updates from summit

Author: warner

docs/specifications/servers-of-happiness.rst

@@ -194,39 +194,53 @@ Calculating Share Placements
 
 We calculate share placement like so:
 
-1. Query *2N* servers for existing shares.
+0. Start with an ordered list of servers. Maybe *2N* of them.
 
-2. Construct a bipartite graph of *readonly* servers to shares, where an edge
-   exists between an arbitrary readonly server S and an arbitrary share T if
-   and only if S currently holds T.
+1. Query all servers for existing shares.
 
-3. Calculate a maximum matching graph of that bipartite graph. There may be
-   more than one maximum matching for this graph; we choose one of them
-   arbitrarily.
+2. Construct a bipartite graph G1 of *readonly* servers to pre-existing
+   shares, where an edge exists between an arbitrary readonly server S and an
+   arbitrary share T if and only if S currently holds T.
 
-4. Construct a bipartite graph of servers (whether readonly or readwrite) to
-   shares, removing any servers and shares used in the maximum matching graph
-   from step 3. Let an edge exist between server S and share T if and only if
-   S already holds T.
+3. Calculate a maximum matching graph of G1 (a set of S->T edges that has or
+   is-tied-for the highest "happiness score"). There is a clever efficient
+   algorithm for this, named "Ford-Fulkerson". There may be more than one
+   maximum matching for this graph; we choose one of them arbitrarily, but
+   prefer earlier servers. Call this particular placement M1. The placement
+   maps shares to servers, where each share appears at most once, and each
+   server appears at most once.
 
-5. Calculate the maximum matching graph of the new graph.
+4. Construct a bipartite graph G2 of readwrite servers to pre-existing
+   shares. Then remove any edge (from G2) that uses a server or a share found
+   in M1. Let an edge exist between server S and share T if and only if S
+   already holds T.
 
-6. Construct a bipartite graph of servers (whether readonly or readwrite) to
-   share, removing any servers and shares used in the maximum matching graphs
-   from steps 3 and 5. Let an edge exist between server S and share T if and
-   only if S *could* hold T (i.e. S is readwrite and S has enough available
-   space to hold a share of at least T's size).
+5. Calculate a maximum matching graph of G2, call this M2, again preferring
+   earlier servers.
 
-7. Calculate the maximum matching graph of the new graph.
+6. Construct a bipartite graph G3 of (only readwrite) servers to shares. Let
+   an edge exist between server S and share T if and only if S already has T,
+   or *could* hold T (i.e. S has enough available space to hold a share of at
+   least T's size). Then remove (from G3) any servers and shares used in M1
+   or M2 (note that we retain servers/shares that were in G1/G2 but *not* in
+   the M1/M2 subsets)
 
-8. Renew the shares on their respective servers from steps 3 and 5.
+7. Calculate a maximum matching graph of G3, call this M3, preferring earlier
+   servers. The final placement table is the union of M1+M2+M3.
 
-9. Place share T on server S if an edge exists between S and T in the maximum
-   matching graph from step 7.
+8. Renew the shares on their respective servers from M1 and M2.
 
-10. If any placements from step 7 fail, remove the server from the set of
-    possible servers and regenerate the matchings. XXX go back to step 4?
+9. Upload share T to server S if an edge exists between S and T in M3.
 
+10. If any placements from step 9 fail, mark the server as read-only. Go back
+    to step 2 (since we may discover a server is/has-become read-only, or has
+    failed, during step 9).
+
+Rationale (Step 4): when we see pre-existing shares on read-only servers, we
+prefer to rely upon those (rather than the ones on read-write servers), so we
+can maybe use the read-write servers for new shares. If we picked the
+read-write server's share, then we couldn't re-use that server for new ones
+(we only rely upon each server for one share, more or less).
 
 Properties of Upload Strategy of Happiness
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