LEDBAT WG                                                    S. Shalunov
Internet-Draft                                            BitTorrent Inc
Intended status: Experimental                             March 22, 2010
Expires: September 23, 2010

             Low Extra Delay Background Transport (LEDBAT)


   LEDBAT is an alternative experimental congestion control algorithm.

   LEDBAT enables an advanced networking application to minimize the
   extra delay it induces in the bottleneck while saturating the
   bottleneck.  It thus implements an end-to-end version of scavenger
   service.  LEDBAT has been been implemented in BitTorrent DNA, as the
   exclusive congestion control mechanism, and in uTorrent, as an
   experimental mechanism, and deployed in the wild with favorable

Status of this Memo

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Copyright Notice

   Copyright (c) 2010 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

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Table of Contents

   1.  Requirements notation  . . . . . . . . . . . . . . . . . . . .  3
   2.  Introduction . . . . . . . . . . . . . . . . . . . . . . . . .  3
   3.  LEDBAT design goals  . . . . . . . . . . . . . . . . . . . . .  3
   4.  LEDBAT motivation  . . . . . . . . . . . . . . . . . . . . . .  4
     4.1.  Simplest network topology  . . . . . . . . . . . . . . . .  4
     4.2.  Extra delay  . . . . . . . . . . . . . . . . . . . . . . .  4
     4.3.  Queuing delay target . . . . . . . . . . . . . . . . . . .  4
     4.4.  Need to measure delay  . . . . . . . . . . . . . . . . . .  5
     4.5.  Queing delay estimate  . . . . . . . . . . . . . . . . . .  5
     4.6.  Controller . . . . . . . . . . . . . . . . . . . . . . . .  5
     4.7.  Max rampup rate same as TCP  . . . . . . . . . . . . . . .  5
     4.8.  Halve on loss  . . . . . . . . . . . . . . . . . . . . . .  6
     4.9.  Yield to TCP . . . . . . . . . . . . . . . . . . . . . . .  6
     4.10. Need for one-way delay . . . . . . . . . . . . . . . . . .  6
     4.11. Measuring one-way delay  . . . . . . . . . . . . . . . . .  6
     4.12. Route changes  . . . . . . . . . . . . . . . . . . . . . .  6
     4.13. Timestamp errors . . . . . . . . . . . . . . . . . . . . .  7
       4.13.1.  Clock offset  . . . . . . . . . . . . . . . . . . . .  7
       4.13.2.  Clock skew  . . . . . . . . . . . . . . . . . . . . .  7
     4.14. Noise filtering  . . . . . . . . . . . . . . . . . . . . .  8
     4.15. Non-bulk flows . . . . . . . . . . . . . . . . . . . . . .  8
     4.16. LEDBAT framing and wire format . . . . . . . . . . . . . .  9
     4.17. Fairness between LEDBAT flows  . . . . . . . . . . . . . .  9
       4.17.1.  Late comers . . . . . . . . . . . . . . . . . . . . . 10
     4.18. Safety of LEDBAT . . . . . . . . . . . . . . . . . . . . . 11
   5.  LEDBAT congestion control  . . . . . . . . . . . . . . . . . . 11
   6.  Security Considerations  . . . . . . . . . . . . . . . . . . . 14
   7.  Normative References . . . . . . . . . . . . . . . . . . . . . 14
   Author's Address . . . . . . . . . . . . . . . . . . . . . . . . . 14

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1.  Requirements notation

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   document are to be interpreted as described in [RFC2119].

2.  Introduction

   The standard congestion control in TCP is based on loss and has not
   been designed to drive delay to any given value.  Because TCP needs
   losses to back off, when a FIFO bottleneck lacks AQM, TCP fills the
   buffer, effectively maximizing possible delay.  Large number of the
   thinnest links in the Internet, particularly most uplinks of home
   connections, lack AQM.  They also frequently contain enough buffer
   space to get delays into hundreds of milliseconds and even seconds.
   There is no benefit to having delays this large, but there are very
   substantial drawbacks for interactive applications: games and VoIP
   become impossible and even web browsing becomes very slow.

