update a few documents, comments, and defaults to mention 3-of-10 instead of 25-of-100

docs/architecture.txt

@@ -270,8 +270,8 @@ Because the shares being downloaded are distributed across a large number of
 peers, the download process will pull from many of them at the same time. The
 current encoding parameters require 3 shares to be retrieved for each
 segment, which means that up to 3 peers will be used simultaneously. For
-larger networks, 25-of-100 encoding is preferred, meaning 25 peers can be
-used simultaneously. This allows the download process to use the sum of the
+larger networks, 8-of-22 encoding could be used, meaning 8 peers can be used
+simultaneously. This allows the download process to use the sum of the
 available peers' upload bandwidths, resulting in downloads that take full
 advantage of the common 8x disparity between download and upload bandwith on
 modern ADSL lines.
@@ -550,10 +550,10 @@ different goals. Each choice results in a number of properties; there are
 many tradeoffs.
 
 First, some terms: the erasure-coding algorithm is described as K-out-of-N
-(for this release, the default values are K=25 and N=100). Each grid will
-have some number of peers; this number will rise and fall over time as peers
-join, drop out, come back, and leave forever. Files are of various sizes,
-some are popular, others are rare. Peers have various capacities, variable
+(for this release, the default values are K=3 and N=10). Each grid will have
+some number of peers; this number will rise and fall over time as peers join,
+drop out, come back, and leave forever. Files are of various sizes, some are
+popular, others are rare. Peers have various capacities, variable
 upload/download bandwidths, and network latency. Most of the mathematical
 models that look at peer failure assume some average (and independent)
 probability 'P' of a given peer being available: this can be high (servers

src/allmydata/encode.py

@@ -21,8 +21,8 @@ of shares is chosen to hit our reliability goals (more shares on more
 machines means more reliability), and is limited by overhead (proportional to
 numshares or log(numshares)) and the encoding technology in use (Reed-Solomon
 only permits 256 shares total). It is also constrained by the amount of data
-we want to send to each host. For estimating purposes, think of 100 shares
-out of which we need 25 to reconstruct the file.
+we want to send to each host. For estimating purposes, think of 10 shares
+out of which we need 3 to reconstruct the file.
 
 The encoder starts by cutting the original file into segments. All segments
 except the last are of equal size. The segment size is chosen to constrain
@@ -71,9 +71,9 @@ PiB=1024*TiB
 
 class Encoder(object):
     implements(IEncoder)
-    NEEDED_SHARES = 25
-    SHARES_OF_HAPPINESS = 75
-    TOTAL_SHARES = 100
+    NEEDED_SHARES = 3
+    SHARES_OF_HAPPINESS = 7
+    TOTAL_SHARES = 10
     MAX_SEGMENT_SIZE = 1*MiB
 
     def __init__(self, options={}):
@@ -285,10 +285,10 @@ class Encoder(object):
 
         # memory footprint: we only hold a tiny piece of the plaintext at any
         # given time. We build up a segment's worth of cryptttext, then hand
-        # it to the encoder. Assuming 25-of-100 encoding (4x expansion) and
-        # 2MiB max_segment_size, we get a peak memory footprint of 5*2MiB =
-        # 10MiB. Lowering max_segment_size to, say, 100KiB would drop the
-        # footprint to 500KiB at the expense of more hash-tree overhead.
+        # it to the encoder. Assuming 3-of-10 encoding (3.3x expansion) and
+        # 2MiB max_segment_size, we get a peak memory footprint of 4.3*2MiB =
+        # 8.6MiB. Lowering max_segment_size to, say, 100KiB would drop the
+        # footprint to 430KiB at the expense of more hash-tree overhead.
 
         d = self._gather_data(self.required_shares, input_piece_size,
                               crypttext_segment_hasher)

src/allmydata/interfaces.py

@@ -682,7 +682,7 @@ class IEncoder(Interface):
         be created.
 
         Encoding parameters can be set in three ways. 1: The Encoder class
-        provides defaults (25/75/100). 2: the Encoder can be constructed with
+        provides defaults (3/7/10). 2: the Encoder can be constructed with
         an 'options' dictionary, in which the
         needed_and_happy_and_total_shares' key can be a (k,d,n) tuple. 3:
         set_params((k,d,n)) can be called.