Hoi,
It is the distribution in time of geographical needs that is critical. When
a particular article becomes relevant in a certain area, you want to address
the flood of requests by distributing the article to the peers that are
close to where the demand is. In this peering system, a node may have an
article but it is not necessary to have all articles.
As was mentioned before, work has been done on the data received from the
WMF. Based on the data a paper will be published in the near future. When it
is available, I will post a link.
Thanks,
Gerard
On 9/15/07, Gregory Maxwell <gmaxwell(a)gmail.com> wrote:
On 9/15/07, GerardM <gerard.meijssen(a)gmail.com> wrote:
Hoi,
The university of Amsterdam (UvA) is getting log information that is
thoroughly anonymised to the point where it becomes not as useful as it
should be. The UvA is working on what they call a "peer to peer
Wikipedia".
Their interest in the data is not in the specific
IP number of a
requester
for information, their interest is in where a
request is coming from.
The
point is that is best, fastest and cheapest when
information is
available
from a peer that is close by.
Would a simple break down of bytes and requests per autonomous system
number over a fairly wide time window (say, days), fit their needs?
Example data:
Collection Span ASN REQs Bytes sent hit-rate
20070801000000-20070801235959 14907 1000 10289000 .99987
20070802000000-20070801235959 14907 2000 20578013 .99916
Or perhaps by hour and AS over some span:
Collection Span HrGMT ASN REQs Bytes sent hit-rate
20070801000000-20070814235959 00 14907 40 411560 .9688
20070801000000-20070814235959 01 14907 20 205780 .9832
I don't see any reason why we couldn't release aggregates like these.
We should be generating them for our own planning purposes in any
case.
If they wanted details about object locality and things like that, we
could anonymize requests objects by unique IDs but doing that would
require a lot more care.
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