May 2017 11:11:51 +0900 (JST) Date: Thu, 11 May 2017 11:11:56 +0900 From: Pedro Martinez-Julia To: Brian E Carpenter Cc: "Fang, Luyuan" , Sheng Jiang , "idnet@ietf.org" Message-ID: <20170511021155.GZ11096@spectre> References: <3e15e008-f2ae-951d-7b2c-7ada800a075d@gmail.com> MIME-Version: 1.0 Content-Type: text/plain; charset=utf-8 Content-Disposition: inline In-Reply-To: <3e15e008-f2ae-951d-7b2c-7ada800a075d@gmail.com> User-Agent: Mutt/1.8.0 (2017-02-23) X-Virus-Scanned: clamav-milter 0.98.7 at zenith2 X-Virus-Status: Clean Archived-At: Subject: Re: [Idnet] Benefits of Introducing AI into Network 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: Thu, 11 May 2017 02:12:01 -0000 On Thu, May 11, 2017 at 01:35:47PM +1200, Brian E Carpenter wrote: > On 10/05/2017 18:26, Fang, Luyuan wrote: > > I think what is driving all these points is scale. Without > > intelligence, very large scale networks simply become unmanageable, > > I am not sure that statement is always true. It is safe to say that > without *distributed solutions*, very large scale networks become > unmanageable, and AI technologies can be used to support distributed > solutions. Distributed solutions are required when the "large scale" is about the number of elements forming a network. However, they are required but not enough for dealing with a "large scale" of heterogeneity and complexity in scenarios. For example: - AI not required: Increase the bandwidth of all links by 10%. - AI required: Increase the bandwidth of all links to meet the possible demands they can have in the near future according to the behavior of the elements they are connected to. I think that with these simple statements we can justify the need for AI methods in networking but, please, let me know your comments. Thank you very much. Regards, Pedro -- Pedro Martinez-Julia Network Science and Convergence Device Technology Laboratory Network System Research Institute National Institute of Information and Communications Technology (NICT) 4-2-1, Nukui-Kitamachi, Koganei, Tokyo 184-8795, Japan Email: pedro@nict.go.jp --------------------------------------------------------- *** Entia non sunt multiplicanda praeter necessitatem *** From nobody Wed May 10 19:25:07 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 7A8A712EB1D for ; Wed, 10 May 2017 19:25:06 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -2 X-Spam-Level: X-Spam-Status: No, score=-2 tagged_above=-999 required=5 tests=[BAYES_00=-1.9, DKIM_SIGNED=0.1, DKIM_VALID=-0.1, DKIM_VALID_AU=-0.1, FREEMAIL_FROM=0.001, RCVD_IN_DNSWL_NONE=-0.0001, SPF_PASS=-0.001] autolearn=ham autolearn_force=no Authentication-Results: ietfa.amsl.com (amavisd-new); dkim=pass (2048-bit key) header.d=gmail.com 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 Njn_dB6c_EOP for ; Wed, 10 May 2017 19:25:05 -0700 (PDT) Received: from mail-pg0-x242.google.com (mail-pg0-x242.google.com [IPv6:2607:f8b0:400e:c05::242]) (using TLSv1.2 with cipher ECDHE-RSA-AES128-GCM-SHA256 (128/128 bits)) (No client certificate requested) by ietfa.amsl.com (Postfix) with ESMTPS id 15F12129BF2 for ; Wed, 10 May 2017 19:25:04 -0700 (PDT) Received: by mail-pg0-x242.google.com with SMTP id u187so1650224pgb.1 for ; Wed, 10 May 2017 19:25:04 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=gmail.com; s=20161025; h=subject:to:references:cc:from:organization:message-id:date :user-agent:mime-version:in-reply-to:content-transfer-encoding; bh=gyronAp2JkEYYO7o8QZCRYEi0W54vZJ2FXXyeBFjoi4=; b=e/HmeYBBfWkm1ewVPFfTxqeSo6Lwuluj6bNRLQAtWGTuVtecvT+SshFNhqJPzSNP+R ZtX/+LemexzFkgVzybcwRt7EjHXRIZCx7AT6qkSFbj0m4xU0v5RSAXjtvU8zz/QOWNRc GDEeFPowPw2fpRWphNWjT8BVIrhAqA2WwGM6kGAu+M2yDFTbEJBwPOGmPOBN7vrRnx27 3bV9zjMdHTKYQLu3jTluKh/KBAcQdINi166MPDt777p2TSoTlEGbVc0gd41IO3pEPtuC cQ8a56z98yWI6+l6sGCTzJHsQKekMh4NfE9yF5qQrUMccUX6j5HS8dcf55+FrNmmOl0X 0NiQ== X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=1e100.net; s=20161025; h=x-gm-message-state:subject:to:references:cc:from:organization :message-id:date:user-agent:mime-version:in-reply-to :content-transfer-encoding; bh=gyronAp2JkEYYO7o8QZCRYEi0W54vZJ2FXXyeBFjoi4=; b=b60E4rG2cyyYygFwu1YmU3SsGgcDtUbE0LLVazsp3a6wECFL9J9l2vNPpaLHuHlHXO KhvJFw2FP91OpopI0QGKKeWVzjIVqlpTkJo26jf9QyNXR9qfKdXlwQXH6OjCL06ZAWuv tw8aB5Ukc4ezUL3vRoyG+zlxjbKN62GpWw1Qrit/onFarHaIfNmgVB3j/7eRZq9ILAOS +7XbEQQ3JDFE3icsFJFG/N+uoco6fpUQSsSrhsDfQjASIyH1KXZUF0011MYyhcgeRMCM +KfClBe825KJkfcVWRnguZr1fBoEpAYY26vXpzy38TLgNXNe2YMDZlJELcbp0dTAnrZk OCIA== X-Gm-Message-State: AODbwcCdEAQ8HcVRwwN/HTn6gFgUYGHsURBEb+HKUrIhyhe+lJhcrawq TFD+HwmRU4Wqog== X-Received: by 10.84.233.131 with SMTP id l3mr12462246plk.18.1494469504482; Wed, 10 May 2017 19:25:04 -0700 (PDT) Received: from [192.168.178.21] (173.230.69.111.dynamic.snap.net.nz. [111.69.230.173]) by smtp.gmail.com with ESMTPSA id o29sm365051pgc.27.2017.05.10.19.25.01 (version=TLS1_2 cipher=ECDHE-RSA-AES128-GCM-SHA256 bits=128/128); Wed, 10 May 2017 19:25:03 -0700 (PDT) To: Pedro Martinez-Julia References: <3e15e008-f2ae-951d-7b2c-7ada800a075d@gmail.com> <20170511021155.GZ11096@spectre> Cc: "Fang, Luyuan" , Sheng Jiang , "idnet@ietf.org" From: Brian E Carpenter Organization: University of Auckland Message-ID: <7ff97e2b-60a3-12a0-88c7-6fa8fbedda04@gmail.com> Date: Thu, 11 May 2017 14:25:08 +1200 User-Agent: Mozilla/5.0 (Windows NT 6.1; WOW64; rv:45.0) Gecko/20100101 Thunderbird/45.8.0 MIME-Version: 1.0 In-Reply-To: <20170511021155.GZ11096@spectre> Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: 7bit Archived-At: Subject: Re: [Idnet] Benefits of Introducing AI into Network 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: Thu, 11 May 2017 02:25:06 -0000 On 11/05/2017 14:11, Pedro Martinez-Julia wrote: > On Thu, May 11, 2017 at 01:35:47PM +1200, Brian E Carpenter wrote: >> On 10/05/2017 18:26, Fang, Luyuan wrote: >>> I think what is driving all these points is scale. Without >>> intelligence, very large scale networks simply become unmanageable, >> >> I am not sure that statement is always true. It is safe to say that >> without *distributed solutions*, very large scale networks become >> unmanageable, and AI technologies can be used to support distributed >> solutions. > > Distributed solutions are required when the "large scale" is about the > number of elements forming a network. However, they are required but not > enough for dealing with a "large scale" of heterogeneity and complexity > in scenarios. > > For example: > - AI not required: Increase the bandwidth of all links by 10%. > - AI required: Increase the bandwidth of all links to meet the possible > demands they can have in the near future according to the behavior of > the elements they are connected to. I can agree with that in the general case, but in some cases a fairly simple predictive algorithm could be used that scarcely deserves the title of AI. It depends very much on the individual use case. > I think that with these simple statements we can justify the need for AI > methods in networking I definitely agree. We just have to be careful not to "sell" AI for cases where it is too much. Regards Brian > but, please, let me know your comments. Thank you > very much. > > Regards, > Pedro > From nobody Wed May 10 20:49:02 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 064A212EAC2 for ; Wed, 10 May 2017 20:48:59 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -4.221 X-Spam-Level: X-Spam-Status: No, score=-4.221 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, RP_MATCHES_RCVD=-0.001, 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 7SLW8v2KRABD for ; Wed, 10 May 2017 20:48:57 -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 471B9129C6F for ; Wed, 10 May 2017 20:48:56 -0700 (PDT) Received: from 172.18.7.190 (EHLO LHREML712-CAH.china.huawei.com) ([172.18.7.190]) by lhrrg02-dlp.huawei.com (MOS 4.3.7-GA FastPath queued) with ESMTP id DGJ50163; Thu, 11 May 2017 03:48:54 +0000 (GMT) Received: from DGGEMM406-HUB.china.huawei.com (10.3.20.214) by LHREML712-CAH.china.huawei.com (10.201.108.35) with Microsoft SMTP Server (TLS) id 14.3.301.0; Thu, 11 May 2017 04:48:52 +0100 Received: from DGGEMM505-MBX.china.huawei.com ([169.254.1.35]) by DGGEMM406-HUB.china.huawei.com ([10.3.20.214]) with mapi id 14.03.0301.000; Thu, 11 May 2017 11:48:43 +0800 From: yanshen To: "Fang, Luyuan" CC: Sheng Jiang , "idnet@ietf.org" Thread-Topic: [Idnet] Benefits of Introducing AI into Network Thread-Index: AQHSyVZaTGXqFLUbRgO5S4jI02SJ/qHueUow Date: Thu, 11 May 2017 03:48:43 +0000 Message-ID: <6AE399511121AB42A34ACEF7BF25B4D293C19C@DGGEMM505-MBX.china.huawei.com> References: In-Reply-To: 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[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 B99F11294B5 for ; Wed, 10 May 2017 23:54:03 -0700 (PDT) Received: from 172.18.7.190 (EHLO LHREML714-CAH.china.huawei.com) ([172.18.7.190]) by lhrrg02-dlp.huawei.com (MOS 4.3.7-GA FastPath queued) with ESMTP id DGJ70029; Thu, 11 May 2017 06:54:02 +0000 (GMT) Received: from NKGEML412-HUB.china.huawei.com (10.98.56.73) by LHREML714-CAH.china.huawei.com (10.201.108.37) with Microsoft SMTP Server (TLS) id 14.3.301.0; Thu, 11 May 2017 07:54:01 +0100 Received: from DGGEMM405-HUB.china.huawei.com (10.3.20.213) by nkgeml412-hub.china.huawei.com (10.98.56.73) with Microsoft SMTP Server (TLS) id 14.3.235.1; Thu, 11 May 2017 14:53:58 +0800 Received: from DGGEMM505-MBX.china.huawei.com ([169.254.1.35]) by DGGEMM405-HUB.china.huawei.com ([10.3.20.213]) with mapi id 14.03.0301.000; Thu, 11 May 2017 14:53:50 +0800 From: yanshen To: Pedro Martinez-Julia CC: "idnet@ietf.org" , Sheng Jiang Thread-Topic: [Idnet] Benefits of Introducing AI into Network Thread-Index: AQHSyVZaTGXqFLUbRgO5S4jI02SJ/qHt1QqAgAAKGgCAANNzoA== Date: Thu, 11 May 2017 06:53:50 +0000 Message-ID: <6AE399511121AB42A34ACEF7BF25B4D293C219@DGGEMM505-MBX.china.huawei.com> References: <3e15e008-f2ae-951d-7b2c-7ada800a075d@gmail.com> <20170511021155.GZ11096@spectre> In-Reply-To: <20170511021155.GZ11096@spectre> 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: text/plain; charset="us-ascii" Content-Transfer-Encoding: quoted-printable MIME-Version: 1.0 X-CFilter-Loop: Reflected X-Mirapoint-Virus-RAPID-Raw: score=unknown(0), refid=str=0001.0A020206.59140A8A.00A8, ss=1, re=0.000, recu=0.000, reip=0.000, cl=1, cld=1, fgs=0, ip=169.254.1.35, so=2013-06-18 04:22:30, dmn=2013-03-21 17:37:32 X-Mirapoint-Loop-Id: b6b6514d592b04631bc055932ff6d770 Archived-At: Subject: Re: [Idnet] Benefits of Introducing AI into Network 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: Thu, 11 May 2017 06:54:07 -0000 > -----Original Message----- > From: IDNET [mailto:idnet-bounces@ietf.org] On Behalf Of Pedro Martinez-J= ulia > Sent: Thursday, May 11, 2017 10:12 AM > To: Brian E Carpenter > Cc: Fang, Luyuan ; idnet@ietf.org; Sheng Jiang > > Subject: Re: [Idnet] Benefits of Introducing AI into Network >=20 > On Thu, May 11, 2017 at 01:35:47PM +1200, Brian E Carpenter wrote: > > On 10/05/2017 18:26, Fang, Luyuan wrote: > > > I think what is driving all these points is scale. Without > > > intelligence, very large scale networks simply become unmanageable, > > > > I am not sure that statement is always true. It is safe to say that > > without *distributed solutions*, very large scale networks become > > unmanageable, and AI technologies can be used to support distributed > > solutions. >=20 > Distributed solutions are required when the "large scale" is about the nu= mber of > elements forming a network. However, they are required but not enough for > dealing with a "large scale" of heterogeneity and complexity in scenarios= . >=20 > For example: > - AI not required: Increase the bandwidth of all links by 10%. > - AI required: Increase the bandwidth of all links to meet the possible > demands they can have in the near future according to the behavior of > the elements they are connected to. >=20 Agreed with your "AI required". The AI cannot create new resource but it is= really good at dealing with complex problems (e.g. resource allocation). > I think that with these simple statements we can justify the need for AI = methods > in networking but, please, let me know your comments. Thank you very much= . >=20 > Regards, > Pedro >=20 > -- > Pedro Martinez-Julia > Network Science and Convergence Device Technology Laboratory Network > System Research Institute National Institute of Information and Communica= tions > Technology (NICT) 4-2-1, Nukui-Kitamachi, Koganei, Tokyo 184-8795, Japan > Email: pedro@nict.go.jp > --------------------------------------------------------- > *** Entia non sunt multiplicanda praeter necessitatem *** >=20 > _______________________________________________ > IDNET mailing list > IDNET@ietf.org > https://www.ietf.org/mailman/listinfo/idnet From nobody Thu May 11 02:06:13 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 3AED312EB8C for ; Thu, 11 May 2017 02:06:12 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -1.899 X-Spam-Level: X-Spam-Status: No, score=-1.899 tagged_above=-999 required=5 tests=[BAYES_00=-1.9, DKIM_SIGNED=0.1, DKIM_VALID=-0.1, HTML_MESSAGE=0.001, RCVD_IN_DNSWL_NONE=-0.0001] autolearn=ham autolearn_force=no Authentication-Results: ietfa.amsl.com (amavisd-new); dkim=pass (2048-bit key) header.d=1-4-5-net.20150623.gappssmtp.com 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 aMHuwfrOXZDu for ; Thu, 11 May 2017 02:06:10 -0700 (PDT) Received: from mail-ua0-x22a.google.com (mail-ua0-x22a.google.com [IPv6:2607:f8b0:400c:c08::22a]) (using TLSv1.2 with cipher ECDHE-RSA-AES128-GCM-SHA256 (128/128 bits)) (No client certificate requested) by ietfa.amsl.com (Postfix) with ESMTPS id 2558212EB86 for ; Thu, 11 May 2017 02:06:08 -0700 (PDT) Received: by mail-ua0-x22a.google.com with SMTP id e28so22840869uah.0 for ; Thu, 11 May 2017 02:06:08 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=1-4-5-net.20150623.gappssmtp.com; s=20150623; h=mime-version:in-reply-to:references:from:date:message-id:subject:to :cc; bh=WzzdutCc74cRVdEHQ5sAZdW1lM4Q0R1TOuVCBhQzadQ=; b=tsHcAKBL3tWleC4g30fOXuFPqkkBlZ6Zap8gXZ722m6jgC25++V13TKO98AtiHbth4 tgzEg6NaE12EIMhJl653AUoJDOADtvUSE3ZC/YNEoZfmnjnQvWUyYjnPyWT+8dedf5+R mRx0aZhKjp7h6t0aI0XAx/5OGXkzQ3yjwtLaOKKhrdZ7zTOTFA0DwT+MsdproZa09/8k Nw7a8wU8LqUxKH70ASJx5Q7om3o80S20ZfwoCuDzSL4Mvu2LCl3RqcupO0vlTYN2j+Hr 49/PCxpMnHtEfGf7Mdrz1i/J0otqyfBgyQ1h0BPRW+E4AXKpixx5/nZF1J9nBq8QbcbW lYdQ== X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=1e100.net; s=20161025; h=x-gm-message-state:mime-version:in-reply-to:references:from:date :message-id:subject:to:cc; bh=WzzdutCc74cRVdEHQ5sAZdW1lM4Q0R1TOuVCBhQzadQ=; b=VYgYVHbcfoWNiOlKCmCku588bcJmtScgrY7WaFRRnJyu5JygO4ATbctDThiZnFsktG NObnvSfI8QOje/RW5DWAb/f/rqHHsD5sNp00cvTj4QBstNRD3RYTM+Aov+isVokL5ADA o9YPEnxYVseRi8GDETjbblAzUOSivRm8QBmNpTJzIzDLUHwcvro7jXDJsLIusY5fMqlV