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author | Julius Bünger <buenger@mytum.de> | 2019-06-22 01:56:10 +0200 |
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committer | Julius Bünger <buenger@mytum.de> | 2019-06-22 01:56:10 +0200 |
commit | 50de5483528687312e90f29178f716c9d868d55c (patch) | |
tree | ea12748e5ecb81c98ccb46d24619bc906f237cc5 /doc/handbook/chapters/developer.texi | |
parent | f031f34d3f523985cbecc13f276c879d35707683 (diff) |
Doc RPS: Add high-level subsection on Brahms
Diffstat (limited to 'doc/handbook/chapters/developer.texi')
-rw-r--r-- | doc/handbook/chapters/developer.texi | 26 |
1 files changed, 26 insertions, 0 deletions
diff --git a/doc/handbook/chapters/developer.texi b/doc/handbook/chapters/developer.texi index e101b06bd..a43bd7b37 100644 --- a/doc/handbook/chapters/developer.texi +++ b/doc/handbook/chapters/developer.texi @@ -8907,3 +8907,29 @@ client requests independently random, they cannot be drawn from the connected peers. The adapted sampler makes sure that each request for random peers is independent from the others. + +@node Brahms +@subsection Brahms +The high-level concept of Brahms is two-fold: Combining push-pull gossip +with locally fixing a assumed bias using cryptographic min-wise +permutations. +The central data structure is the view - a peer's current local sample. +This view is used to select peers to push to and pull from. +This simple mechanism can be biased easily. For this reason Brahms +'fixes' the bias by using the so-called sampler. A data structure that +takes a list of elements as input and outputs a random one of them +independently of the frequency in the input set. Both an element that +was put into the sampler a single time and an element that was put into +it a million times have the same probability of being the output. +This is achieved this is achieved with exploiting min-wise independent +permutations. In rps we use HMACs: On the initialisation of a sampler +element, a key is chosen at random. On each input the HMAC with the +random key is computed. The sampler element keeps the element with the +minimal HMAC. + +In order to fix the bias in the view, a fraction of the elements in the +view are sampled through the sampler from the random stream of peer IDs. + +According to the theoretical analysis of Bortnikov et al. this suffices +to keep the network connected and having random peers in the view. + |