Further Prop 324 Updates:

Circuits will record the current RTT measurement as a field in their

circuit_t data structure. The current RTT is N-EWMA smoothed[27] over a

'cc_ewma_cwnd_cnt' multiple of congestion window worth.

'cc_ewma_cwnd_cnt' multiple of congestion window worth of sendme acks.

Circuits will also record the minimum and maximum RTT seen so far.

cells are handled is addressed in section [SYSTEM_INTERACTIONS].

   XXX: Hrmm, this is not strictly necessary for this proposal to function.

   It may make conflux easier though, but we can defer it to then.

   It may make conflux easier though, but we can defer it to then. The

   current implementation only counts RELAY_COMMAND_DATA towards sendme

   acks, which is the same behavior as the old fixed sendme implementation.

Third, authenticated SENDMEs can remain as-is in terms of protocol

behavior, but will require some implementation updates to account for

Note that the congestion window update algorithms differ slightly from the

background tor-dev mails[1,2], due to corrections and improvements. Hence they

have been given different names than in those two mails. The third algorithm,

[TOR_NOLA], simply uses BDP estimate directly as its congestion window.

[TOR_NOLA], simply uses the latest BDP estimate directly as its congestion

window.

These algorithms will be evaluated by running Shadow simulations, to

help determine parameter ranges, but experimentation on the live network

are inflight.

While these algorithms are in use, updates and checks of the current

'package_window' field are disabled. The 'deliver_window' field is still used

to decide when to send a SENDME. In C tor, the deliver window is initially set

at 1000, but it never gets below 900, because authenticated sendmes (Proposal

289) require that we must send only one SENDME at a time, and send it

immediately after 100 cells are received. This property turns out to be very

useful for [BDP_ESTIMATION].

'package_window' field are disabled. Where a 'package_window' value is

still needed, for example by cell packaging schedulers, 'cwnd - inflight' is

used (with checks to return 0 in the event of negative values).

The 'deliver_window' field is still used to decide when to send a SENDME. In C

tor, the deliver window is initially set at 1000, but it never gets below 900,

because authenticated sendmes (Proposal 289) require that we must send only

one SENDME at a time, and send it immediately after 100 cells are received.

This property turns out to be very useful for [BDP_ESTIMATION].

Implementation of different algorithms should be very simple - each

algorithm should have a different update function depending on the selected algorithm,

requires averaging over multiple SENDME acks to do so. The congestion window

and inflight estimates rely on the congestion algorithm more or less correctly

tracking an approximation of the BDP, and then use current and minimum RTT to

compensate for overshoot. These estimators tend to be accurate once the

congestion window exceeds BDP.

compensate for overshoot.

The SENDME estimator tends to be accurate after ~3-5 SENDME acks. The cwnd and

inflight estimators tend to be accurate once the congestion window exceeds

BDP.

We specify all three because they are all useful in various cases. These cases

are broken up and combined to form the Piecewise BDP estimator.

It is also useful to smooth these estimates through N-EWMA averaging on these

estimators[27], to smooth out temporary effects. The N parameter can be

modified by consensus parameter 'cc_ewma_cwnd_cnt', which specifies the number

of congestion windows worth of SENDME acks to compute an N-EWMA average over.

The SENDME estimator is smoothed through N-EWMA averaging on these

estimators[27], to smooth out temporary effects. This is accomplished by using

an EWMA function with alpha = 2/(N+1):

  N_EWMA = BDP*2/(N+1) + N_EWMA_prev*(N-1)/(N+1).

N is specified in terms of the number of current congestion windows worth of

SENDMEs to average, via consensus parameter 'cc_ewma_cwnd_cnt'.

The cwnd and inflight estimators also use N-EWMA smoothing in the same way,

but only smooth the current RTT estimate, not the congestion window value.

