On Sat, Nov 22, 2003 at 06:22:57PM +0200, Jusa Saari wrote: > On Fri, 21 Nov 2003 22:47:21 +0000, Toad wrote: > > > On Fri, Nov 21, 2003 at 03:20:58PM -0500, Ed Tomlinson wrote: > >> On November 21, 2003 01:45 pm, Toad wrote: > >> > On Fri, Nov 21, 2003 at 12:01:27PM -0500, Ed Tomlinson wrote: > >> > > On November 21, 2003 06:41 am, Ian Clarke wrote: > >> > > > It seems that we aren't seeing the hoped-for specialization in NGR. > >> > > > Rather than futzing about with all sorts of ideas while trying to test > >> > > > them in the chaotic real network, we need a simple simulator to help us > >> > > > test these ideas. > >> > > > >> > > One idea to test on that simulator is are we specializing by key or > >> > > for fast connections. It seems to me that, by far, the largest chunks > >> > > of the NG estimator are from transmission time... When I did the > >> > > first stabs at NG I was only basing it on search times and, if > >> > > memory serves, it was getting much better numbers. > >> > > > >> > > Maybe we should be normallizing to a size that does not give > >> > > a number much greater than transmission time? > >> > > >> > Why? > >> > >> The search time is usually a number averaging around 15,000 ms > >> The time to recieve a normalized file is over 150,000 ms. This > >> means the 15000 (or 2000 or 30000) gets lost in the noise and NGR > >> just looks for the fastest node. > > > > Those are not the only factors involved. The transfer time is multiplied > > by the probability of a transfer occurring. > > > I must ask... Doesn't this mean that the worse the node's chances of > finding a given key, the better (lower) the estimate ? Shouldn't you > multiply by the (1 - probability of transfer occurring) ?
No. The possibility of failure is also taken into account. Further, a node that is better at a given key subspace should also transfer data faster in that area. > > Unfortunately, I was unable to find the formula of estimate in the CVS > source, so I couldn't check... Anyway, if this is true, it would explain > the despecialization. StandardNodeEstimator.longEstimate(). -- Matthew J Toseland - [EMAIL PROTECTED] Freenet Project Official Codemonkey - http://freenetproject.org/ ICTHUS - Nothing is impossible. Our Boss says so.
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