   While a number of delay-based congestion control mechanisms have been
   proposed, they were generally not designed to minimize the delay
   induced in the network.

   LEDBAT is designed to allow to keep the latency across the congested
   bottleneck low even as it is saturated.  This allows applications
   that send large amounts of data, particularly upstream on home
   connections, such as peer-to-peer application, to operate without
   destroying the user experience in interactive applications.  LEDBAT
   takes advantage of delay measurements and backs off before loss
   occurs.  It has been deployed by BitTorrent in the wild with the
   BitTorrent DNA client and now, experimentally, with the uTorrent
   client.  This mechanism not only allows to keep delay across a
   bottleneck low, but also yields quickly in the presence of competing
   traffic with loss-based congestion control.

   Beyond its utility for P2P, LEDBAT enables other advanced networking
   applications to better get out of the way of interactive apps.

   In addition to direct and immediate benefits for P2P and other
   application that can benefit from scavenger service, LEDBAT could
   point the way for a possible future evolution of the Internet where
   loss is not part of the designed behavior and delay is minimized.

3.  LEDBAT design goals

   LEDBAT design goals are:

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   1.  saturate the bottleneck
   2.  keep delay low when no other traffic is present
   3.  quickly yield to traffic sharing the same bottleneck queue that
       uses standard TCP congestion control
   4.  add little to the queuing delays induced by TCP traffic
   5.  operate well in networks with FIFO queuing with drop-tail
   6.  be deployable for popular applications that currently comprise
       noticeable fractions of Internet traffic
   7.  where available, use explicit congestion notification (ECN),
       active queue management (AQM), and/or end-to-end differentiated
       services (DiffServ).

4.  LEDBAT motivation

   This section describes LEDBAT informally and provides some
   motivation.  It is expected to be helpful for general understanding
   and useful in discussion of the properties of LEDBAT.

   Without a loss of generality, we can consider only one direction of
   the data transfer.  The opposite direction can be treated

4.1.  Simplest network topology

   Consider first the desired behavior when there's only a single
   bottleneck and no competing traffic whatsoever, not even other LEDBAT
   connections.  The design goals obviously need to be robustly met for
   this trivial case.

4.2.  Extra delay

   Consider the queuing delay on the bottleneck.  This delay is the
   extra delay induced by congestion control.  One of our design goals
   is to keep this delay low.  However, when this delay is zero, the
   queue is empty and so no data is being transmitted and the link is
   thus not saturated.  Hence, our design goal is to keep the queuing
   delay low, but non-zero.

4.3.  Queuing delay target

   How low do we want the queuing delay to be?  Because another design
   goal is to be deployable on networks with only simple FIFO queuing
   and drop-tail discipline, we can't rely on explicit signaling for the
   queuing delay.  So we're going to estimate it using external
   measurements.  The external measurements will have an error at least
   on the order of best-case scheduling delays in the OSes.  There's

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   thus a good reason to try to make the queuing delay larger than this
   error.  There's no reason that would want us to push the delay much
   further up.  Thus, we will have a delay target that we would want to

4.4.  Need to measure delay

   To maintain delay near the target, we have to use delay measurements.
   Lacking delay measurements, we'd have to go only by loss (when ECN is
   lacking).  For loss to occur (on a FIFO link with drop-tail
   discipline), the buffer must first be filled.  This would drive the
   delay to the largest possible value for this link, thus violating our
   design goal of keeping delay low.

4.5.  Queing delay estimate

   Since our goal is to control the queuing delay, it is natural to
   maintain an estimate of it.  Let's call delay components propagation,
   serialization, processing, and queuing.  All components but queuing
   are nearly constant and queuing is variable.  Because queuing delay
   is always positive, the constant propagation+serialization+processing
   delay is no less than the minimum delay observed.  Assuming that the
   queuing delay distribution density has non-zero integral from zero to
   any sufficiently small upper limit, minimum is also an asymptotically
   consistent estimate of the constant fraction of the delay.  We can
   thus estimate the queuing delay as the difference between current and
   base delay as usual.

