Internet DRAFT - draft-ietf-ecm-cm
Internet Engineering Task Force Hari Balakrishnan
INTERNET DRAFT MIT LCS
Document: draft-ietf-ecm-cm-04.txt Srinivasan Seshan
Expires: November 2001
The Congestion Manager
Status of this Memo
This document is an Internet-Draft and is in full conformance with
all provisions of Section 10 of RFC-2026 [Bradner96].
Internet-Drafts are working documents of the Internet Engineering
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This document describes the Congestion Manager (CM), an end-system
(i) Enables an ensemble of multiple concurrent streams from a
sender destined to the same receiver and sharing the same
congestion properties to perform proper congestion avoidance and
(ii) Allows applications to easily adapt to network congestion.
The framework described in this document integrates congestion
management across all applications and transport protocols. The CM
maintains congestion parameters (available aggregate and per-stream
bandwidth, per-receiver round-trip times, etc.) and exports an API
that enables applications to learn about network characteristics,
pass information to the CM, share congestion information with each
other, and schedule data transmissions. This document focuses on
applications and transport protocols with their own independent
per-byte or per-packet sequence number information, and does not
require modifications to the receiver protocol stack. However, the
receiving application must provide feedback to the sending
application about received packets and losses, and the latter is
expected to use the CM API to update CM state. This document does
not address networks with reservations or service differentiation.
2. Conventions used in this document:
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in
this document are to be interpreted as described in RFC-2119
A group of packets that all share the same source and
destination IP address, IP type-of-service, transport
protocol, and source and destination transport-layer port
A group of CM-enabled streams that all use the same congestion
management and scheduling algorithms, and share congestion
state information. Currently, streams destined to different
receivers belong to different macroflows. Streams destined to
the same receiver MAY belong to different macroflows. When
the Congestion Manager is in use, streams that experience
identical congestion behavior and use the same congestion
control algorithm SHOULD belong to the same macroflow.
Any software module that uses the CM. This includes
user-level applications such as Web servers or audio/video
servers, as well as in-kernel protocols such as TCP [Postel81]
that use the CM for congestion control.
An application that only transmits when allowed by the CM and
accurately accounts for all data that it has sent to the
receiver by informing the CM using the CM API.
PATH MAXIMUM TRANSMISSION UNIT (PMTU)
The size of the largest packet that the sender can transmit
without it being fragmented en route to the receiver. It
includes the sizes of all headers and data except the IP
CONGESTION WINDOW (cwnd)
A CM state variable that modulates the amount of outstanding
data between sender and receiver.
OUTSTANDING WINDOW (ownd)
The number of bytes that has been transmitted by the source,
but not known to have been either received by the destination
or lost in the network.
INITIAL WINDOW (IW)
The size of the sender's congestion window at the beginning of
DATA TYPE SYNTAX
We use "u64" for unsigned 64-bit, "u32" for unsigned 32-
bit, "u16" for unsigned 16-bit, "u8" for unsigned 8-bit, "i32" for
signed 32-bit, "i16" for signed 16-bit quantities, "float" for IEEE
floating point values. The type "void" is used to indicate that no
return value is expected from a call. Pointers are referred to
using "*" syntax, following C language convention.
We emphasize that all the API functions described in this
document are "abstract" calls and that conformant CM
implementations may differ in specific implementation details.
The CM is an end-system module that enables an ensemble of multiple
concurrent streams to perform stable congestion avoidance and
control, and allows applications to easily adapt their
transmissions to prevailing network conditions. It integrates
congestion management across all applications and transport
protocols. It maintains congestion parameters (available aggregate
and per-stream bandwidth, per-receiver round-trip times, etc.) and
exports an API that enables applications to learn about network
characteristics, pass information to the CM, share congestion
information with each other, and schedule data transmissions. When
the CM is used, all data transmissions subject to the CM must be
done with the explicit consent of the CM via this API to ensure
proper congestion behavior.
Systems MAY choose to use CM, and if so they MUST follow this
This document focuses on applications and networks where the
following conditions hold:
1. Applications are well-behaved with their own independent
per-byte or per-packet sequence number information, and use the
CM API to update internal state in the CM.
2. Networks are best-effort without service discrimination or
reservations. In particular, it does not address situations
where different streams between the same pair of hosts traverse
paths with differing characteristics.
The Congestion Manager framework can be extended to support
applications that do not provide their own feedback and to
differentially-served networks. These extensions will be addressed
in later documents.