EFEZhVw9GKbs2m35WNmei1d6cCERr3zliWnT0dmyIMyshliqtlrT+0qIUE+tYFvZGNpx Z+3QEHkWBFny0BSGswV1/Wi+xcjc0ee9ZCnj7HdC5IRwiC9aSNDMN8oDsdJGrbJIx4Pa fggg== X-Gm-Message-State: AODbwcC4C/sUlF6V39+L9+2DHgEjIVlhfOG/lREvA8xGKE9vpQlp6QVP gijOtk6C47HiOLY0aHFqABYUQeiWOA== X-Received: by 10.176.24.93 with SMTP id j29mr5395931uag.141.1494493567165; Thu, 11 May 2017 02:06:07 -0700 (PDT) MIME-Version: 1.0 Received: by 10.176.9.6 with HTTP; Thu, 11 May 2017 02:06:06 -0700 (PDT) X-Originating-IP: [209.117.102.182] In-Reply-To: <3e15e008-f2ae-951d-7b2c-7ada800a075d@gmail.com> References: <3e15e008-f2ae-951d-7b2c-7ada800a075d@gmail.com> From: David Meyer Date: Thu, 11 May 2017 05:06:06 -0400 Message-ID: To: Brian E Carpenter Cc: "Fang, Luyuan" , Sheng Jiang , "idnet@ietf.org" Content-Type: multipart/alternative; boundary=f403043c437430bb9d054f3be667 Archived-At: Subject: Re: [Idnet] Benefits of Introducing AI into Network 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: Thu, 11 May 2017 09:06:12 -0000 --f403043c437430bb9d054f3be667 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: quoted-printable Brian, On Wed, May 10, 2017 at 9:35 PM, Brian E Carpenter < brian.e.carpenter@gmail.com> wrote: > On 10/05/2017 18:26, Fang, Luyuan wrote: > > I think what is driving all these points is scale. Without intelligence= , > very large scale networks simply become unmanageable, > I am not sure that statement is always true. It is safe to say that > without *distributed solutions*, very large scale networks become > unmanageable, and AI technologies can be used to support distributed > solutions. > Can you support this assertion? Further, what is an "AI technology", and which ways can "AI technologies can be used to support distributed solutions."? > > Let's take a specific example: the CASM work in the IETF. One approach to > massive scale support of address and prefix management is a massive > centralised database and an old-fashioned (NETCONF/YANG style) mechanism = to > push allocations out into the network. Another approach is a large set of > distributed autonomic prefix managers that request new space from a > distributed address pool when necessary. The second one is definitely a > target for machine learning, in order to set optimal parameters for the > individual prefix managers. > Phrases like "massive scale" don't seem to convey anything quantitative (or even qualitative, for that matter) about the problem space, and as such don't appear to be that useful (unless of course you can meaningfully quantify what is meant by "massive scale"). In addition, what kinds of machine learning would be applicable to the case of distributed autonomic prefix managers that you describe above (simply stating that it is so isn't that helpful)? For example, how would learning work, e.g., what kinds of models and related hyper-parameters do you envision being appropriate, and what kinds of data sets would be needed to efficiently train these models? In addition, how would inference work, where inference here means whatever you do with the trained model, including inference (computing the posterior), prediction (MAP or MLE), regression, ...? > > > and cannot maintain service availability. Just adding work force would > not help. > > It will help where the problem can genuinely be tackled by "divide and > conquer", for example where localised optimisation and localised repair c= an > help. But when localised solutions are inadequate and traditional > centralised solutions do not scale, AI can be the answer. > What is AI in this context? In addition, why can AI (whatever that is) be the answer to localized or centralized solutions that don't scale? Again, simply stating that it is so doesn't really help. Thanks, Dave > > I would suggest to add > > > > - ability to manage network at scale (as 2nd point) > > > > - potential self-healing (after =E2=80=9Cpredictive=E2=80=9D) > > Agreed. > > Brian > > > > Thx, > > Luyuan > > > > From: IDNET on behalf of Sheng Jiang < > jiangsheng@huawei.com> > > Date: Tuesday, May 9, 2017 at 7:53 PM > > To: "idnet@ietf.org" > > Subject: [Idnet] Benefits of Introducing AI into Network > > > > In ETSI NGP ISP, we have an Work Item for IDN (Intelligence-Defined > Network). In one of the general sections, We briefly describes the benefi= ts > of introducing AI into network, as below. > > > > > > - Towards Fully Autonomic Network > > > > - Ability of Handling Complex Issues > > > > - More Adaptive and Flex > > > > - Predictive > > > > - Potential Self-Evolving Ability > > > > - Potential Decision Efficiency > > > > If there are major benefits that we have not covered, we would like to > include. > > > > Regards, > > > > Sheng > > > > > > > > _______________________________________________ > > 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 > --f403043c437430bb9d054f3be667 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable

Brian,

<= br>
On Wed, May 10, 2017 at 9:35 PM, Brian E Carp= enter <brian.e.carpenter@gmail.com> wrote:
On 10/= 05/2017 18:26, Fang, Luyuan wrote:
> I think what is driving all these points is scale. Without intelligenc= e, very large scale networks simply become unmanageable,

I am not sure that statement is always true. It is safe to say that = without *distributed solutions*, very large scale networks become unmanagea= ble, and AI technologies can be used to support distributed solutions.
<= /blockquote>

Can you support this assertion? Further, wh= at is an "AI technology", and which ways can "AI technologie= s can be used to support distributed solutions."?
=C2=A0

Let's take a specific example: the CASM work in the IETF. One approach = to massive scale support of address and prefix management is a massive cent= ralised database and an old-fashioned (NETCONF/YANG style) mechanism to pus= h allocations out into the network. Another approach is a large set of dist= ributed autonomic prefix managers that request new space from a distributed= address pool when necessary. The second one is definitely a target for mac= hine learning, in order to set optimal parameters for the individual prefix= managers.

Phrases like "massive s= cale" don't seem to convey anything quantitative (or even qualitat= ive, for that matter) about the problem space, and as such don't appear= to be that useful (unless of course you can meaningfully quantify what is = meant by "massive scale"). In addition, what kinds of machine lea= rning would be applicable to the case of distributed autonomic prefix manag= ers that you describe above (simply stating that it is so isn't that he= lpful)? For example, how would learning work, e.g., what kinds of models an= d related hyper-parameters do you envision being appropriate, and what kind= s of data sets would be needed to efficiently train these models? In additi= on, how would inference work, where inference here means whatever you do wi= th the trained model, including inference (computing the posterior), predic= tion (MAP or MLE), regression, ...?

> and cannot maintain service availability. Just adding work force would= not help.

It will help where the problem can genuinely be tackled by "div= ide and conquer", for example where localised optimisation and localis= ed repair can help. But when localised solutions are inadequate and traditi= onal centralised solutions do not scale, AI can be the answer.

What is AI in this context? In addition, why can AI= (whatever that is) be the answer to localized or centralized solutions tha= t don't scale?=C2=A0 Again, simply stating that it is so doesn't re= ally help.

Thanks,

Dave


> I would suggest to add
>
> -=C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 ability to manage network at scale= (as 2nd point)
>
> -=C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 potential self-healing (after =E2= =80=9Cpredictive=E2=80=9D)

Agreed.

=C2=A0 =C2=A0 Brian
>
> Thx,
> Luyuan
>
> From: IDNET <idnet-bounce= s@ietf.org> on behalf of Sheng Jiang <jiangsheng@huawei.com>
> Date: Tuesday, May 9, 2017 at 7:53 PM
> To: "idnet@ietf.org" &= lt;idnet@ietf.org>
> Subject: [Idnet] Benefits of Introducing AI into Network
>
> In ETSI NGP ISP, we have an Work Item for IDN (Intelligence-Defined Ne= twork). In one of the general sections, We briefly describes the benefits o= f introducing AI into network, as below.
>
>
> -=C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 Towards Fully Autonomic Network >
> -=C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 Ability of Handling Complex Issues=
>
> -=C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 More Adaptive and Flex
>
> -=C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 Predictive
>
> -=C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 Potential Self-Evolving Ability >
> -=C2=A0 =C2=A0 =C2=A0 =C2=A0 =C2=A0 Potential Decision Efficiency
>
> If there are major benefits that we have not covered, we would like to= include.
>
> Regards,
>
> Sheng
>
>
>
> ___________= ____________________________________
> 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