3.1.1. SENDME arrival BDP estimation

   BWE = num_sendmes * cc_sendme_inc / num_sendme_timestamp_delta

   BDP = BWE * RTT_min

However, because the timestamps are microseconds, to avoid integer

truncation, we compute the BDP using multiplication first:

   BDP = num_sendmes * cc_sendme_inc * RTT_min / num_sendme_timestamp_delta

Note that the SENDME BDP estimation will only work after two (2) SENDME acks

have been received. Additionally, it tends not to be stable unless at least

five (5) num_sendme's are used, due to ack compression. This is controlled by

If all edge connections no longer have data available to send on a circuit

and all circuit queues have drained without blocking the local orconn, we stop

updating this BDP estimate and discard old timestamps.

updating this BDP estimate and discard old timestamps. However, we retain the

actual estimator value.

3.1.2. Congestion Window BDP Estimation

the bandwidth estimate is the current congestion window size divided by the

RTT estimate:

   BWE = cwnd / RTT_current

   BWE = cwnd / RTT_current_ewma

The BDP estimate is computed by multiplying the Bandwidth estimate by

the *minimum* circuit latency:

Simplifying:

   BDP = cwnd * RTT_min / RTT_current

   BDP = cwnd * RTT_min / RTT_current_ewma

The net effect of this estimation is to correct for any overshoot of

the cwnd over the actual BDP. It will obviously underestimate BDP if cwnd

circuit queue use from the inflight packet count. This means it will be strictly

less than or equal to the cwnd version:

   BDP = (inflight - circ.chan_cells.n) * RTT_min / RTT_current

   BDP = (inflight - circ.chan_cells.n) * RTT_min / RTT_current_ewma

If all edge connections no longer have data available to send on a circuit

and all circuit queues have drained without blocking the local orconn, we stop

estimates based on lack of edge connection use, this estimator uses the

Congestion Window BDP estimator value.

3.1.5. N-EWMA Smoothing

To further minimize the effects of ack compression and sudden ephemeral

changes in RTT, we create smoothed versions of all three BDP estimators using

N-EWMA[27].

This is accomplished by using an EWMA function with alpha = 2/(N+1):

  BDP_EWMA = BDP*2/(N+1) + BDP_EWMA*(N-1)/(N+1).

N is specified in terms of the number of current congestion windows worth of

SENDMEs to average, via consensus parameter 'cc_ewma_cwnd_cnt'.

3.2. Tor Westwood: TCP Westwood using RTT signaling [TOR_WESTWOOD]

   http://intronetworks.cs.luc.edu/1/html/newtcps.html#tcp-westwood

measured arbitrarily, so long as it is larger than what we would get from

SENDME.

RTT_current is N-EWMA smoothed over a congestion window worth of SENDME acks.

RTT_current is N-EWMA smoothed over 'cc_ewma_cwnd_cnt' congestion windows

worth of SENDME acks.

Recall that BOOTLEG_RTT_TOR emits a congestion signal when the current

RTT falls below some fractional threshold ('cc_westwood_rtt_thresh') fraction

ideas/xxx-backward-ecn.txt, to exit Slow Start.)

Congestion signals from RTT, blocked OR connections, or ECN are processed only

once per congestion window.

once per congestion window. This is achieved through the next_cc_event flag,

which is initialized to a cwnd worth of SENDME acks, and is decremented

each ack. Congestion signals are only evaluated when it reaches 0.

Note that because the congestion signal threshold of TOR_WESTWOOD is a

function of RTT_max, and excessive queuing can cause an increase in RTT_max,

 if next_cc_event == 0:

   # BOOTLEG_RTT_TOR threshold; can also be BACKWARD_ECN check:

   if (RTT_current <

      (1−cc_westwood_rtt_thresh)*RTT_min + cc_westwood_rtt_thresh*RTT_max) or

      orconn_blocked:

      (100−cc_westwood_rtt_thresh)*RTT_min/100 +

      cc_westwood_rtt_thresh*RTT_max/100) or orconn_blocked:

     if in_slow_start:

       cwnd += cwnd * cc_cwnd_inc_pct_ss             # Exponential growth

     else:

   http://www.mathcs.richmond.edu/~lbarnett/cs332/assignments/brakmo_peterson_vegas.pdf

   ftp://ftp.cs.princeton.edu/techreports/2000/628.pdf

TCP Vegas control algorithm makes use of two RTT measurements:

RTT_current and RTT_min. Like TCP Westwood, it also maintains a

bandwidth estimate and a BDP estimate, but those can be simplified away

with algebra.

