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@@ -34,6 +34,9 @@ Implementation
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From our initial observations, this value appears to be on the order
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of 1000, but will be configurable in a #define NCIRCUITS_TO_OBSERVE.
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+ The exact value for this #define will be determined by performing
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+ goodness of fit tests using measurments obtained from the shufflebt.py
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+ script from TorFlow.
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Long Term Storage
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@@ -41,17 +44,31 @@ Implementation
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histogram with BUILDTIME_BIN_WIDTH millisecond buckets (default 50) when
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writing out the statistics to disk. The format of this histogram on disk
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is yet to be finalized, but it will likely be of the format
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- 'CircuitBuildTime <bin> <count>'.
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+ 'CircuitBuildTime <bin> <count>', with the total specified as
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+ 'TotalBuildTimes <total>'
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Example:
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- CircuitBuildTimeBin 1 100
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- CircuitBuildTimeBin 2 50
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+ TotalBuildTimes 100
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+ CircuitBuildTimeBin 1 50
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+ CircuitBuildTimeBin 2 25
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+ CircuitBuildTimeBin 3 13
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...
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Reading the histogram in will entail multiplying each bin by the
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BUILDTIME_BIN_WIDTH and then inserting <count> values into the
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circuit_build_times array each with the value of
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- <bin>*BUILDTIME_BIN_WIDTH.
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+ <bin>*BUILDTIME_BIN_WIDTH. In order to evenly distribute the
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+ values in the circular array, a form of index skipping must
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+ be employed. Values from bin #N with bin count C and total T
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+ will occupy indexes specified by N+((T/C)*k)-1, where k is the
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+ set of integers ranging from 0 to C-1.
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+
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+ For example, this would mean that the values from bin 1 would
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+ occupy indexes 1+(100/50)*k-1, or 0, 2, 4, 6, 8, 10 and so on.
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+ The values for bin 2 would occupy positions 1, 5, 9, 13. Collisions
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+ will be inserted at the first empty position in the array greater
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+ than the selected index (which may requiring looping around the
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+ array back to index 0).
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Learning the CircuitBuildTimeout
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@@ -71,6 +88,27 @@ Implementation
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From http://en.wikipedia.org/wiki/Pareto_distribution#Definition,
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the calculation we need is pow(BUILDTIME_PERCENT_CUTOFF/100.0, k)/Xm.
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+ Testing
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+
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+ After circuit build times, storage, and learning are implemented,
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+ the resulting histogram should be checked for consistency by
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+ verifying it persists across successive Tor invocations where
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+ no circuits are built. In addition, we can also use the existing
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+ buildtime scripts to record build times, and verify that the histogram
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+ the python produces matches that which is output to the state file in Tor,
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+ and verify that the Pareto parameters and cutoff points also match.
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+
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+ Soft timeout vs Hard Timeout
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+
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+ At some point, it may be desirable to change the cutoff from a
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+ single hard cutoff that destroys the circuit to a soft cutoff and
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+ a hard cutoff, where the soft cutoff merely triggers the building
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+ of a new circuit, and the hard cutoff triggers destruction of the
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+ circuit.
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+
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+ Good values for hard and soft cutoffs seem to be 85% and 65%
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+ respectively, but we should eventually justify this with observation.
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+
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When to Begin Calculation
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The number of circuits to observe (NCIRCUITS_TO_CUTOFF) before
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@@ -87,9 +125,6 @@ Implementation
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Also, in the event of network failure, the observation mechanism
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should stop collecting timeout data.
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- Circuits that timeout will be destroyed, as this indicates one
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- or more of their respective nodes are currently overloaded.
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-
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Client Hints
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Some research still needs to be done to provide initial values
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