The CM is motivated by two main goals:
(i) Enable efficient multiplexing. Increasingly, the trend on the
Internet is for unicast data senders (e.g., Web servers) to
transmit heterogeneous types of data to receivers, ranging from
unreliable real-time streaming content to reliable Web pages and
applets. As a result, many logically different streams share the
same path between sender and receiver. For the Internet to remain
stable, each of these streams must incorporate control protocols
that safely probe for spare bandwidth and react to
congestion. Unfortunately, these concurrent streams typically compete
with each other for network resources, rather than share them
effectively. Furthermore, they do not learn from each other about
the state of the network. Even if they each independently implement
congestion control (e.g., a group of TCP connections each
implementing the algorithms in [Jacobson88, Allman99]), the
ensemble of streams tends to be more aggressive in the face of
congestion than a single TCP connection implementing standard TCP
congestion control and avoidance [Balakrishnan98].
(ii) Enable application adaptation to congestion. Increasingly
popular real-time streaming applications run over UDP using their
own user-level transport protocols for good application
performance, but in most cases today do not adapt or react properly
to network congestion. By implementing a stable control algorithm
and exposing an adaptation API, the CM enables easy application
adaptation to congestion. Applications adapt the data they
transmit to the current network conditions.
The CM framework builds on recent work on TCP control block sharing
[Touch97], integrated TCP congestion control (TCP-Int)
[Balakrishnan98] and TCP sessions [Padmanabhan98]. [Touch97]
advocates the sharing of some of the state in the TCP control block
to improve transient transport performance and describes sharing
across an ensemble of TCP connections. [Balakrishnan98],
[Padmanabhan98], and [Eggert00] describe several experiments that
quantify the benefits of sharing congestion state, including
improved stability in the face of congestion and better loss
recovery. Integrating loss recovery across concurrent connections
significantly improves performance because losses on one connection
can be detected by noticing that later data sent on another
connection has been received and acknowledged. The CM framework
extends these ideas in two significant ways: (i) it extends
congestion management to non-TCP streams, which are becoming
increasingly common and often do not implement proper congestion
management, and (ii) it provides an API for applications to adapt
their transmissions to current network conditions. For an extended
discussion of the motivation for the CM, its architecture, API,
and algorithms, see [Balakrishnan99]; for a description of an
implementation and performance results, see [Andersen00].
The resulting end-host protocol architecture at the sender is shown
in Figure 1. The CM helps achieve network stability by
implementing stable congestion avoidance and control algorithms
that are "TCP-friendly" [Mahdavi98] based on algorithms described
in [Allman99]. However, it does not attempt to enforce proper
congestion behavior for all applications (but it does not preclude
a policer on the host that performs this task). Note that while
the policer at the end-host can use CM, the network has to be
protected against compromises to the CM and the policer at the end
hosts, a task that requires router machinery [Floyd99a]. We do not
address this issue further in this document.
|--------| |--------| |--------| |--------| |--------------|
| HTTP | | FTP | | RTP 1 | | RTP 2 | | |
|--------| |--------| |--------| |--------| | |
| | | ^ | ^ | |
| | | | | | | Scheduler |
| | | | | | |---| | |
| | | |-------|--+->| | | |
| | | | | |<--| |
v v v v | | |--------------|
|--------| |--------| |-------------| | | ^
| TCP 1 | | TCP 2 | | UDP 1 | | A | |
|--------| |--------| |-------------| | | |
^ | ^ | | | | |--------------|
| | | | | | P |-->| |
| | | | | | | | |
|---|------+---|--------------|------->| | | Congestion |
| | | | I | | |
v v v | | | Controller |
|-----------------------------------| | | | |
| IP |-->| | | |
|-----------------------------------| | | |--------------|
The key components of the CM framework are (i) the API, (ii) the
congestion controller, and (iii) the scheduler. The API is (in
part) motivated by the requirements of application-level framing
(ALF) [Clark90], and is described in Section 4. The CM internals
(Section 5) include a congestion controller (Section 5.1) and a
scheduler to orchestrate data transmissions between concurrent
streams in a macroflow (Section 5.2). The congestion controller
adjusts the aggregate transmission rate between sender and receiver
based on its estimate of congestion in the network. It obtains
feedback about its past transmissions from applications themselves
via the API. The scheduler apportions available bandwidth amongst
the different streams within each macroflow and notifies
applications when they are permitted to send data. This document
focuses on well-behaved applications; a future one will describe
the sender-receiver protocol and header formats that will handle
applications that do not incorporate their own feedback to the CM.
4. CM API
By convention, the IETF does not treat Application Programming
Interfaces as standards track. However, it is considered important
to have the CM API and CM algorithm requirements in one coherent
document. The following section on the CM API uses the terms MUST,
SHOULD, etc. but the terms are meant to apply within the context of
an implementation of the CM API. The section does not apply to
congestion control implementations in general, only to those
implementations offering the CM API.
