Re: [dtn-interest] Question

Yes, thats a question i still seem to have, for DSN and even distant
plantes, will reliable transport alone suffice? and is intermediate nodes
all the way upto the desitnation is feasible? For, DTN, it appears,
essentially relies on, intermediate nodes (or the distance between source
and destination say such as for mars say being mangeable) so as to not
have intermediate nodes and do store and forward at source.
> I think a lot of work in reliable multicasts has foundations in tornado
> codes such as digital fountain.  They may be using non-proprietary stuff
> here.
>
> http://en.wikipedia.org/wiki/Tornado_code
>
> Interleaving helps with gaps.
>
> That being said, most of this discussion  is related to reliable transport
> (convergence layer) more so than store and forward.
>
> Will
>
> ******************************
> William D. Ivancic
> Phone 216-433-3494
> Fax 216-433-8705
> Networking Lab 216-433-2620
> Mobile 440-503-4892
> http://roland.grc.nasa.gov/~ivancic
>
>
>
>> From: Daniel Ellard <dellard@bbn.com>
>> Date: Mon, 28 Jan 2013 21:12:14 -0600
>> To: "dtn-interest@irtf.org" <dtn-interest@irtf.org>
>> Subject: Re: [dtn-interest] Question
>>
>> On 1/28/13 8:44 PM, sitaraman@nmsworks.co.in wrote:
>>> I did, and my understanding is it is an erasure code  with a larger
>>> margin
>>> of error allowed for the signal can be recovered from a subset of the
>>> encoded signals...so it still cant handle losses?
>>
>> It is correct that a "digital fountain" is an instance of a forward
>> error-correcting code.
>>
>> As such, it has the property that it encodes a string of data D of
>> length N as a set of much smaller strings e0, e1, ..., eX such that
>> the original string D can be reconstructed from any subset of e0,
>> e1, ... eX if the sum of the lengths of each e in the subset is
>> greater or equal to N.  (an "efficient" FEC is one such that any
>> subset of length N will suffice; my recollection is that fountain
>> codes are not guaranteed to be efficient, but are generally within a
>> small margin of it.)  It is possible to choose an encoding method to
>> make each e computable independently of the rest, and the set of all
>> possible e's for a given D practically unlimited.
>>
>> The sender can continuously compute and transmit e's, and as soon as
>> the receiver receives enough e's, the receiver is successful.  It
>> doesn't matter how many e's are lost en route (or which are lost) as
>> long as enough arrive eventually.
>>
>> Fountain codes are one example of a FEC with this property, but the
>> last time I checked (which was a while ago, admittedly) they had two
>> drawbacks: first, the efficient implementations were protected by
>> patents, and second, they weren't well-described or available as
>> open-source.  Perhaps that has changed.
>>
>> In any case, if you want to understand the basic theory of efficient
>> FECs, Rabin's "Information Dispersal Algorithm", based on polynomial
>> interpolation, is a good place to start.  For implementations of
>> related codes that can be implemented efficiently, James Plank's
>> work on erasure codes for storage is the most practical work of
>> which I am aware.
>>
>> -Dan
>>
>> --
>> Daniel Ellard, Ph.D.
>> Senior Scientist, Network Research
>> Raytheon BBN Technologies
>> dellard@bbn.com
>>
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