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- Title: Computing Bandwidth Adjustments
- Filename: 161-computing-bandwidth-adjustments.txt
- Author: Mike Perry
- Created: 12-May-2009
- Target: 0.2.2.x
- Status: Open
- 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. For nodes in the first 15% of the
- network, a 500K file will be used. For nodes in the next 15%, a 250K file
- will be used. For nodes in next 15%, a 100K file will be used. The
- remainder of the nodes will fetch a 75K file.[1]
- This process is repeated 250 times, and average stream capacities are
- assigned to each node from these results.
-
- In the future, a node generator type can be created to ensure that
- each node is chosen to participate in an equal number of circuits,
- and the selection will continue until every live node is chosen
- to participate in at least 7 circuits.
-
- 4. Ratio Calculation Options
- There are two options for deriving the ratios themselves. They can
- be obtained by dividing each nodes' average stream capacity by
- either the average for the slice, or the average for the network as a
- whole.
- Dividing by the network-wide average has the advantage that it will
- account for issues related to unbalancing between higher vs lower
- capacity, such as Steven Murdoch's queuing theory weighting result.
- For this reason, we will opt for network-wide averages.
- 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 calculated as the maximum of
- these two resulting ratios if both are less than 1.0, the minimum
- if both are greater than 1.0, and the mean if one is greater
- and one is less than 1.0.
- 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)
- Normal_Routers(S) = {N | Bw_measured(N)/Bw_avg(S) > 0.5 }
- for N in S:
- Normal_Streams(N) =
- {stream via N | all nodes in stream not in {Normal_Routers(S)-N}
- and bandwidth > BW_measured(N)-Bw_stddev(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_measured2(N)/Bw_Norm_net_avg(Slices)
- if Bw_net_ratio(N) < 1.0 and Bw_Norm_net_ratio(N) < 1.0:
- ResultRatio(N) = MAX(Bw_net_ratio(N), Bw_Norm_net_ratio(N))
- else if Bw_net_ratio(N) > 1.0 and Bw_Norm_net_ratio(N) > 1.0:
- ResultRatio(N) = MIN(Bw_net_ratio(N), Bw_Norm_net_ratio(N))
- else:
- ResultRatio(N) = MEAN(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.
- 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 fetch can also be obscured by using SSL
- and periodically changing the large document that is fetched.
- 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=<idhex> SP strm_bw=<BW_measured(N)> SP
- filt_bw=<BW_Norm_measured(N)> 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 line that yields a ratio
- closest to 1.0 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 = (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.
- This will produce a new bandwidth value that will be output into a
- file consisting of lines of the form:
- node_id=<idhex> SP bw=<Bw_new> 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.
- 1. Exact values for each segment are still being determined via
- test scans.
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