Using the CM API, streams can determine their share of the available
bandwidth, request and have their data transmissions scheduled,
inform the CM about successful transmissions, and be informed when
the CM's estimate of path bandwidth changes. Thus, the CM frees
applications from having to maintain information about the state of
congestion and available bandwidth along any path.
The function prototypes below follow standard C language
convention. We emphasize that these API functions are abstract
calls and conformant CM implementations may differ in specific
details, as long as equivalent functionality is provided.
When a new stream is created by an application, it passes some
information to the CM via the cm_open(stream_info) API call.
Currently, stream_info consists of the following information: (i)
the source IP address, (ii) the source port, (iii) the destination
IP address, (iv) the destination port, and (v) the IP protocol
4.1 State maintenance
1. Open: All applications MUST call cm_open(stream_info) before
using the CM API. This returns a handle, cm_streamid, for the
application to use for all further CM API invocations for that
stream. If the returned cm_streamid is -1, then the cm_open()
failed and that stream cannot use the CM.
All other calls to the CM for a stream use the cm_streamid
returned from the cm_open() call.
2. Close: When a stream terminates, the application SHOULD invoke
cm_close(cm_streamid) to inform the CM about the termination
of the stream.
3. Packet size: cm_mtu(cm_streamid) returns the estimated PMTU of
the path between sender and receiver. Internally, this
information SHOULD be obtained via path MTU discovery
[Mogul90]. It MAY be statically configured in the absence of
such a mechanism.
4.2 Data transmission
The CM accommodates two types of adaptive senders, enabling
applications to dynamically adapt their content based on
prevailing network conditions, and supporting ALF-based
1. Callback-based transmission. The callback-based transmission API
puts the stream in firm control of deciding what to transmit at
each point in time. To achieve this, the CM does not buffer any
data; instead, it allows streams the opportunity to adapt to
unexpected network changes at the last possible instant. Thus,
this enables streams to "pull out" and repacketize data upon
learning about any rate change, which is hard to do once the data
has been buffered. The CM must implement a cm_request(i32
cm_streamid) call for streams wishing to send data in this style.
After some time, depending on the rate, the CM MUST
invoke a callback using cmapp_send(), which is
a grant for the stream to send up to PMTU bytes. The
callback-style API is the recommended choice for ALF-based streams.
Note that cm_request() does not take the number of bytes or
MTU-sized units as an argument; each call to cm_request() is an
implicit request for sending up to PMTU bytes. The CM MAY provide
an alternate interface, cm_request(int k). The cmapp_send callback
for this request is granted the right to send up to k PMTU sized
segments. Section 4.3 discusses the time duration for which the
transmission grant is valid, while Section 5.2 describes how these
requests are scheduled and callbacks made.
2. Synchronous-style. The above callback-based API accommodates a
class of ALF streams that are "asynchronous." Asynchronous
transmitters do not transmit based on a periodic clock, but do so
triggered by asynchronous events like file reads or captured
frames. On the other hand, there are many streams that are
"synchronous" transmitters, which transmit periodically based on
their own internal timers (e.g., an audio senders that sends at a
constant sampling rate). While CM callbacks could be configured to
periodically interrupt such transmitters, the transmit loop of such
applications is less affected if they retain their original
timer-based loop. In addition, it complicates the CM API to have a
stream express the periodicity and granularity of its callbacks.
Thus, the CM MUST export an API that allows such streams to be informed
of changes in rates using the cmapp_update(u64 newrate, u32 srtt,
u32 rttdev) callback function, where newrate is the new rate in
bits per second for this stream, srtt is the current smoothed round
trip time estimate in microseconds, and rttdev is the smoothed
linear deviation in the round-trip time estimate calculated using
the same algorithm as in TCP [Paxson00]. The newrate value reports
an instantaneous rate calculated, for example, by taking the ratio
of cwnd and srtt, and dividing by the fraction of that ratio
allocated to the stream. In response, the stream MUST adapt its
packet size or change its timer interval to conform to (i.e., not
exceed) the allowed rate. Of course, it may choose not to use all
of this rate. Note that the CM is not on the data path of the
To avoid unnecessary cmapp_update() callbacks that the application
will only ignore, the CM MUST provide a cm_thresh(float
rate_downthresh, float rate_upthresh, float rtt_downthresh, float
rtt_upthresh) function that a stream can use at any stage in its execution.
In response, the CM SHOULD invoke the callback only when the rate decreases
to less than (rate_downthresh * lastrate) or increases to more than
(rate_upthresh * lastrate), where lastrate is the rate last
notified to the stream, or when the round-trip time changes
correspondingly by the requisite thresholds. This information is
used as a hint by the CM, in the sense the cmapp_update() can be
called even if these conditions are not met.