RTT_current is N-EWMA smoothed over a congestion window worth of SENDME acks.

The bandwidth estimate is the current congestion window size divided by

the RTT estimate:

TCP Vegas control algorithm estimates the queue lengths at relays by

subtracting the current BDP estimate from the current congestion window.

   BWE = cwnd/RTT_current

The extra queue use along a path can thus be estimated by first

estimating the path's bandwidth-delay product:

   BDP = BWE*RTT_min

Assuming the BDP estimate is accurate, any amount by which the congestion

window exceeds the BDP will cause data to queue.

TCP Vegas then estimates the queue use caused by congestion as:

Thus, Vegas estimates estimates the queue use caused by congestion as:

   queue_use = cwnd - BDP

             = cwnd - cwnd*RTT_min/RTT_current

             = cwnd * (1 - RTT_min/RTT_current)

However, because the SENDME BDP estimate is more accurate, and because

Piecewise BDP allows us to back off more when the local OR connection is

blocked, we parameterize this cwnd-based queue_use calculation as a tunable

weighted average between the cwnd-based estimate and the piecewise estimate

(consensus parameter 'cc_vegas_bdp_mix').

Original TCP Vegas used a cwnd BDP estimator only. However, because the SENDME

BDP estimate is more accurate, and because Piecewise BDP allows us to back off

more when the local OR connection is blocked, we use Piecewise BDP here.

For testing, we also parameterize this queue_use calculation as a tunable

weighted average between the cwnd-based BDP estimate and the piecewise

estimate (consensus parameter 'cc_vegas_bdp_mix').

Additionally, if the local OR connection is blocked at the time of SENDME ack

arrival, this is treated as an immediate congestion signal.

ideas/xxx-backward-ecn.txt, to exit Slow Start.)

Congestion signals from RTT, blocked OR connections, or ECN are processed only

once per congestion window.

once per congestion window. This is achieved through the next_cc_event flag,

which is initialized to a cwnd worth of SENDME acks, and is decremented

each ack. Congestion signals are only evaluated when it reaches 0.

Here is the complete pseudocode for TOR_VEGAS, which is run once per SENDME

ack:

Such an algorithm would need to overshoot the BDP slightly, especially in the

presence of competing algorithms. But other than that, it can be exceedingly

simple. Like Vegas, but without puttin' on airs. Just enough strung together.

simple. Like Vegas, but without putting on airs. Just enough strung together.

After meditating on this for a while, it also occurred to me that no one has

named a congestion control algorithm after New Orleans. We have Reno, Vegas,

Here's the pseudocode for TOR_NOLA that runs on every SENDME ack:

  if orconn_blocked:

    cwnd = BDP

  else:

    cwnd = BDP + cc_nola_overshoot

  cwnd = MAX(cwnd, cc_circwindow_min)

6.1. Congestion Signal Experiments

Our first experiments will be to conduct client-side experiments to

Our first experiments were to conduct client-side experiments to

determine how stable the RTT measurements of circuits are across the

live Tor network, to determine if we need more frequent SENDMEs, and/or

need to use any RTT smoothing or averaging.

Once we have a reliable way to measure RTT, we will need to test the

reliability and accuracy of the Bandwidth Estimation (BWE) and

Bandwidth-Delay-Product (BDP) measurements that are required for

[TOR_WESTWOOD] and [TOR_VEGAS]. These experiments can be conducted in

Shadow, with precise network topologies for which actual bandwidth and

latency (and thus BWE and BDP) are known parameters.  We should use the

most accurate form of these estimators from Shadow experimentation to

run some client tests with custom Exits on the live network, to check

for high variability in these estimates, discrepancy with client

application throughput and application latency, and other surprises.