4.6.  Controller

   When our estimate of the queuing delay is lower than the target, it's
   natural to send faster.  When our estimate is higher, it's natural to
   send slower.  To avoid trivial oscillations on round-trip-time (RTT)
   scale, the response of the controller needs to be near zero when the
   estimate is near the target.  To converge faster, the response needs
   to increase as the difference increases.  The simplest controller
   with this property is the linear controller, where the response is
   proportional to the difference between the estimate and the target.
   This controller happens to work well in practice obviating the need
   for more complex ones.

4.7.  Max rampup rate same as TCP

   The maximum speed with which we can increase our congestion window is
   then when queuing delay estimate is zero.  To be on the safe side,
   we'll make this speed equal to how fast TCP increases its sending
   speed.  Since queuing delay estimate is always non-negative, this
   will ensure never ramping up faster than TCP would.

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4.8.  Halve on loss

   Further, to deal with severe congestion when most packets are lost
   and to provide a safety net against incorrect queuing delay
   estimates, we'll halve the window when a loss event is detected.
   We'll do so at most once per RTT.

4.9.  Yield to TCP

   Consider competition between a LEDBAT connection and a connection
   governed by loss-based congestion control (on a FIFO bottleneck with
   drop-tail discipline).  Loss-based connection will need to experience
   loss to back off.  Loss will only occur after the connection
   experiences maximum possible delays.  LEDBAT will thus receive
   congestion indication sooner than the loss-based connection.  If
   LEDBAT can ramp down faster than the loss-based connection ramps up,
   LEDBAT will yield.  LEDBAT ramps down when queuing delay estimate
   exceeds the target: the more the excess, the faster the ramp-down.
   When the loss-based connection is standard TCP, LEDBAT will yield at
   precisely the same rate as TCP is ramping up when the queuing delay
   is double the target.

4.10.  Need for one-way delay

   Now consider a case when one link direction is saturated with
   unrelated TCP traffic while another direction is near-empty.
   Consider LEDBAT sending in the near-empty direction.  Our design goal
   is to saturate it.  However, if we pay attention to round-trip
   delays, we'll sense the delays on the reverse path and respond to
   them as described in the previous paragraph.  We must, thus, measure
   one-way delay and use that for our queuing delay estimate.

4.11.  Measuring one-way delay

   A special IETF protocol, One-Way Active Measurement Protocol (OWAMP),
   exists for measuring one-way delay.  However, since LEDBAT will
   already be sending data, it is more efficient to add a timestamp to
   the packets on the data direction and a measurement result field on
   the acknowledgement direction.  This also prevents the danger of
   measurement packets being treated differently from the data packets.
   The failure case would be better treatment of measurement packets,
   where the data connection would be driven to losses.

4.12.  Route changes

   Routes can change.  To deal, base delay needs to be computed over a
   period of last few minutes instead of since the start of connection.
   The tradeoff is: for longer intervals, base is more accurate; for

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   shorter intervals, reaction to route changes is faster.

   A convenient way to implement an approximate minimum over last N
   minutes is to keep separate minima for last N+1 minutes (last one for
   the partial current minute).

4.13.  Timestamp errors

   One-way delay measurement needs to deal with timestamp errors.  We'll
   use the same locally linear clock model and the same terminology as
   Network Time Protocol (NTP).  This model is valid for any
   differentiable clocks.  NTP uses the term "offset" to refer to
   difference from true time and "skew" to refer to difference of clock
   rate from the true rate.  The clock will thus have a fixed offset
   from the true time and a skew.  We'll consider what we need to do
   about the offset and the skew separately.

4.13.1.  Clock offset

   First, consider the case of zero skew.  The offset of each of the two
   clocks shows up as a fixed error in one-way delay measurement.  The
   difference of the offsets is the absolute error of the one-way delay
   estimate.  We won't use this estimate directly, however.  We'll use
   the difference between that and a base delay.  Because the error
   (difference of clock offsets) is the same for the current and base
   delay, it cancels from the queuing delay estimate, which is what
   we'll use.  Clock offset is thus irrelevant to the design.