The CM MUST implement a cm_query(i32 cm_streamid, u64* rate,
u32* srtt, u32* rttdev) to allow an application to query
the current CM state. This sets the rate variable to
the current rate estimate in bits per second, the
srtt variable to the current smoothed round-trip time estimate in
microseconds, and rttdev to the mean linear deviation. If the CM
does not have valid estimates for the macroflow, it fills in
negative values for the rate, srtt, and rttdev.
Note that a stream can use more than one of the above transmission
APIs at the same time. In particular, the knowledge of sustainable
rate is useful for asynchronous streams as well as synchronous
ones; e.g., an asynchronous Web server disseminating images using
TCP may use cmapp_send() to schedule its transmissions and
cmapp_update() to decide whether to send a low-resolution or
high-resolution image. A TCP implementation using the CM is
described in Section 6.1.1, where the benefit of the cm_request()
callback API for TCP will become apparent.
The reader will notice that the basic CM API does not provide an
interface for buffered congestion-controlled transmissions. This
is intentional, since this transmission mode can be implemented
using the callback-based primitive. Section 6.1.2 describes how
congestion-controlled UDP sockets may be implemented using the CM
4.3 Application notification
When a stream receives feedback from receivers, it MUST use
cm_update(i32 cm_streamid, u32 nrecd, u32 nlost, u8 lossmode, i32
rtt) to inform the CM about events such as congestion losses,
successful receptions, type of loss (timeout event, Explicit
Congestion Notification [Ramakrishnan98], etc.) and round-trip time
samples. The nrecd parameter indicates how many bytes were
successfully received by the receiver since the last cm_update
call, while the nrecd parameter identifies how many bytes were
received were lost during the same time period. The rtt value
indicates the round-trip time measured during the transmission of
these bytes. The rtt value must be set to -1 if no valid
round-trip sample was obtained by the application. The lossmode
parameter provides an indicator of how a loss was detected. A
value of CM_NO_FEEDBACK indicates that the application has received
no feedback for all its outstanding data, and is reporting this to
the CM. For example, a TCP that has experienced a timeout would
use this parameter to inform the CM of this. A value of
CM_LOSS_FEEDBACK indicates that the application has experienced
some loss, which it believes to be due to congestion, but not all
outstanding data has been lost. For example, a TCP segment loss
detected using duplicate (selective) acknowledgements or other
data-driven techniques fits this category. A value of
CM_EXPLICIT_CONGESTION indicates that the receiver echoed an
explicit congestion notification message. Finally, a value of
CM_NO_CONGESTION indicates that no congestion-related loss has
occurred. The lossmode parameter MUST be reported as a bit-vector
where the bits correspond to CM_NO_FEEDBACK, CM_LOSS_FEEDBACK,
CM_EXPLICIT_CONGESTION, and CM_NO_CONGESTION. Note that over links
(paths) that experience losses for reasons other than congestion,
an application SHOULD inform the CM of losses, with the
CM_NO_CONGESTION field set.
cm_notify(i32 cm_streamid, u32 nsent) MUST be called when data is
transmitted from the host (e.g., in the IP output routine) to
inform the CM that nsent bytes were just transmitted on a given
stream. This allows the CM to update its estimate of the number of
outstanding bytes for the macroflow and for the stream.
A cmapp_send() grant from the CM to an application is valid only
for an expiration time, equal to the larger of the round-trip time
and an implementation-dependent threshold communicated as an
argument to the cmapp_send() callback function. The application
MUST NOT send data based on this callback after this time has
expired. Furthermore, if the application decides not to send data
after receiving this callback, it SHOULD call
cm_notify(stream_info, 0) to allow the CM to permit other streams
in the macroflow to transmit data. The CM congestion controller
MUST be robust to applications forgetting to invoke
cm_notify(stream_info, 0) correctly, or applications that crash or
disappear after having made a cm_request() call.
If applications wish to learn about per-stream available bandwidth
and round-trip time, they can use the CM's cm_query(i32
cm_streamid, i64* rate, i32* srtt, i32* rttdev) call, which fills
in the desired quantities. If the CM does not have valid estimates
for the macroflow, it fills in negative values for the rate, srtt,
4.5 Sharing granularity
One of the decisions the CM needs to make is the granularity at
which a macroflow is constructed, by deciding which streams belong
to the same macroflow and share congestion information. The API
provides two functions that allow applications to decide which of
their streams ought to belong to the same macroflow.
cm_getmacroflow(i32 cm_streamid) returns a unique i32 macroflow
identifier. cm_setmacroflow(i32 cm_macroflowid, i32 cm_streamid)
sets the macroflow of the stream cm_streamid to cm_macroflowid. If the
cm_macroflowid that is passed to cm_setmacroflow() is -1, then a
new macroflow is constructed and this is returned to the caller.
