Re: [Idnet] IETF99 for applying AI/ML into network management: Follow-up

yanshen <yanshen@huawei.com> Fri, 28 July 2017 10:05 UTC

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From: yanshen <yanshen@huawei.com>
To: Simone Ferlin <simone@ferlin.io>
CC: "idnet@ietf.org" <idnet@ietf.org>, Pedro Martinez-Julia <pedro@nict.go.jp>
Thread-Topic: [Idnet] IETF99 for applying AI/ML into network management: Follow-up
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Date: Fri, 28 Jul 2017 10:05:05 +0000
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Subject: Re: [Idnet] IETF99 for applying AI/ML into network management: Follow-up
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Dear Simone,

Sheng had sent a page of PPT which was mostly focused in the meeting. You can find it in: https://www.ietf.org/mail-archive/web/idnet/current/msg00113.html

BTW, according to the discussion in mailing list, Pedro and I made a little modification and you can find it in the attachment: https://www.ietf.org/mail-archive/web/idnet/current/msg00104.html

It is welcome to point out the drawbacks and improve it.

Yansen

> -----Original Message-----
> From: Simone Ferlin [mailto:simone@ferlin.io]
> Sent: Thursday, July 27, 2017 11:05 AM
> To: Pedro Martinez-Julia <pedro@nict.go.jp>
> Cc: yanshen <yanshen@huawei.com>om>; idnet@ietf.org
> Subject: Re: [Idnet] IETF99 for applying AI/ML into network management:
> Follow-up
> 
> Hello everyone,
> 
> I have been following this list for some time, but I have not been in the meetings
> (f2f nor online) yet due to lack of time.
> Do you have a summary of these meetings, including the topics discussed at
> IETF'99, so that people like me could engage in the discussions? I see you started
> a thread here, but not with much I could understand the starting point.
> 
> Thanks and cheers,
> Simone
> 
> On Thu, Jul 27, 2017 at 11:16 AM, Pedro Martinez-Julia <pedro@nict.go.jp>
> wrote:
> > Dear Yanshen,
> >
> > Thanks for your comments, please find my reply in-line.
> >
> > On Thu, Jul 27, 2017 at 01:54:58AM +0000, yanshen wrote:
> >> > For me that depends on the algorithmic representation. We have two
> >> > types of
> >> > variables:
> >> >
> >> > - Measurable and controllable variables, such as the load of a resource
> >> >   managed by the solution, which can be known and can be altered by
> some
> >> >   decision of such solution (increase/decrease the amount of resources).
> >> >
> >> > - Measurable but non-controllable, which are outside the control of the
> >> >   solution. They can be known and used to take decisions but cannot be
> >> >   altered (directly or indirectly) by the solution. A simple example can
> >> >   be found in the occurrence of some event that can affect to a system,
> >> >   such as the number of attendees to a baseball match. The management
> >> >   solution cannot control such variable but uses it to determine the
> >> >   amount of network resources assigned to the network of the stadium.
> >>
> >> I have a similar thought. I try to divide the variables into
> >> objective and subjective (may corresponding to your controllable and
> >> non-controllable. Perhaps a little different).
> >>
> >>       - The objective data means that we can capture, input or measure it
> >>       periodically from any source (whatever it is). This class of data
> >>       needs to be focused and formatted, including the context and format
> >>       and so on. One of the cases is QoS value which I just mentioned.
> >>
> >>       - The subjective data means that it is imported into the machine
> >>       (AI/Brain/Knowledge system) temporarily or irregularly. This class
> >>       of data may be high-level and diversity. The solution for them I
> >>       think should be pushed to application layer. It is not our dishes.
> >>       Another thought is that we should try to obtain more subjective data
> >>       by objective way, for example, we should try to change the way of
> >>       obtaining the "reward" feedback from "user randomly report" to
> >>       "periodically capture". Unless such, it should not be included into
> >>       our consideration.
> >>
> >> I think it is significant to combine our two dimensions into one. Of
> >> course other dimensions may also considerable.
> >
> > They are different aspects and, of course, they must be combined. My
> > classification is based on the "control theory", which clearly states
> > what a controlled variable means and the strict definition of the loop
> > closure (closed-loop controller), which implies to check such
> > variables and confirm they are changed according to the intended
> > objective after some change/s is/are applied to the controlled environment.
> >
> > On the other hand, your view is more practical in terms of the scope
> > of the information in relation to the AI algorithm and its needs. It
> > would be good to simplify/unify both dimensions but also to
> > simplify/unify the differences within them. I mean that it would be
> > probably a good option to consider any kind of data homogeneously. I
> > am using a simple ontology to resolve such problem, so we could
> > probably use it and a corresponding YANG model, as I proposed in my
> > other message, to achieve such unified view. Please, let me know your
> thoughts. 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 ***
> >
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