Care will need to be taken to increase or alter Tor's circwindow during

these experiments in Shadow and on the custom Exits, so that the default

of 1000 does not impose an artificial ceiling on circuit bandwidth.

These experiments were performed using onion service clients and services on

the live Tor network. From these experiments, we tuned the RTT and BDP

estimators, and arrived at reasonable values for EWMA smoothing and the

minimum number of SENDME acks required to estimate BDP.

We should check small variations in the EWMA smoothing and minimum BDP ack

counts in Shadow experimentation, to check for high variability in these

estimates, and other surprises.

6.2. Congestion Algorithm Experiments

In order to evaluate performance of congestion control algorithms, we

will need to implement [TOR_WESTWOOD], [TOR_VEGAS], and also variants of

those without the Westwood BDP fast recovery backoff. We will need to

In order to evaluate performance of congestion control algorithms, we will

need to implement [TOR_WESTWOOD], [TOR_VEGAS], and [TOR_NOLA]. We will need to

simulate their use in the Shadow Tor network simulator.

Simulation runs will need to evaluate performance on networks that use

need to be set, but this will result in additional queueing as well as

sub-optimal behavior once all clients upgrade.

If Tor's current flow control is too aggressive, we can experiment with

kneecapping these legacy flow control Tor clients by setting a low

'circwindow' consensus parameter for them. This will allow us to set more

reasonable parameter values, without waiting for all clients to upgrade.

In particular, during live onion service testing, we noticed that these

algorithms required particularly agressive default values to compete against

a network full of current clients. As more clients upgrade, we may be able

to lower these defaults. We should get a good idea of what values we can

choose at what upgrade point, from mixed Shadow simulation.

If Tor's current flow control is so aggressive that it causes probelems with

any amount of remaining old clients, we can experiment with kneecapping these

legacy flow control Tor clients by setting a low 'circwindow' consensus

parameter for them. This will allow us to set more reasonable parameter

values, without waiting for all clients to upgrade.

Because custom congestion control can be deployed by any Exit or onion

service that desires better service, we will need to be particularly

as per [SECURITY_ANALYSIS]. This may requiring tuning CircuitEWMAHalfLife,

as well as the oomkiller cutoffs.

Additionally, we will need to experiment with reducing the cell queue

limits on OR conns before they are blocked, and study the interaction

of that with treating the or conn block as a congestion signal.

  TODO: We should make that into a consensus parameter

Finally, we should determine if the [BACKWARD_ECN] cell_t.command

congestion signal is enough of an optimization to be worth the

complexity, especially if it is only used once, to exit slow start. This

can be determined in Shadow.

Additionally, we specified that the algorithms maintain previous congestion

window estimates in the event that a circuit goes idle, rather than revert

to slow start. We should experiment with intermittent idle/active clients

to make sure that this behavior is acceptable.

6.3. Flow Control Algorithm Experiments

Exits. This can be done in simulation, but will require fine-tuning on

the live network.

Relays will need to report these statistics in extra-info descriptor,

to help with monitoring the live network conditions.

Additionally, we will need to experiment with reducing the cell queue

limits on OR conns before they are blocked, and study the interaction

of that with treating the or conn block as a congestion signal.

  TODO: We should make the cell queue highwater value into a consensus

  parameter in the flow control implementation.

Relays may report these statistics in extra-info descriptor, to help with

monitoring the live network conditions, but this might also require

aggregation or minimization.