Each call to cm_setmacroflow() overrides the previous macroflow
association for the stream, should one exist.
The default suggested aggregation method is to aggregate by
destination IP address; i.e., all streams to the same destination
address are aggregated to a single macroflow by default. The
cm_getmacroflow() and cm_setmacroflow() calls can then be used to
change this as needed. We do note that there are some cases where
this may not be optimal, even over best-effort networks. For
example, when a group of receivers are behind a NAT device, the
sender will see them all as one address. If the hosts behind the
NAT are in fact connected over different bottleneck links, some of
those hosts could see worse performance than before. It is
possible to detect such hosts when using delay and loss estimates,
although the specific mechanisms for doing so are beyond the scope
of this document.
The objective of this interface is to set up sharing of groups not
sharing policy of relative weights of streams in a macroflow. The
latter requires the scheduler to provide an interface to set
sharing policy. However, because we want to support many different
schedulers (each of which may need different information to set
policy), we do not specify a complete API to the scheduler (but see
Section 5.2). A later guideline document is expected to describe a
few simple schedulers (e.g., weighted round-robin, hierarchical
scheduling) and the API they export to provide relative
5. CM internals
This section describes the internal components of the CM. It
includes a Congestion Controller and a Scheduler, with
well-defined, abstract interfaces exported by them.
5.1 Congestion controller
Associated with each macroflow is a congestion control algorithm;
the collection of all these algorithms comprises the congestion
controller of the CM. The control algorithm decides when and how
much data can be transmitted by a macroflow. It uses application
notifications (Section 4.3) from concurrent streams on the same
macroflow to build up information about the congestion state of the
network path used by the macroflow.
The congestion controller MUST implement a "TCP-friendly"
[Mahdavi98] congestion control algorithm. Several macroflows MAY
(and indeed, often will) use the same congestion control algorithm
but each macroflow maintains state about the network used by its
The congestion control module MUST implement the following abstract
interfaces. We emphasize that these are not directly visible to
applications; they are within the context of a macroflow, and are
different from the CM API functions of Section 4.
- void query(u64 *rate, u32 *srtt, u32 *rttdev): This function
returns the estimated rate (in bits per second) and smoothed
round trip time (in microseconds) for the macroflow.
- void notify(u32 nsent): This function MUST be used to notify the
congestion control module whenever data is sent by an
application. The nsent parameter indicates the number of bytes
just sent by the application.
- void update(u32 nsent, u32 nrecd, u32 rtt, u32 lossmode): This
function is called whenever any of the CM streams associated with
a macroflow identifies that data has reached the receiver or has
been lost en route. The nrecd parameter indicates the number of
bytes that have just arrived at the receiver. The nsent
parameter is the sum of the number of bytes just received and the
number of bytes identified as lost en route. The rtt parameter is
the estimated round trip time in microseconds during the
transfer. The lossmode parameter provides an indicator of how a
loss was detected (section 4.3).
Although these interfaces are not visible to applications, the
congestion controller MUST implement these abstract interfaces to
provide for modular inter-operability with different
The congestion control module MUST also call the associated
scheduler's schedule function (section 5.2) when it believes that
the current congestion state allows an MTU-sized packet to be sent.
While it is the responsibility of the congestion control module to
determine when and how much data can be transmitted, it is the
responsibility of a macroflow's scheduler module to determine which
of the streams should get the opportunity to transmit data.
The Scheduler MUST implement the following interfaces:
- void schedule(u32 num_bytes): When the congestion control module
determines that data can be sent, the schedule() routine MUST be
called with no more than the number of bytes that can be sent.
In turn, the scheduler MAY call the cmapp_send() function that CM
applications must provide.
- float query_share(i32 cm_streamid): This call returns the
described stream's share of the total bandwidth available to the
macroflow. This call combined with the query call of the
congestion controller provides the information to satisfy an
application's cm_query() request.
- void notify(i32 cm_streamid, u32 nsent): This interface is used
to notify the scheduler module whenever data is sent by a CM
application. The nsent parameter indicates the number of bytes
just sent by the application.
The Scheduler MAY implement many additional interfaces. As
experience with CM schedulers increases, future documents may
make additions and/or changes to some parts of the scheduler
6.1 Example applications
This section describes three possible uses of the CM API by
applications. We describe two asynchronous applications---an
implementation of a TCP sender and an implementation of
congestion-controlled UDP sockets, and a synchronous
application---a streaming audio server. More details of these
applications and CM implementation optimizations for efficient
operation are described in [Andersen00].