--f403043c437430bb9d054f3be667-- From nobody Thu May 11 13:35:50 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 E595312F24E for ; Thu, 11 May 2017 13:35:47 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -2 X-Spam-Level: X-Spam-Status: No, score=-2 tagged_above=-999 required=5 tests=[BAYES_00=-1.9, DKIM_SIGNED=0.1, DKIM_VALID=-0.1, DKIM_VALID_AU=-0.1, FREEMAIL_FROM=0.001, RCVD_IN_DNSWL_NONE=-0.0001, SPF_PASS=-0.001] autolearn=ham autolearn_force=no Authentication-Results: ietfa.amsl.com (amavisd-new); dkim=pass (2048-bit key) header.d=gmail.com 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 TBElwO83lGCr for ; Thu, 11 May 2017 13:35:45 -0700 (PDT) Received: from mail-pf0-x233.google.com (mail-pf0-x233.google.com [IPv6:2607:f8b0:400e:c00::233]) (using TLSv1.2 with cipher ECDHE-RSA-AES128-GCM-SHA256 (128/128 bits)) (No client certificate requested) by ietfa.amsl.com (Postfix) with ESMTPS id 7901F12E051 for ; Thu, 11 May 2017 13:30:17 -0700 (PDT) Received: by mail-pf0-x233.google.com with SMTP id e193so19149959pfh.0 for ; Thu, 11 May 2017 13:30:17 -0700 (PDT) DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=gmail.com; s=20161025; h=subject:to:references:cc:from:organization:message-id:date :user-agent:mime-version:in-reply-to:content-transfer-encoding; bh=MK2cjXa7R2a6c4WMRKfFWIEHxGbYyBUP78V0h3AmMNo=; b=PfxvVK592bAk2GLaKFiC2w7C1OrnHIbvctWX5TsjFiJ02ZChw0MqtAcJ00j/H0garR qKKqtm8gzpwAiqXgnpCe0LG2Ob6In7/q6YxRajnOn8uTt7dJAS71N6/SLMz+DbGn3gcP HVLaSyCLJz8wKWS/cwO201KI8umQJ6rRL7UscTtZpxIAtspZznRPbBUcZsPmmTh5tgrv fVbL9y6ErU9CdWRMqdUYxVd/WBCVT+BubHfYImIlq5e5kToxbL/hDQ1SOjFc4IRX+PEY X2gdHaAmt1m3M7yaq+5LsXZlPIgWTkTlvruyy3bxMoPTyv89gvBP66S4kzDFY1C38oFt ecqw== X-Google-DKIM-Signature: v=1; a=rsa-sha256; c=relaxed/relaxed; d=1e100.net; s=20161025; h=x-gm-message-state:subject:to:references:cc:from:organization :message-id:date:user-agent:mime-version:in-reply-to :content-transfer-encoding; bh=MK2cjXa7R2a6c4WMRKfFWIEHxGbYyBUP78V0h3AmMNo=; b=JVSAKXr6C/zYG9zLGpvZLLNdINdHu42tHO08LcalZcnL6pS5BYuBLeSoa3g97KRj9X vDBUuTXe5Yq1ceA/DqNeycaLDSHH/ZfHeAd4n9FEe0werL7FtUlwpAo1APb8lYrr8pvm uyB2/vnxL3Bi8uhdxGl1jeBed2lm66oIKvHsSIh4GcDaAeCIVWWq0Z9YRLBUTZ00owH8 jiekm/mJPZo8TgIrz7dfp2LVD743YGpunlCCGMMGsU82NahiZNVDL/M3sX0tGMXtFPnV Lr1bEtU7sRQU5Njd6bac70G19MVQ9EUkrGDijMGsNaaJ3pEKevwGjczRJSWBTbPtxwJF G40A== X-Gm-Message-State: AODbwcATOn/1LJG7RDm93ixx1HHOzfCeTqTJ4OxPGQXMgQhGs4z9lh20 Pz//8oUO/TDdmA== X-Received: by 10.99.107.201 with SMTP id g192mr362553pgc.149.1494534617009; Thu, 11 May 2017 13:30:17 -0700 (PDT) Received: from [192.168.178.21] ([118.149.111.242]) by smtp.gmail.com with ESMTPSA id l7sm2141795pgn.10.2017.05.11.13.30.13 (version=TLS1_2 cipher=ECDHE-RSA-AES128-GCM-SHA256 bits=128/128); Thu, 11 May 2017 13:30:15 -0700 (PDT) To: David Meyer References: <3e15e008-f2ae-951d-7b2c-7ada800a075d@gmail.com> Cc: "Fang, Luyuan" , Sheng Jiang , "idnet@ietf.org" From: Brian E Carpenter Organization: University of Auckland Message-ID: <3acb4821-fa60-4771-1e04-b94ac5eab487@gmail.com> Date: Fri, 12 May 2017 08:30:22 +1200 User-Agent: Mozilla/5.0 (Windows NT 6.1; WOW64; rv:45.0) Gecko/20100101 Thunderbird/45.8.0 MIME-Version: 1.0 In-Reply-To: Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: quoted-printable Archived-At: Subject: Re: [Idnet] Benefits of Introducing AI into Network 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: Thu, 11 May 2017 20:35:48 -0000 On 11/05/2017 21:06, David Meyer wrote: > Brian, >=20 >=20 > On Wed, May 10, 2017 at 9:35 PM, Brian E Carpenter < > brian.e.carpenter@gmail.com> wrote: >=20 >> On 10/05/2017 18:26, Fang, Luyuan wrote: >>> I think what is driving all these points is scale. Without intelligen= ce, >> very large scale networks simply become unmanageable, >=20 >=20 >> I am not sure that statement is always true. It is safe to say that >> without *distributed solutions*, very large scale networks become >> unmanageable, and AI technologies can be used to support distributed >> solutions. >> >=20 > Can you support this assertion? Further, what is an "AI technology", I'm not brave enough to try to answer that in a few words. But clearly ML is an example. Some kind of inference engine is another. Also, specifi= c heuristic algorithms seem very suitable for use in systems of distributed= agents, because each agent needs to respond to local conditions. > and > which ways can "AI technologies can be used to support distributed > solutions."? Either by installing heuristics in individual agents, or by allowing agents to consult a central oracle when they need help ("AI as a service"= if you like). But there's a lot to work out. =20 >> >> Let's take a specific example: the CASM work in the IETF. One approach= to >> massive scale support of address and prefix management is a massive >> centralised database and an old-fashioned (NETCONF/YANG style) mechani= sm to >> push allocations out into the network. Another approach is a large set= of >> distributed autonomic prefix managers that request new space from a >> distributed address pool when necessary. The second one is definitely = a >> target for machine learning, in order to set optimal parameters for th= e >> individual prefix managers. >> >=20 > Phrases like "massive scale" don't seem to convey anything quantitative= (or > even qualitative, for that matter) about the problem space, and as such= > don't appear to be that useful (unless of course you can meaningfully > quantify what is meant by "massive scale").=20 Well, in this case think of an ISP with tens of millions of subscribers, and work back from that to how many distributed agents might be involved.