Neural Networks implementation on SAN - Storage

This is a discussion on Neural Networks implementation on SAN - Storage ; Dear friends, Please let me know is there any recent work on SAN(Storage Area Network) based on Neural Networks implementation. Basically I want to know FC,SCSI,RAID or SAN which involved the implementation on Neural Networks. Thanks & Regds, Babi...

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Thread: Neural Networks implementation on SAN

  1. Neural Networks implementation on SAN


    Dear friends,
    Please let me know is there any recent work on SAN(Storage Area
    Network) based on Neural Networks implementation.
    Basically I want to know FC,SCSI,RAID or SAN which involved the
    implementation on Neural Networks.


    Thanks & Regds,
    Babi


  2. Re: Neural Networks implementation on SAN


    "babi" wrote in message
    news:1120131842.847151.207260@o13g2000cwo.googlegr oups.com...
    >
    > Dear friends,
    > Please let me know is there any recent work on SAN(Storage Area
    > Network) based on Neural Networks implementation.
    > Basically I want to know FC,SCSI,RAID or SAN which involved the
    > implementation on Neural Networks.
    >


    Huh? SANs deal with getting blocks from storage to hosts, as such it's hard
    to see how (or for that matter why) you would need to implement a neural
    network in your SAN.


    --
    Nik Simpson



  3. Re: Neural Networks implementation on SAN

    Neural network can be used to perfomance prediction since the media
    devices are involved. From the host system the intelligence can be used
    to predict the intense I/O storage to route the request from host to
    storage. This may be intereesting but I am not sure.
    Thanks & Regds,
    Babi


  4. Re: Neural Networks implementation on SAN


    "babi" wrote in message
    news:1120214135.972078.29820@g43g2000cwa.googlegro ups.com...
    > Neural network can be used to perfomance prediction since the media
    > devices are involved. From the host system the intelligence can be used
    > to predict the intense I/O storage to route the request from host to
    > storage. This may be intereesting but I am not sure.
    > Thanks & Regds,
    > Babi
    >


    My Only thoughts on this matter are that if you are using a neural net to
    perform calcutions made up of various cells like grid network then a SAN
    would assist in providing a storage network enabling data sharing through
    SAN equivelant software to NFS, like SANFS, SANergy, etc..

    Regards
    Paresh



  5. Re: Neural Networks implementation on SAN

    What problems are you trying to solve here? You may be on the road to
    creating something too complicated to be reliable. I know that one thing
    that could potentially be good about a SAN might be striping a little bit of
    high-i/o data across a bunch of disks that are mostly full of data that is
    rarely if ever read, this way you could get most of your heads spinning at
    the same time, while not wasting gigs of space to do it. I suspect that you
    are going after a certain level of flexibility, but if your solution is too
    big you could be headed for the weeds.

    c ya

    "babi" wrote in message
    news:1120214135.972078.29820@g43g2000cwa.googlegro ups.com...
    > Neural network can be used to perfomance prediction since the media
    > devices are involved. From the host system the intelligence can be used
    > to predict the intense I/O storage to route the request from host to
    > storage. This may be intereesting but I am not sure.
    > Thanks & Regds,
    > Babi
    >




  6. Re: Neural Networks implementation on SAN

    In article <1120214135.972078.29820@g43g2000cwa.googlegroups.c om>,
    babi wrote:
    >Neural network can be used to perfomance prediction since the media
    >devices are involved. From the host system the intelligence can be used
    >to predict the intense I/O storage to route the request from host to
    >storage. This may be intereesting but I am not sure.


    If I understand this post correctly, you propose the following:

    1. A. Predict performance of storage devices and SANs. This requires
    a detailed understanding of the devices, the SAN components, and
    the workload (the set of IOs that the application will issue).
    B. Do this performance prediction using neural networks.
    2. Then use the performance prediction to configure the workload and
    SAN, optimizing it for your desired goals (low cost, good
    performance, high reliability, certain tradeoffs between these
    quantities, or whatever tickles your fancy).

    These ideas are very old, and this path is extremely well-trodden. If
    I were funny and cynical, I would say that this path is lined with the
    dead bodies of hundreds of researchers and industry practitioners who
    attempted to do this (and mostly failed, or died of old age before
    succeeding). If you succeeded in this endeavor, you would have solved
    one large problem on the way to building self-managing storage.

    I've never heard of anyone using neural networks for the performance
    prediction (the step 1.B. from above). The usual techniques use
    ingredients from queueing theory, markov models, utilization metrics,
    grey- and block-box techniques, heuristics. Also tried were genetic
    algorithms and a few other exotics (most of which I've forgotten
    about). There is maybe a half dozen textbooks on performance
    prediction and optimization as applied to computer systems; most of
    the stuff written in them has been applied to storage systems and
    storage networks at some time or another.

    Read the research literature, to get a level set on the state of the
    art today. Easiest thing to do is to do a google search for the
    "Minerva" and "Hippodrome" papers (authors include Wilkes, Merchant,
    Alvarez, Veitch, and a host of others), and use those as a starting
    point, following their references and citations (those two papers see
    the world through one particular set of rose-colored glasses, so don't
    assume that their conclusions are not controversial, because other
    workers in this field have differently rose-colored glasses). Once
    you are done with that, I would get my hands on the proceedings of the
    three or four "FAST" conferences (stands for "File and Storage
    Technologies", look at the Usenix website or in a library near you),
    where you can study the state of the art in storage performance
    prediction and self-management. For your particular interest, a long
    look at the proceedings of the "SigMetrics" conference might also be
    highly interesting.

    --
    The address in the header is invalid for obvious reasons. Please
    reconstruct the address from the information below (look for _).
    Ralph Becker-Szendy _firstname_@lr_dot_los-gatos_dot_ca.us

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