4.13.2.  Clock skew

   Now consider the skew.  For a given clock, skew manifests in a
   linearly changing error in the time estimate.  For a given pair of
   clocks, the difference in skews is the skew of the one-way delay
   estimate.  Unlike the offset, this no longer cancels in the
   computation of the queuing delay estimate.  On the other hand, while
   the offset could be huge, with some clocks off by minutes or even
   hours or more, the skew is typically not too bad.  For example, NTP
   is designed to work with most clocks, yet it gives up when the skew
   is more than 500 parts per million (PPM).  Typical skews of clocks
   that have never been trained seem to often be around 100-200 PPM.
   Previously trained clocks could have 10-20 PPM skew due to
   temperature changes.  A 100-PPM skew means accumulating 6
   milliseconds of error per minute.  The expiration of base delay
   related to route changes mostly takes care of clock skew.  A
   technique to specifically compute and cancel it is trivially possible
   and involves tracking base delay skew over a number of minutes and
   then correcting for it, but usually isn't necessary, unless the
   target is unusually low, the skew is unusually high, or the base

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   interval is unusually long.  It is not further described in this

4.14.  Noise filtering

   In addition to timestamp errors, one-way delay estimate includes an
   error of measurement when part of the time measured was spent inside
   the sending or the receiving machines.  Different views are possible
   on the nature of this delay: one view holds that, to the extent this
   delay internal to a machine is not constant, it is a variety of
   queuing delay and nothing needs to be done to detect or eliminate it;
   another view holds that, since this delay does not have the same
   characteristics as queuing delay induced by a fixed-capacity
   bottleneck, it is more correctly classified as non-constant
   processing delay and should be filtered out.  In practice, this
   doesn't seem to matter very much one way or the other.  The way to
   filter the noise out is to observe, again, that the noise is always
   nonnegative and so a good filter is the minimum of several recent
   delay measurements.

4.15.  Non-bulk flows

   Normally in transport, we're mainly concerned with bulk flows with
   infinite sources.  Sometimes this model needs modification.  For
   example, an application might be limiting the rate at which the data
   is fed to the transport layer.  If the offered rate can be carried by
   the network without any sign of congestion, an adaptive congestion
   control loop will increase the rate allowed by congestion control.
   The LEDBAT mechanism in the form described above will keep increasing
   the congestion window linearly with time.  This is clearly wrong for
   non-bulk flows because it allows the congestion control to decide
   that it is allowed to send much faster than it has ever sent.
   Therefore, some special treatment is required to deal with the case
   of non-bulk flows.

   The same problem may also occur in some TCP implementations.  It has
   first been noticed for TCP in situations where a connection has been
   idle for a substantial time and the original workaround was to re-
   enter slow start after an idle period.  While re-entering slow start
   (or, more generally, returning to the original state of the
   connection) is a good idea after a long idle period, it does not
   solve the problem for connections that are trickling data out at an
   application-determined rate.  In fact, even application-level
   keepalives or small metadata exchanges can be enough to keep the
   connection from becoming idle for long.  The fix for this problem is
   to limit the growth of the congestion window by a quantity related to
   the current flight size, i.e., the amount of outstanding
   unacknowledged data.

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   The congestion window should not grow beyond a factor of the current
   flight size for sufficiently large values of the flight size.  This
   provides leeway for the congestion window to grow and probe the
   network beyond the current rate, at the same time keeping it on a
   tether that does not let it increase indefinitely.  A refinement of
   this rule is that the congestion window should not grow beyond a
   constant plus a factor of the flight size.  The presence of the
   additive constant is necessary because the congestion window needs to
   be able to increase at least by one packet even when it is small --
   otherwise no probing is possible.  The smallest value, one packet,
   then would define the minimum value of the factor: 2.  However, for
   larger values of congestion window, a tighter bound than "double the
   flight size" may be desirable.  The additive constant makes it
   possible to use values between 1 and 2 for the factor.

4.16.  LEDBAT framing and wire format

   The actual framing and wire format of the protocol(s) using the
   LEDBAT congestion control mechanism is outside of scope of this
   document, which only describes the congestion control part.

   There is an implication of the need to use one-way delay from the
   sender to the receiver in the sender.  An obvious way to support this
   is to use a framing that timestamps packets at the sender and conveys
   the measured one-way delay back to the sender in ack packets.  This
   is the method we'll keep in mind for the purposes of exposition.
   Other methods are possible and valid.

