Internet Engineering Task Force                       Hari Balakrishnan
INTERNET DRAFT                                                  MIT LCS
Document: draft-ietf-ecm-cm-00.txt                    Srinivasan Seshan
                                                             July, 2000
                                                  Expires: January 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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1.      Abstract

   This document describes the Congestion Manager (CM), an end-system
   module that (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
   control, and (ii) allows applications to easily adapt to network
   congestion. This CM framework 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.  The
   receiving application must provide feedback to the sending
   application about received packets and losses, and the latter uses
   the CM API to update CM state.  This document does not address
   networks with reservations or service discrimination.

2.      Conventions used in this document:
   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   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 port numbers.

        Identical to STREAM.

        A group of 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.  Streams
        that experience identical congestion behavior in the Internet
        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.

        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

        A CM state variable that modulates the amount of outstanding
        data between sender and receiver.

        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.

        The size of the sender's congestion window at the beginning of
        a macroflow.

           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.

3.      Introduction

   The CM is an end-system module that enables an ensemble of multiple
   concurrent streams to perform proper 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.  All
   data transmissions MUST be done with the explicit consent of the CM
   via this API to ensure proper congestion behavior.

   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                  |-->|   |   |              |
     |-----------------------------------|   |   |   |--------------|

                                   Figure 1

   The key components of the CM framework are (i) the API, (ii) the
   congestion controller, (iii) the scheduler.  The API is (in part)
   motivated by the ideas 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

   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 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 use ALF to dynamically adapt their content based on
   prevailing network conditions.

   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.  A stream wishing to send data in this style
   MUST call cm_request(i32 cm_streamid).  After some time, depending on
   the rate, the CM invokes 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.  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 exports 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.  In response, the
   stream MUST adapt its packet size or change its timer interval to
   conform to (not exceed) the allowed rate.  Of course, it may choose
   not to use all of this rate.

   To avoid unnecessary cmapp_update() callbacks that the application
   will only ignore, the stream can use the cm_thresh(float
   rate_downthresh, float rate_upthresh, float rtt_downthresh, float
   rtt_upthresh) function at any stage in its execution.  In response,
   the CM will 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.

   An application can query the current CM state by using cm_query(i32
   cm_streamid, u64* rate, u32* srtt, u32* rttdev).  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 such a 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_PERSISTENT indicates that the application believes
   congestion to be severe, e.g., a TCP that has experienced a
   timeout.  A value of CM_TRANSIENT indicates that the application
   believes that the congestion is not severe, e.g., a TCP loss
   detected using duplicate (selective) acknowledgements or other
   data-driven techniques.  A value of CM_ECN indicates that the
   receiver echoed an explicit congestion notification message.
   Finally, a value of CM_NOLOSS indicates that no congestion-related
   loss has occurred.

   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.  If a stream
   does not transmit any data upon a cmapp_send() callback invocation,
   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 should be robust to applications forgetting to invoke
   cm_notify(stream_info, 0) correctly.

   4.4 Querying

   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,
   and rttdev.

   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; i.e., all streams to the same destination are
   aggregated to a single macroflow by default.  The cm_getmacroflow()
   and cm_setmacroflow() calls can then be used to change this as

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
   separately-developed schedulers.

   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.

   5.2 Scheduler

   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.

6.      Examples

   6.1 Example applications

   The following describes the possible use of the CM API by an
   asynchronous application (an implementation of a TCP sender) and a
   synchronous application (an audio server).  More details of these
   applications and CM implementation optimizations for efficient
   operation are described in [Andersen00].  We emphasize that the
   protocols in this section are examples and suggestions for
   implementation, rather than requirements of any conformant

   6.1.1 TCP

   A TCP MUST 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,
     CM_NOLOSS, rtt).

     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_TRANSIENT, 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,
     CM_NOLOSS, rtt).

     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_NOLOSS, rtt). CM_NOLOSS is used
     since the loss period has already been reported. TCP also
     enqueues a retransmission of the lost segment and calls

   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_PERSISTENT, 0) to signify the occurrence of
   persistent congestion to the CM.  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.

   To use the CM, the application MUST incorporate feedback from the
   receiver. In this 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 CM changing
   its estimates and calling cmapp_update() of the streams of the

   6.3 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_PERSISTENT and to cwnd/2
     (with a minimum of 1 MTU) if the loss_mode is CM_TRANSIENT or
     CM_ECN.  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

   6.4 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
     robin fashion.

   - 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.  The more dangerous form of attack is giving 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.

8.      References

   [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.

   [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
      1999. (Experimental.)

   [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,
      December 1998.

   [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.)

9.      Acknowledgments

   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 and patience, and Sally Floyd,
   Mark Handley, and Steven McCanne for useful feedback on the CM

10.     Authors' addresses

   Hari Balakrishnan
   Laboratory for Computer Science
   545 Technology Square
   Massachusetts Institute of Technology
   Cambridge, MA 02139

   Srinivasan Seshan
   School of Computer Science
   Carnegie Mellon University
   5000 Forbes Ave.
   Pittsburgh, PA 15213

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