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Title: Computing Bandwidth Adjustments
Filename: 161-computing-bandwidth-adjustments.txt
Author: Mike Perry
Created: 12-May-2009
Target: 0.2.1.x
Status: Closed
1. Motivation
There is high variance in the performance of the Tor network. Despite
our efforts to balance load evenly across the Tor nodes, some nodes are
significantly slower and more overloaded than others.
Proposal 160 describes how we can augment the directory authorities to
vote on measured bandwidths for routers. This proposal describes what
goes into the measuring process.
2. Measurement Selection
The general idea is to determine a load factor representing the ratio
of the capacity of measured nodes to the rest of the network. This load
factor could be computed from three potentially relevant statistics:
circuit failure rates, circuit extend times, or stream capacity.
Circuit failure rates and circuit extend times appear to be
non-linearly proportional to node load. We've observed that the same
nodes when scanned at US nighttime hours (when load is presumably
lower) exhibit almost no circuit failure, and significantly faster
extend times than when scanned during the day.
Stream capacity, however, is much more uniform, even during US
nighttime hours. Moreover, it is a more intuitive representation of
node capacity, and also less dependent upon distance and latency
if amortized over large stream fetches.
3. Average Stream Bandwidth Calculation
The average stream bandwidths are obtained by dividing the network into
slices of 50 nodes each, grouped according to advertised node bandwidth.
Two hop circuits are built using nodes from the same slice, and a large
file is downloaded via these circuits. The file sizes are set based
on node percentile rank as follows:
0-10: 2M
10-20: 1M
20-30: 512k
30-50: 256k
50-100: 128k
These sizes are based on measurements performed during test scans.
This process is repeated until each node has been chosen to participate
in at least 5 circuits.
4. Ratio Calculation
The ratios are calculated by dividing each measured value by the
network-wide average.
5. Ratio Filtering
After the base ratios are calculated, a second pass is performed
to remove any streams with nodes of ratios less than X=0.5 from
the results of other nodes. In addition, all outlying streams
with capacity of one standard deviation below a node's average
are also removed.
The final ratio result will be greater of the unfiltered ratio
and the filtered ratio.
6. Pseudocode for Ratio Calculation Algorithm
Here is the complete pseudocode for the ratio algorithm:
Slices = {S | S is 50 nodes of similar consensus capacity}
for S in Slices:
while exists node N in S with circ_chosen(N) < 7:
fetch_slice_file(build_2hop_circuit(N, (exit in S)))
for N in S:
BW_measured(N) = MEAN(b | b is bandwidth of a stream through N)
Bw_stddev(N) = STDDEV(b | b is bandwidth of a stream through N)
Bw_avg(S) = MEAN(b | b = BW_measured(N) for all N in S)
for N in S:
Normal_Streams(N) = {stream via N | bandwidth >= BW_measured(N)}
BW_Norm_measured(N) = MEAN(b | b is a bandwidth of Normal_Streams(N))
Bw_net_avg(Slices) = MEAN(BW_measured(N) for all N in Slices)
Bw_Norm_net_avg(Slices) = MEAN(BW_Norm_measured(N) for all N in Slices)
for N in all Slices:
Bw_net_ratio(N) = Bw_measured(N)/Bw_net_avg(Slices)
Bw_Norm_net_ratio(N) = BW_Norm_measured(N)/Bw_Norm_net_avg(Slices)
ResultRatio(N) = MAX(Bw_net_ratio(N), Bw_Norm_net_ratio(N))
7. Security implications
The ratio filtering will deal with cases of sabotage by dropping
both very slow outliers in stream average calculations, as well
as dropping streams that used very slow nodes from the calculation
of other nodes.
This scheme will not address nodes that try to game the system by
providing better service to scanners. The scanners can be detected
at the entry by IP address, and at the exit by the destination fetch
IP.
Measures can be taken to obfuscate and separate the scanners' source
IP address from the directory authority IP address. For instance,
scans can happen offsite and the results can be rsynced into the
authorities. The destination server IP can also change.
Neither of these methods are foolproof, but such nodes can already
lie about their bandwidth to attract more traffic, so this solution
does not set us back any in that regard.
8. Parallelization
Because each slice takes as long as 6 hours to complete, we will want
to parallelize as much as possible. This will be done by concurrently
running multiple scanners from each authority to deal with different
segments of the network. Each scanner piece will continually loop
over a portion of the network, outputting files of the form:
node_id= SP strm_bw= SP
filt_bw= ns_bw= NL
The most recent file from each scanner will be periodically gathered
by another script that uses them to produce network-wide averages
and calculate ratios as per the algorithm in section 6. Because nodes
may shift in capacity, they may appear in more than one slice and/or
appear more than once in the file set. The most recently measured
line will be chosen in this case.
9. Integration with Proposal 160
The final results will be produced for the voting mechanism
described in Proposal 160 by multiplying the derived ratio by
the average published consensus bandwidth during the course of the
scan, and taking the weighted average with the previous consensus
bandwidth:
Bw_new = Round((Bw_current * Alpha + Bw_scan_avg*Bw_ratio)/(Alpha + 1))
The Alpha parameter is a smoothing parameter intended to prevent
rapid oscillation between loaded and unloaded conditions. It is
currently fixed at 0.333.
The Round() step consists of rounding to the 3 most significant figures
in base10, and then rounding that result to the nearest 1000, with
a minimum value of 1000.
This will produce a new bandwidth value that will be output into a
file consisting of lines of the form:
node_id= SP bw= NL
The first line of the file will contain a timestamp in UNIX time()
seconds. This will be used by the authority to decide if the
measured values are too old to use.
This file can be either copied or rsynced into a directory readable
by the directory authority.
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