   The protocols to which this congestion control mechanism is
   applicable, with possible appropriate extensions, are TCP, SCTP,
   DCCP, etc.  It is not a goal of this document to cover such
   applications.  The mechanism can also be used with proprietary
   transport protocols, e.g., those built over UDP for P2P applications.

4.17.  Fairness between LEDBAT flows

   The design goals of LEDBAT center around the aggregate behavior of
   LEDBAT flows when they compete with standard TCP.  It is also
   interesting how LEDBAT flows share bottleneck bandwidth when they
   only compete between themselves.

   LEDBAT as described so far lacks a mechanism specifically designed to
   equalize utilization between these flows.  The observed behavior of
   existing implementations indicates that a rough equalization, in
   fact, does occur.

   The delay measurements used as control inputs by LEDBAT contain some
   amount of noise and errors.  The linear controller converts this

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   input noise into the same amount of output noise.  The effect that
   this has is that the uncorrelated component of the noise between
   flows serves to randomly shuffle some amount of bandwidth between
   flows.  The amount shuffled during each RTT is proportional to the
   noise divided by the target delay.  The random-walk trajectory of
   bandwidth utilized by each of the flows over time tends to the fair
   share.  The timescales on which the rates become comparable are
   proportional to the target delay multiplied by the RTT and divided by
   the noise.

   In complex real-life systems, the main concern is usually the
   reduction of the amount of noise, which is copious if not eliminated.
   In some circumstances, however, the measurements might be "too good"
   -- since the equalization timescale is inversely proportional to
   noise, perfect measurements would result in lack of convergence.

   Under these circumstances, it may be beneficial to introduce some
   artificial randomness into the inputs (or, equivalently, outputs) of
   the controller.  Note that most systems should not require this and
   should be primarily concerned with reducing, not adding, noise.

4.17.1.  Late comers

   With delay-based congestion control systems, there's a concern about
   the ability of late comers to measure the base delay correctly.
   Suppose a LEDBAT flow saturates a bottleneck; another LEDBAT flow
   starts and proceeds to measure the base delay and the current delay
   and to estimate the queuing delay.  If the bottleneck always contains
   target delay worth of packets, the second flow would see the
   bottleneck as empty start building a second target delay worth of
   queue on top of the existing queue.  The concern ("late comers'
   advantage") is that the initial flow would now back off because it
   sees the real delay and the late comer would use the whole capacity.

   However, once the initial flow yields, the late comer immediately
   measures the true base delay and the two flows operate from the same
   (correct) inputs.

   Additionally, in practice this concern is further alleviated by the
   burstiness of network traffic: all that's needed to measure the base
   delay is one small gap.  These gaps can occur for a variety of
   reasons: the OS may delay the scheduling of the sending process until
   a time slice ends, the sending computer might be unusually busy for
   some number of milliseconds or tens of milliseconds, etc.  If such a
   gap occurs while the late comer is starting, base delay is
   immediately correctly measured.  With small number of flows, this
   appears to be the main mechanism of regulating the late comers'

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4.18.  Safety of LEDBAT

   LEDBAT is most aggressive when its queuing delay estimate is most
   wrong and is as low as it can be.  Queuing delay estimate is
   nonnegative, therefore the worst possible case is when somehow the
   estimate is always returned as zero.  In this case, LEDBAT will ramp
   up as fast as TCP and halve the rate on loss.  Thus, in case of worst
   possible failure of estimates, LEDBAT will behave identically to TCP.
   This provides an extra safety net.

5.  LEDBAT congestion control

   Consider two parties, a sender and a receiver, with the sender having
   an unlimited source of data to send to the receiver and the receiver
   merely acknowledging the data.  (In an actual protocol, it's more
   convenient to have bidirectional connections, but unidirectional
   abstraction suffices to describe the congestion control mechanism.)

   Consider a protocol that uses packets of equal size and acknowledges
   each of them separately.  (Variable-sized packets and delayed
   acknowledgements are possible and are being implemented, but
   complicate the exposition.)