= For example, at least 1000 agents each handling address space delegation to 10000 subscribers. > In addition, what kinds of > machine learning would be applicable to the case of distributed autonom= ic > prefix managers that you describe above (simply stating that it is so i= sn't > that helpful)? For example, how would learning work, e.g., what kinds o= f > models and related hyper-parameters do you envision being appropriate, = and > what kinds of data sets would be needed to efficiently train these mode= ls? > In addition, how would inference work, where inference here means whate= ver > you do with the trained model, including inference (computing the > posterior), prediction (MAP or MLE), regression, ...? Dunno. These are good questions. =20 >> >>> and cannot maintain service availability. Just adding work force woul= d >> not help. >> >> It will help where the problem can genuinely be tackled by "divide and= >> conquer", for example where localised optimisation and localised repai= r can >> help. But when localised solutions are inadequate and traditional >> centralised solutions do not scale, AI can be the answer. >> >=20 > What is AI in this context? In addition, why can AI (whatever that is) = be > the answer to localized or centralized solutions that don't scale? Aga= in, > simply stating that it is so doesn't really help. Learning from experience is the key benefit, I think. That's why I imagin= e that the distributed agents could share a central ML oracle, which will build up knowledge over the long term. To invent a heuristic out of thin air: "An agent will experience a burst of address space requests at 19:00= in its local time zone. Therefore it should request extra space at 18:30.= " That seems like something that an ML/inference engine could produce from reports sent in by distributed agents. Regards Brian =20 > Thanks, >=20 > Dave >=20 >=20 >>> I would suggest to add >>> >>> - ability to manage network at scale (as 2nd point) >>> >>> - potential self-healing (after =E2=80=9Cpredictive=E2=80=9D= ) >> >> Agreed. >> >> Brian >>> >>> Thx, >>> Luyuan >>> >>> From: IDNET on behalf of Sheng Jiang < >> jiangsheng@huawei.com> >>> Date: Tuesday, May 9, 2017 at 7:53 PM >>> To: "idnet@ietf.org" >>> Subject: [Idnet] Benefits of Introducing AI into Network >>> >>> In ETSI NGP ISP, we have an Work Item for IDN (Intelligence-Defined >> Network). In one of the general sections, We briefly describes the ben= efits >> of introducing AI into network, as below. >>> >>> >>> - Towards Fully Autonomic Network >>> >>> - Ability of Handling Complex Issues >>> >>> - More Adaptive and Flex >>> >>> - Predictive >>> >>> - Potential Self-Evolving Ability >>> >>> - Potential Decision Efficiency >>> >>> If there are major benefits that we have not covered, we would like t= o >> include. >>> >>> Regards, >>> >>> Sheng >>> >>> >>> >>> _______________________________________________ >>> 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 >> >=20 From nobody Thu May 11 15:40:55 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 7E22112EC67 for ; 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X-Gm-Message-State: AODbwcAW7XU2KNNvcT86LAv+Cx5hUhGUZdr1Bu/vnvITgyUnTPHkxcvY fW44NLd6a61vMw== X-Received: by 10.99.109.129 with SMTP id i123mr1889770pgc.103.1494557937660; Thu, 11 May 2017 19:58:57 -0700 (PDT) Received: from [192.168.178.21] ([118.149.111.242]) by smtp.gmail.com with ESMTPSA id g5sm1905186pfe.34.2017.05.11.19.58.55 (version=TLS1_2 cipher=ECDHE-RSA-AES128-GCM-SHA256 bits=128/128); Thu, 11 May 2017 19:58:57 -0700 (PDT) To: Javier Antich Romaguera , "Fang, Luyuan" , Sheng Jiang , "idnet@ietf.org" References: <3e15e008-f2ae-951d-7b2c-7ada800a075d@gmail.com> <7D1D8481-335B-4F91-B96D-A50B1F75ECA4@juniper.net> From: Brian E Carpenter Organization: University of Auckland Message-ID: <6f7d1c50-a10f-7c8a-f084-7c8b1f543bbb@gmail.com> Date: Fri, 12 May 2017 14:59:04 +1200 User-Agent: Mozilla/5.0 (Windows NT 6.1; WOW64; rv:45.0) Gecko/20100101 Thunderbird/45.8.0 MIME-Version: 1.0 In-Reply-To: <7D1D8481-335B-4F91-B96D-A50B1F75ECA4@juniper.net> Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: quoted-printable Archived-At: Subject: Re: [Idnet] Benefits of Introducing AI into Network 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: Fri, 12 May 2017 03:04:13 -0000 Hi, On 12/05/2017 10:35, Javier Antich Romaguera wrote: >>> Let's take a specific example: the CASM work in the IETF. One approac= h to massive scale support of address and prefix management is a massive = centralised database and an old-fashioned (NETCONF/YANG style) mechanism = to push allocations out into the network. Another approach is a large set= of distributed autonomic prefix managers that request new space from a d= istributed address pool when necessary. The second one is definitely a ta= rget for machine learning, in order to set optimal parameters for the ind= ividual prefix managers. >=20 > I=C2=B4m sorry, but what is the relationship between something being ce= ntralized or distributed and using or not a mechanism like Netconf using = YANG models to communicate certain information (in this case prefixes or = addresses)? They are entirely orthogonal.=20 I don't believe they are orthogonal when you consider scaling and resilie= nce simultaneously. Of course the actual delivery of parameters to end systems can be perform= ed using the same tools like NETCONF (or RADIUS, or DHCPv6/PD) whether or not it's centrali= sed. However, at large scale, if the network partitions, you will not get resiliency from = a centralised scheme. > Wherever you do your processing (centralized or distributed) or your st= orage (centralized or distributed) you still need a mechanism to model yo= ur data (YANG or other) and a mechanism to encode and transport your data= (Netconf or other).=20 Yes, if that was unclear in what I wrote, I apologise. I mean to say that= the mechanisms used to achieve very large scale, resilience and optimization will be dis= tribution of functions supported by machine learning etc. But indeed the delivery of c= onfig to the end systems will very likely not change. > Not sure what exactly is old-fashioned on Netconf/YANG for this purpose= s discussion, and what is has to do with using AI or not. =20 The point is that Netconf (and CLI, Radius, DHCP or any other way of deli= vering config) are all fundamentally equivalent, and my understanding is that on this li= st we are looking for innovation. Brian From salah@boun.edu.tr Fri May 12 07:22:55 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 9427912EBAB for ; Fri, 12 May 2017 07:22:55 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: 1.298 X-Spam-Level: * X-Spam-Status: No, score=1.298 tagged_above=-999 required=5 tests=[BAYES_50=0.8, RCVD_IN_SORBS_SPAM=0.5, RP_MATCHES_RCVD=-0.001, SPF_HELO_PASS=-0.001, SPF_PASS=-0.001, URIBL_BLOCKED=0.001] autolearn=no 