6.4. Performance Metrics [EVALUATION_METRICS]

from throughput to RTT, to load balancing, queue length, overload, and

other failure conditions, the full set of performance metrics will be

required:

  https://trac.torproject.org/projects/tor/wiki/org/roadmaps/CoreTor/PerformanceMetrics

  https://gitlab.torproject.org/legacy/trac/-/wikis/org/roadmaps/CoreTor/PerformanceMetrics

We will also need to monitor network health for relay queue lengths,

relay overload, and other signs of network stress (and particularly the

parameters for our consensus parameters for each algorithm. We will then

re-run these tuning experiments on the live Tor network, as described

in:

  https://trac.torproject.org/projects/tor/wiki/org/roadmaps/CoreTor/PerformanceExperiments

  https://gitlab.torproject.org/tpo/core/team/-/wikis/NetworkTeam/Sponsor61/PerformanceExperiments

6.5.1. Parameters common to all algorithms

    - Tuning Notes:

           The lower this value is, the sooner we can get an estimate of

           the true BDP of a circuit. Low values may lead to massive

           over-estimation, due to ack compression.

           over-estimation, due to ack compression. However, if this

           value is above the number of acks that fit in cc_icw, then

           we won't get a BDP estimate within the first use of the circuit.

           Additionally, if this value is above the number of acks that

           fit in cc_cwnd_min, we may not be able to estimate BDP

           when the congestion window is small. If we need small congestion

           windows, we should also lower cc_sendme_inc, which will get us more

           frequent acks with less data.

  cc_sendme_inc:

    - Description: Specifies how many cells a SENDME acks

    - Range: [1, 5000]

    - Default: 50

    - Tuning Values: 25,33,50

    - Tuning Notes:

           Increasing this increases overhead, but also increases BDP

           estimation accuracy. Since we only use circuit-level sendmes,

           and the old code sent sendmes at both every 50 cells, and every

           100, we can set this as low as 33 to have the same amount of

           overhead.

  cc_icw:

    - Description: Initial congestion window for new congestion

    - Tuning Values: 150,200,250,500

    - Tuning Notes:

           Higher initial congestion windows allow the algorithms to

           more accurately, but will lead to queue bursts and latency.

           Ultimately, the ICW should be set to approximately

           measure initial BDP more accurately, but will lead to queue bursts

           and latency.  Ultimately, the ICW should be set to approximately

           'cc_bwe_min'*'cc_sendme_inc', but the presence of competing

           fixed window clients may require higher values.

           enough data to get any acks, and will stall. If it falls below

           cc_bwe_min*cc_sendme_inc, connections can't use SENDME BDP

           estimates. Likely we want to set this around

           cc_bwe_min*cc_sendme_inc.

           cc_bwe_min*cc_sendme_inc, but no lower than cc_sendme_inc.

  circwindow:

    - Description: Initial congestion window for legacy Tor clients

                   by during slow start, every cwnd.

    - Range: [10, 300]

    - Tuning Values: 50,100,200

    - Tuning Notes:

           On the current live network, the algorithms tended to exit slow

           start early, so we did not exercise this much. This may not be the

           case in Shadow, or once clients upgrade to the new algorithms.

  cc_bdp_alg:

    - Description: The BDP estimation algorithm to use.

    - Tuning Notes:

           We don't expect to need to tune this.

  cc_sendme_inc:

    - Description: Specifies how many cells a SENDME acks

    - Range: [1, 5000]

    - Default: 50

    - Tuning Notes:

           We don't expect to need to tune this.

6.5.2. Westwood parameters

  cc_westwood_rtt_thresh:

    https://github.com/torproject/tor/blob/master/doc/HACKING/CircuitPaddingDevelopment.md

24. Plans for Tor Live Network Performance Experiments

    https://trac.torproject.org/projects/tor/wiki/org/roadmaps/CoreTor/PerformanceExperiments

    https://gitlab.torproject.org/tpo/core/team/-/wikis/NetworkTeam/Sponsor61/PerformanceExperiments

25. Tor Performance Metrics for Live Network Tuning

    https://trac.torproject.org/projects/tor/wiki/org/roadmaps/CoreTor/PerformanceMetrics

    https://gitlab.torproject.org/legacy/trac/-/wikis/org/roadmaps/CoreTor/PerformanceMetrics

26. Bandwidth-Delay Product

    https://en.wikipedia.org/wiki/Bandwidth-delay_product