All applications that use the CM MUST incorporate feedback from the
receiver. For example, it must periodically (typically once or
twice per round trip time) determine how many of its packets
arrived at the receiver. When the source gets this feedback, it
MUST use cm_update() to inform the CM of this new information.
This results in the CM updating ownd and may result in the CM
changing its estimates and calling cmapp_update() of the streams of
The protocols in this section are examples and suggestions for
implementation, rather than requirements for any conformant
A TCP implementation that uses CM should use the cmapp_send()
callback API. TCP only identifies which data it should send upon
the arrival of an acknowledgement or expiration of a timer. As a
result, it requires tight control over when and if new data or
retransmissions are sent.
When TCP either connects to or accepts a connection from another
host, it performs a cm_open() call to associate the TCP connection
with a cm_streamid.
Once a connection is established, the CM is used to control the
transmission of outgoing data. The CM eliminates the need for
tracking and reacting to congestion in TCP, because the CM and its
transmission API ensure proper congestion behavior. Loss recovery
is still performed by TCP based on fast retransmissions and
recovery as well as timeouts. In addition, TCP is also modified to
have its own outstanding window (tcp_ownd) estimate. Whenever data
segments are sent from its cmapp_send() callback, TCP updates its
tcp_ownd value. The ownd variable is also updated after each
cm_update() call. TCP also maintains a count of the number of
outstanding segments (pkt_cnt). At any time, TCP can calculate the
average packet size (avg_pkt_size) as tcp_ownd/pkt_cnt. The
avg_pkt_size is used by TCP to help estimate the amount of
outstanding data. Note that this is not needed if the SACK option
is used on the connection, since this information is explicitly
The TCP output routines are modified as follows:
1. All congestion window (cwnd) checks are removed.
2. When application data is available. The TCP output routines
perform all non-congestion checks (Nagle algorithm,
receiver-advertised window check, etc). If these checks pass,
the output routine queues the data and calls cm_request() for the
3. If incoming data or timers result in a loss being detected,
the retransmission is also placed in a queue and cm_request() is
called for the stream.
4. The cmapp_send() callback for TCP is set to an output
routine. If any retransmission is enqueued, the routine outputs
the retransmission. Otherwise, the routine outputs as much new
data as the TCP connection state allows. However, the
cmapp_send() never sends more than a single segment per call.
This routine arranges for the other output computations to be
done, such as header and options computations.
The IP output routine on the host calls cm_notify() when the
packets are actually sent out. Because it does not know which
cm_streamid is responsible for the packet, cm_notify() takes the
stream_info as argument (see Section 4 for what the stream_info
should contain). Because cm_notify() reports the IP payload size,
TCP keeps track of the total header size and incorporates these
The TCP input routines are modified as follows:
1. RTT estimation is done as normal using either timestamps or
Karn's algorithm. Any rtt estimate that is generated is passed
to CM via the cm_update call.
2. All cwnd and slow start threshold (ssthresh) updates are
3. Upon the arrival of an ack for new data, TCP computes the
value of in_flight (the amount of data in flight) as
snd_max-ack-1 (i.e. MAX Sequence Sent - Current Ack - 1). TCP
then calls cm_update(streamid, tcp_ownd - in_flight, 0,
4. Upon the arrival of a duplicate acknowledgement, TCP must
check its dupack count (dup_acks) to determine its action. If
dup_acks < 3, the TCP does nothing. If dup_acks == 3, TCP
assumes that a packet was lost and that at least 3 packets
arrived to generate these duplicate acks. Therefore, it calls
cm_update(streamid, 4 * avg_pkt_size, 3 * avg_pkt_size,
CM_LOSS_FEEDBACK, rtt). The average packet size is used since the
acknowledgements do not indicate exactly how much data has
reached the other end. Most TCP implementations interpret a
duplicate ACK as an indication that a full MSS has reached its
destination. Once a new ACK is received, these TCP sender
implementations may resynchronize with TCP receiver. The CM API
does not provide a mechanism for TCP to pass information from
this resynchronization. Therefore, TCP can only infer the
arrival of an avg_pkt_size amount of data from each duplicate
ack. TCP also enqueues a retransmission of the lost segment and
calls cm_request(). If dup_acks > 3, TCP assumes that a packet
has reached the other end and caused this ack to be sent. As a
result, it calls cm_update(streamid, avg_pkt_size, avg_pkt_size,
5. Upon the arrival of a partial acknowledgment (one that does
not exceed the highest segment transmitted at the time the loss
occurred, as defined in [Floyd99b]), TCP assumes that a packet
was lost and that the retransmitted packet has reached the
recipient. Therefore, it calls cm_update(streamid, 2 *
avg_pkt_size, avg_pkt_size, CM_NO_CONGESTION,
rtt). CM_NO_CONGESTION is used since the loss period has already
been reported. TCP also enqueues a retransmission of the lost
segment and calls cm_request().