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 vFoWD8pCFG_K for ; Fri, 12 May 2017 07:22:51 -0700 (PDT) Received: from smtp.boun.edu.tr (ispinoz.cc.boun.edu.tr [IPv6:2001:a98:8010:ccd0::16]) (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 EA12612EBC9 for ; Fri, 12 May 2017 07:17:54 -0700 (PDT) Received: from mail-io0-f176.google.com (mail-io0-f176.google.com [209.85.223.176]) by smtp.boun.edu.tr (Postfix) with ESMTPSA id 8E9B542EAD for ; Fri, 12 May 2017 17:17:50 +0300 (+03) Received: by mail-io0-f176.google.com with SMTP id o12so40957696iod.3 for ; Fri, 12 May 2017 07:17:50 -0700 (PDT) X-Gm-Message-State: AODbwcCPEOJEuRIIQ/yi+WMDAfjM654kSfkW1QBsB1TSTxex7ST7O2JE 71Y1QKFEefSRjqrJ2eTElsPc25X97g== X-Received: by 10.107.144.138 with SMTP id s132mr4641859iod.22.1494598668481; Fri, 12 May 2017 07:17:48 -0700 (PDT) MIME-Version: 1.0 Reply-To: salah@boun.edu.tr Received: by 10.36.172.98 with HTTP; Fri, 12 May 2017 07:17:18 -0700 (PDT) From: Albert Ali Salah Date: Fri, 12 May 2017 17:17:18 +0300 X-Gmail-Original-Message-ID: Message-ID: To: IDNET@ietf.org, connectionists@cs.cmu.edu Content-Type: text/plain; charset="UTF-8" Archived-At: Subject: [Idnet] Call for interest in an Advanced Workshop on Machine Learning For Network Security 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: Fri, 12 May 2017 14:46:24 -0000 Hi, We are planning to organize a NATO Science for Peace and Security (SPS) Programme Advanced Workshop that brings together machine learning and network security experts to advance the state of the art in this area. Typically, network intrusion detection systems (IDS) and intrusion prevention systems (IPS) work by pattern matching, and maintain signatures of different attack types in a centralized and widely used database. Such databases are regularly updated with new attack patterns, as soon as they are known. There are several open source platforms that can handle large volumes of network traffic, and became industry standards. However, attackers constantly adapt their approaches. These platforms need to be extended or supplemented with flexible, adaptive machine learning solutions. The planned topics are for the workshop are: -Fast machine learning approaches for network anomaly detection -Deep learning systems for detection of network attacks -Approaches for integrating CRM and network data for network security -Algorithms for attack type classification -DDOS attacks generated by IoT devices -Machine learning for security on software defined networking and NFV -Data and analytics driven network security We are collecting expressions of interest at the moment, either to be a speaker or a participant in such an event. The workshop will be followed by focused sessions to discuss joint project collaborations for the NATO SPS program. We are hoping to make some travel funding available for the participants. If you are interested in machine learning and network security, please contact A.A. Salah (salah@boun.edu.tr, Bogazici University) or S. Kuran (sukru.kuran@agu.edu.tr, Abdullah Gul University) until 25 May, 2017. We will determine the time & location of the workshop based on the interest. -- Dr. Albert Ali Salah Bogazici University, Computer Engineering Dept. 34342 Bebek - Istanbul, Turkey Phone: +90 212 359 (7774) http://www.cmpe.boun.edu.tr/~salah/ Bogazici University, Cognitive Science MA Program http://www.cogsci.boun.edu.tr From nobody Thu May 18 15:41:49 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 AC1B4129B9E for ; Thu, 18 May 2017 15:41:48 -0700 (PDT) X-Virus-Scanned: amavisd-new at amsl.com X-Spam-Flag: NO X-Spam-Score: -1.998 X-Spam-Level: X-Spam-Status: No, score=-1.998 tagged_above=-999 required=5 tests=[BAYES_50=0.8, HEADER_FROM_DIFFERENT_DOMAINS=0.001, HTML_MESSAGE=0.001, RCVD_IN_DNSWL_NONE=-0.0001, RCVD_IN_MSPIKE_H2=-2.8, RP_MATCHES_RCVD=-0.001, SPF_PASS=-0.001, TVD_SPACE_RATIO=0.001, URIBL_BLOCKED=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 GYf2WakTgBPa for ; Thu, 18 May 2017 15:41:46 -0700 (PDT) Received: from mx02.fc.ul.pt (mx02.fc.ul.pt [194.117.42.36]) (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 A8D3C12EBB0 for ; Thu, 18 May 2017 15:36:02 -0700 (PDT) Received: from FC-MBX1.fc.ul.pt (fc-mbx1.fc.ul.pt [10.121.30.11]) by mx02.fc.ul.pt (8.14.4/8.14.4) with ESMTP id v4IMYrIW010953 for ; Thu, 18 May 2017 23:34:54 +0100 Received: from FC-CAS2.fc.ul.pt (2001:690:21c0:f603::ca52) by FC-MBX1.fc.ul.pt (2001:690:21c0:f330::11) with Microsoft SMTP Server (TLS) id 15.0.1293.2; Thu, 18 May 2017 23:34:54 +0100 Received: from smtp.ciencias.ulisboa.pt (194.117.42.59) by FC-CAS2.fc.ul.pt (194.117.42.62) with Microsoft SMTP Server id 15.0.1293.2 via Frontend Transport; Thu, 18 May 2017 23:34:53 +0100 Received: from [IPv6:2001:8a0:6a4c:af01:6886:5860:ccb0:97e5] (unknown [IPv6:2001:8a0:6a4c:af01:6886:5860:ccb0:97e5]) (using TLSv1.2 with cipher ECDHE-RSA-AES256-GCM-SHA384 (256/256 bits)) (No client certificate requested) (Authenticated sender: fvramos@fc.ul.pt) by smtp.ciencias.ulisboa.pt (Postfix) with ESMTPSA id A339B40A0C21; Thu, 18 May 2017 23:34:53 +0100 (WEST) From: Fernando Ramos Content-Type: multipart/alternative; boundary="Apple-Mail-AB695C77-C343-4471-951B-17386F13FB36" Content-Transfer-Encoding: 7bit MIME-Version: 1.0 (1.0) Date: Thu, 18 May 2017 23:34:53 +0100 Message-ID: <18F3B1CF-7109-4B18-9607-102D5D204BCD@ciencias.ulisboa.pt> To: X-Mailer: iPad Mail (14E304) X-FCUL-MailScanner-Information: Please contact the ISP for more information X-FCUL-MailScanner-ID: v4IMYrIW010953 X-FCUL-MailScanner: Found to be clean X-FCUL-MailScanner-From: fvramos@fc.ul.pt Archived-At: Subject: [Idnet] TensorFlow Research Cloud 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: Thu, 18 May 2017 22:41:48 -0000 --Apple-Mail-AB695C77-C343-4471-951B-17386F13FB36 Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: 7bit Really great opportunity: https://www.tensorflow.org/tfrc/ Cheers, Fernando --Apple-Mail-AB695C77-C343-4471-951B-17386F13FB36 Content-Type: text/html; charset="utf-8" Content-Transfer-Encoding: 7bit Really great opportunity:


Cheers,

Fernando
--Apple-Mail-AB695C77-C343-4471-951B-17386F13FB36--