   Assume that each data packet contains a header field timestamp.  The
   sender puts a timestamp from its clock into this field.  Further
   assume that each acknowledgement packet contains a field delay.  It
   is shown below how it is populated.

   Slow start behavior is unchanged in LEDBAT.  Note that rampup is
   faster in slow start than during congestion avoidance and so very
   conservative implementations MAY skip slow start altogether.

   As far as congestion control is concerned, the receiver is then very
   simple and operates as follows, using a pseudocode:

   on data_packet:
     remote_timestamp = data_packet.timestamp
     acknowledgement.delay = local_timestamp() - remote_timestamp
     # fill in other fields of acknowledgement

   The sender actually operates the congestion control algorithm and
   acts, in first approximation, as follows:

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   on initialization:
     base_delay = +infinity

   on acknowledgement:
     current_delay = acknowledgement.delay
     base_delay = min(base_delay, current_delay)
     queuing_delay = current_delay - base_delay
     off_target = TARGET - queuing_delay
     cwnd += GAIN * off_target / cwnd

   The pseudocode above is a simplification and ignores noise filtering
   and base expiration.  The more precise pseudocode that takes these
   factors into account is as follows and MUST be followed:

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   on initialization:
     set all NOISE_FILTER delays used by current_delay() to +infinity
     set all BASE_HISTORY delays used by base_delay() to +infinity
     last_rollover = -infinity # More than a minute in the past.

   on acknowledgement:
     delay = acknowledgement.delay
     queuing_delay = current_delay() - base_delay()
     off_target = TARGET - queuing_delay + random_input()
     cwnd += GAIN * off_target / cwnd
     # flight_size() is the amount of currently not acked data.
     max_allowed_cwnd = ALLOWED_INCREASE + TETHER*flight_size()
     cwnd = min(cwnd, max_allowed_cwnd)

     # random() is a PRNG between 0.0 and 1.0
     # NB: RANDOMNESS_AMOUNT is normally 0
     RANDOMNESS_AMOUNT * TARGET * ((random() - 0.5)*2)

     # Maintain a list of NOISE_FILTER last delays observed.
     forget the earliest of NOISE_FILTER current_delays
     add delay to the end of current_delays

     min(the NOISE_FILTER delays stored by update_current_delay)

     # Maintain BASE_HISTORY min delays. Each represents a minute.
     if round_to_minute(now) != round_to_minute(last_rollover)
       last_rollover = now
       forget the earliest of base delays
       add delay to the end of base_delays
       last of base_delays = min(last of base_delays, delay)

     min(the BASE_HISTORY min delays stored by update_base_delay)

   TARGET parameter MUST be set to 25 milliseconds and GAIN MUST be set
   so that max rampup rate is the same as for TCP.  BASE_HISTORY SHOULD
   be 2; it MUST be no less than 2 and SHOULD NOT be more than 10.
   NOISE_FILTER SHOULD be 1; it MAY be tuned so that it is at least 1
   and no more than cwnd/2.  ALLOWED_INCREASE SHOULD BE 1 packet; it
   MUST be at least 1 packet and SHOULD NOT be more than 3 packets.
   TETHER SHOULD be 1.5; it MUST be greater than 1.  RANDONMESS_AMOUNT

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   SHOULD be 0; it MUST be between 0 and 0.1 inclusively.

6.  Security Considerations

   A network on the path might choose to cause higher delay measurements
   than the real queuing delay so that LEDBAT backs off even when
   there's no congestion present.  Shaping of traffic into an
   artificially narrow bottleneck can't be counteracted, but faking
   timestamp field can and SHOULD.  A protocol using the LEDBAT
   congestion control SHOULD authenticate the timestamp and delay
   fields, preferably as part of authenticating most of the rest of the
   packet, with the exception of volatile header fields.  The choice of
   the authentication mechanism that resists man-in-the-middle attacks
   is outside of scope of this document.

7.  Normative References

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", BCP 14, RFC 2119, March 1997.

Author's Address

   Stanislav Shalunov
   BitTorrent Inc
   612 Howard St, Suite 400
   San Francisco, CA  94105

   Email: shalunov@bittorrent.com
   URI:   http://shlang.com

Shalunov               Expires September 23, 2010              [Page 14]