Update proposal to bring it more in-line with implementation.

1 files changed, 40 insertions, 40 deletions

diff --git a/proposals/151-path-selection-improvements.txt b/proposals/151-path-selection-improvements.txt
index 3d5f07d..df19e0f 100644
--- a/proposals/151-path-selection-improvements.txt
+++ b/proposals/151-path-selection-improvements.txt
@@ -2,7 +2,7 @@ Filename: 151-path-selection-improvements.txt
 Title: Improving Tor Path Selection
 Author: Fallon Chen, Mike Perry
 Created: 5-Jul-2008
-Status: Draft
+Status: Implemented
 
 Overview
 
@@ -22,51 +22,37 @@ Implementation
 
   Storing Build Times
 
-    Circuit build times will be stored in the circular array
-    'circuit_build_times' consisting of uint16_t elements as milliseconds.
-    The total size of this array will be based on the number of circuits
+    Circuit build times are stored in the circular array
+    'circuit_build_times' consisting of uint32_t elements as milliseconds.
+    The total size of this array is based on the number of circuits
     it takes to converge on a good fit of the long term distribution of
     the circuit builds for a fixed link. We do not want this value to be
     too large, because it will make it difficult for clients to adapt to
     moving between different links.
 
-    From our initial observations, this value appears to be on the order 
-    of 1000, but will be configurable in a #define NCIRCUITS_TO_OBSERVE.
-    The exact value for this #define will be determined by performing
-    goodness of fit tests using measurments obtained from the shufflebt.py
-    script from TorFlow.
+    From our observations, this value appears to be on the order of 1000, 
+    but is configurable in a #define NCIRCUITS_TO_OBSERVE.
  
   Long Term Storage
 
-    The long-term storage representation will be implemented by storing a 
+    The long-term storage representation is implemented by storing a 
     histogram with BUILDTIME_BIN_WIDTH millisecond buckets (default 50) when 
-    writing out the statistics to disk. The format of this histogram on disk 
-    is yet to be finalized, but it will likely be of the format 
-    'CircuitBuildTime <bin> <count>', with the total specified as 
-    'TotalBuildTimes <total>'
+    writing out the statistics to disk. The format this takes in the
+    state file is 'CircuitBuildTime <bin-ms> <count>', with the total 
+    specified as 'TotalBuildTimes <total>'
     Example:
 
     TotalBuildTimes 100
-    CircuitBuildTimeBin 1 50
-    CircuitBuildTimeBin 2 25
-    CircuitBuildTimeBin 3 13
+    CircuitBuildTimeBin 0 50
+    CircuitBuildTimeBin 50 25
+    CircuitBuildTimeBin 100 13
     ...
 
-    Reading the histogram in will entail multiplying each bin by the 
-    BUILDTIME_BIN_WIDTH and then inserting <count> values into the 
-    circuit_build_times array each with the value of
-    <bin>*BUILDTIME_BIN_WIDTH. In order to evenly distribute the 
-    values in the circular array, a form of index skipping must
-    be employed. Values from bin #N with bin count C and total T
-    will occupy indexes specified by N+((T/C)*k)-1, where k is the
-    set of integers ranging from 0 to C-1.
-
-    For example, this would mean that the values from bin 1 would
-    occupy indexes 1+(100/50)*k-1, or 0, 2, 4, 6, 8, 10 and so on.
-    The values for bin 2 would occupy positions 1, 5, 9, 13. Collisions
-    will be inserted at the first empty position in the array greater 
-    than the selected index (which may requiring looping around the 
-    array back to index 0).
+    Reading the histogram in will entail inserting <count> values
+    into the circuit_build_times array each with the value of
+    <bin-ms> milliseconds. In order to evenly distribute the values
+    in the circular array, the Fisher-Yates shuffle will be performed
+    after reading values from the bins.
 
   Learning the CircuitBuildTimeout
 
@@ -77,14 +63,28 @@ Implementation
     fitting the data using the estimators at
     http://en.wikipedia.org/wiki/Pareto_distribution#Parameter_estimation.
 
-    The timeout itself will be calculated by solving the CDF for the 
-    a percentile cutoff BUILDTIME_PERCENT_CUTOFF. This value
-    represents the percentage of paths the Tor client will accept out of
-    the total number of paths. We have not yet determined a good
-    cutoff for this mathematically, but 85% seems a good choice for now.
+    The timeout itself is calculated by using the Quartile function (the
+    inverted CDF) to give us the value on the CDF such that
+    BUILDTIME_PERCENT_CUTOFF (80%) of the mass of the distribution is
+    below the timeout value.
 
-    From http://en.wikipedia.org/wiki/Pareto_distribution#Definition,
-    the calculation we need is pow(BUILDTIME_PERCENT_CUTOFF/100.0, k)/Xm. 
+    Thus, we expect that the Tor client will accept the fastest 80% of 
+    the total number of paths on the network.
+
+  Detecting Changing Network Conditions
+
+    We attempt to detect both network connectivty loss and drastic
+    changes in the timeout characteristics. Network connectivity loss
+    is detected by recording a timestamp every time Tor either completes
+    a TLS connection or receives a cell. If this timestamp is more than 
+    90 seconds in the past, circuit timeouts are no longer counted.
+
+    If more than MAX_RECENT_TIMEOUT_RATE (80%) of the past 
+    RECENT_CIRCUITS (20) time out, we assume the network connection
+    has changed, and we discard all buildtimes history and compute
+    a new timeout by estimating a new Pareto curve using the
+    position on the Pareto Quartile function for the ratio of
+    timeouts. 
 
   Testing
 
@@ -104,7 +104,7 @@ Implementation
     of a new circuit, and the hard cutoff triggers destruction of the 
     circuit.
 
-    Good values for hard and soft cutoffs seem to be 85% and 65% 
+    Good values for hard and soft cutoffs seem to be 80% and 60% 
     respectively, but we should eventually justify this with observation.
 
   When to Begin Calculation