When the TCP retransmission timer expires, the sender identifies
that a segment has been lost and calls cm_update(streamid,
avg_pkt_size, 0, CM_NO_FEEDBACK, 0) to signify that no feedback has
been received from the receiver and that one segment is sure to
have "left the pipe." TCP also enqueues a retransmission of the
lost segment and calls cm_request().
6.1.2 Congestion-controlled UDP
Congestion-controlled UDP is a useful CM application, which we
describe in the context of Berkeley sockets [Stevens94]. They
provide the same functionality as standard Berkeley UDP sockets,
but instead of immediately sending the data from the kernel packet
queue to lower layers for transmission, the buffered socket
implementation makes calls to the API exported by the CM inside the
kernel and gets callbacks from the CM. When a CM UDP socket is
created, it is bound to a particular stream. Later, when data is
added to the packet queue, cm_request() is called on the stream
associated with the socket. When the CM schedules this stream for
transmission, it calls udp_ccappsend() in the UDP module. This
function transmits one MTU from the packet queue, and schedules the
transmission of any remaining packets. The in-kernel
implementation of the CM UDP API should not require any additional
data copies and should support all standard UDP options. Modifying
existing applications to use congestion-controlled UDP requires the
implementation of a new socket option on the socket. To work
correctly, the sender must obtain feedback about congestion. This
can be done in at least two ways: (i) the UDP receiver application
can provide feedback to the sender application, which will inform
the CM of network conditions using cm_update(); (ii) the UDP
receiver implementation can provide feedback to the sending UDP.
Note that this latter alternative requires changes to the
receiver's network stack and the sender UDP cannot assume that all
receivers support this option without explicit negotiation.
6.1.3 Audio server
A typical audio application often has access to the sample in a
multitude of data rates and qualities. The objective of the
application is then to deliver the highest possible quality of
audio (typically the highest data rate) its clients. The selection
of which version of audio to transmit should be based on the
current congestion state of the network. In addition, the source
will want audio delivered to its users at a consistent sampling
rate. As a result, it must send data a regular rate, minimizing
delaying transmissions and reducing buffering before playback. To
meet these requirements, this application can use the synchronous
sender API (Section 4.2).
When the source first starts, it uses the cm_query() call to get an
initial estimate of network bandwidth and delay. If some other
streams on that macroflow have already been active, then it gets an
initial estimate that is valid; otherwise, it gets negative values,
which it ignores. It then chooses an encoding that does not exceed
these estimates (or, in the case of an invalid estimate, uses
application-specific initial values) and begins transmitting
data. The application also implements the cmapp_update() callback.
When the CM determines that network characteristics have changed,
it calls the application's cmapp_update() function and passes it a
new rate and round-trip time estimate. The application must change
its choice of audio encoding to ensure that it does not exceed
these new estimates.
6.2 Example congestion control module
To illustrate the responsibilities of a congestion control module,
the following describes some of the actions of a simple TCP-like
congestion control module that implements Additive Increase
Multiplicative Decrease congestion control (AIMD_CC):
- query(): AIMD_CC returns the current congestion window (cwnd)
divided by the smoothed rtt (srtt) as its bandwidth estimate. It
returns the smoothed rtt estimate as srtt.
- notify(): AIMD_CC adds the number of bytes sent to its
outstanding data window (ownd).
- update(): AIMD_CC subtracts nsent from ownd. If the value of rtt
is non-zero, AIMD_CC updates srtt using the TCP srtt calculation.
If the update indicates that data has been lost, AIMD_CC sets
cwnd to 1 MTU if the loss_mode is CM_NO_FEEDBACK and to cwnd/2
(with a minimum of 1 MTU) if the loss_mode is CM_LOSS_FEEDBACK or
CM_EXPLICIT_CONGESTION. AIMD_CC also sets its internal ssthresh
variable to cwnd/2. If no loss had occurred, AIMD_CC mimics TCP
slow start and linear growth modes. It increments cwnd by nsent
when cwnd < ssthresh (bounded by a maximum of ssthresh-cwnd) and
by nsent * MTU/cwnd when cwnd > ssthresh.
- When cwnd or ownd are updated and indicate that at least one MTU
may be transmitted, AIMD_CC calls the CM to schedule a
6.3 Example Scheduler Module
To clarify the responsibilities of a scheduler module, the
following describes some of the actions of a simple round robin
scheduler module (RR_sched):
- schedule(): RR_sched schedules as many streams as possible in round
- query_share(): RR_sched returns 1/(number of streams in macroflow).
- notify(): RR_sched does nothing. Round robin scheduling is not
affected by the amount of data sent.
7. Security considerations
The CM provides many of the same services that the congestion
control in TCP provides. As such, it is vulnerable to many of the
same security problems. For example, incorrect reports of losses
and transmissions will give the CM an inaccurate picture of the
network's congestion state. By giving CM a high estimate of
congestion, an attacker can degrade the performance observed by
applications. For example, a stream on a host can arbitrarily slow
down any other stream on the same macroflow, a form of denial of
The more dangerous form of attack occurs when an application gives
the CM a low estimate of congestion. This would cause CM to be
overly aggressive and allow data to be sent much more quickly than
sound congestion control policies would allow.
[Touch97] describes a number of the security problems that arise
with congestion information sharing. An additional vulnerability
(not covered by [Touch97])) occurs because applications have access
through the CM API to control shared state that will affect other
applications on the same computer. For instance, a poorly
designed, possibly a compromised, or intentionally malicious UDP
application could misuse cm_update() to cause starvation and/or
too-aggressive behavior of others in the macroflow.
[Allman99] Allman, M. and Paxson, V., TCP Congestion Control,
RFC-2581, April 1999.
[Andersen00] Andersen, D., Bansal, D., Curtis, D., Seshan, S., and
Balakrishnan, H., System Support for Bandwidth Management and
Content Adaptation in Internet Applications, Proc. 4th Symp. on
Operating Systems Design and Implementation, San Diego, CA,
October 2000. Available from
[Balakrishnan98] Balakrishnan, H., Padmanabhan, V., Seshan, S.,
Stemm, M., and Katz, R., "TCP Behavior of a Busy Web Server:
Analysis and Improvements," Proc. IEEE INFOCOM, San Francisco,
CA, March 1998.
[Balakrishnan99] Balakrishnan, H., Rahul, H., and Seshan, S., "An
Integrated Congestion Management Architecture for Internet
Hosts," Proc. ACM SIGCOMM, Cambridge, MA, September 1999.
[Bradner96] Bradner, S., "The Internet Standards Process ---
Revision 3", BCP 9, RFC-2026, October 1996.
[Bradner97] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC-2119, March 1997.
[Clark90] Clark, D. and Tennenhouse, D., "Architectural
Consideration for a New Generation of Protocols", Proc. ACM
SIGCOMM, Philadelphia, PA, September 1990.
[Eggert00] Eggert, L., Heidemann, J., and Touch, J., "Effects of
Ensemble TCP," ACM Computer Comm. Review, January 2000.
[Floyd99a] Floyd, S. and Fall, K.," Promoting the Use of End-to-End
Congestion Control in the Internet," IEEE/ACM Trans. on
Networking, 7(4), August 1999, pp. 458-472.
[Floyd99b] Floyd, S. and Henderson, T., "The NewReno Modification
to TCP's Fast Recovery Algorithm," RFC-2582, April
[Jacobson88] Jacobson, V., "Congestion Avoidance and Control,"
Proc. ACM SIGCOMM, Stanford, CA, August 1988.
[Mahdavi98] Mahdavi, J. and Floyd, S., "The TCP Friendly Website,"
[Mogul90] Mogul, J. and Deering, S., "Path MTU Discovery,"
RFC-1191, November 1990.
[Padmanabhan98] Padmanabhan, V., "Addressing the Challenges of Web
Data Transport," PhD thesis, Univ. of California, Berkeley,
[Paxson00] Paxson. V. and Allman, M., "Computing TCP's
Retransmission Timer," Internet Draft
draft-paxson-tcp-rto-01.txt, April 2000. (Expires October
[Postel81] Postel, J. (ed.), "Transmission Control Protocol,"
RFC-793, September 1981.
[Ramakrishnan98] Ramakrishnan, K. and Floyd, S., "A Proposal to Add
Explicit Congestion Notification (ECN) to IP," RFC-2481.
[Stevens94] Stevens, W., TCP/IP Illustrated, Volume 1.
Addison-Wesley, Reading, MA, 1994.
[Touch97] Touch, J., "TCP Control Block Interdependence," RFC-2140,
April 1997. (Informational.)
We thank David Andersen, Deepak Bansal, and Dorothy Curtis for
their work on the CM design and implementation. We thank Vern
Paxson for his detailed comments, feedback, and patience, and Sally
Floyd, Mark Handley, and Steven McCanne for useful feedback on the
CM architecture. Allison Mankin and Joe Touch provided several
useful comments on previous drafts of this document.
10. Authors' addresses
Laboratory for Computer Science
200 Technology Square
Massachusetts Institute of Technology
Cambridge, MA 02139
School of Computer Science
Carnegie Mellon University
5000 Forbes Ave.
Pittsburgh, PA 15213
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