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Versions: 00                                                            
SIPPING Working Group                                      V. Hilt (Ed.)
Internet-Draft                                  Bell Labs/Alcatel-Lucent
Intended status: Informational                              July 5, 2008
Expires: January 6, 2009

  Design Considerations for Session Initiation Protocol (SIP) Overload

Status of this Memo

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   Overload occurs in Session Initiation Protocol (SIP) networks when
   SIP servers have insufficient resources to handle all SIP messages
   they receive.  Even though the SIP protocol provides a limited
   overload control mechanism through its 503 (Service Unavailable)
   response code, SIP servers are still vulnerable to overload.  This
   document discusses models and design considerations for a SIP
   overload control mechanism.

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Table of Contents

   1.  Introduction . . . . . . . . . . . . . . . . . . . . . . . . .  3
   2.  Implicit vs. Explicit Overload Control . . . . . . . . . . . .  4
   3.  System Model . . . . . . . . . . . . . . . . . . . . . . . . .  5
   4.  Degree of Cooperation  . . . . . . . . . . . . . . . . . . . .  6
     4.1.  Hop-by-Hop . . . . . . . . . . . . . . . . . . . . . . . .  7
     4.2.  End-to-End . . . . . . . . . . . . . . . . . . . . . . . .  8
     4.3.  Local Overload Control . . . . . . . . . . . . . . . . . .  9
   5.  Topologies . . . . . . . . . . . . . . . . . . . . . . . . . .  9
   6.  Type of Overload Control Feedback  . . . . . . . . . . . . . . 11
     6.1.  Rate-based Overload Control  . . . . . . . . . . . . . . . 11
     6.2.  Loss-based Overload Control  . . . . . . . . . . . . . . . 12
     6.3.  Window-based Overload Control  . . . . . . . . . . . . . . 13
     6.4.  On-/Off Overload Control . . . . . . . . . . . . . . . . . 14
   7.  Overload Control Algorithms  . . . . . . . . . . . . . . . . . 14
   8.  Self-Limiting  . . . . . . . . . . . . . . . . . . . . . . . . 15
   9.  Security Considerations  . . . . . . . . . . . . . . . . . . . 15
   10. IANA Considerations  . . . . . . . . . . . . . . . . . . . . . 15
   Appendix A.  Contributors  . . . . . . . . . . . . . . . . . . . . 15
   11. Informative References . . . . . . . . . . . . . . . . . . . . 16
   Author's Address . . . . . . . . . . . . . . . . . . . . . . . . . 16
   Intellectual Property and Copyright Statements . . . . . . . . . . 17

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1.  Introduction

   As with any network element, a Session Initiation Protocol (SIP)
   [RFC3261] server can suffer from overload when the number of SIP
   messages it receives exceeds the number of messages it can process.
   Overload can pose a serious problem for a network of SIP servers.
   During periods of overload, the throughput of a network of SIP
   servers can be significantly degraded.  In fact, overload may lead to
   a situation in which the throughput drops down to a small fraction of
   the original processing capacity.  This is often called congestion

   Overload is said to occur if a SIP server does not have sufficient
   resources to process all incoming SIP messages.  These resources may
   include CPU, memory, network bandwidth, input/output, or disk

   For overload control, we only consider failure cases where SIP
   servers are unable to process all SIP requests due to resource
   constraints.  There are other cases where a SIP server can
   successfully process incoming requests but has to reject them due to
   other failure conditions.  For example, a PSTN gateway that runs out
   of trunk lines but still has plenty of capacity to process SIP
   messages should reject incoming INVITEs using a 488 (Not Acceptable
   Here) response [RFC4412].  Similarly, a SIP registrar that has lost
   connectivity to its registration database but is still capable of
   processing SIP messages should reject REGISTER requests with a 500
   (Server Error) response [RFC3261].  Overload control does not apply
   to these cases and SIP provides appropriate response codes for them.

   The SIP protocol provides a limited mechanism for overload control
   through its 503 (Service Unavailable) response code.  However, this
   mechanism cannot prevent overload of a SIP server and it cannot
   prevent congestion collapse.  In fact, the use of the 503 (Service
   Unavailable) response code may cause traffic to oscillate and to
   shift between SIP servers and thereby worsen an overload condition.
   A detailed discussion of the SIP overload problem, the problems with
   the 503 (Service Unavailable) response code and the requirements for
   a SIP overload control mechanism can be found in

   This document discusses the models, assumptions and design
   considerations for a SIP overload control mechanism.  The document is
   a product of the SIP overload control design team.

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2.  Implicit vs. Explicit Overload Control

   Two fundamental approaches to overload control exist: implicit and
   explicit overload control.

   A key contributor to the SIP congestion collapse
   [I-D.rosenberg-sipping-overload-reqs] is the regenerative behavior of
   overload in the SIP protocol.  Messages that get dropped by a SIP
   server due to overload are retransmitted and increase the offered
   load for the already overloaded server.  This increase in load
   worsens the severity of the overload condition and, in turn, causes
   more messages to be dropped.  The goal of an implicit overload
   control is therefore to change the fundamental mechanisms of the SIP
   protocol such that regenerative behavior of overload is avoided.  In
   the ideal case, overload behavior of SIP would be fully non-
   regenerative, which would lead to a stable operation during overload.
   Even if a fully non-regenerative behavior for SIP is challenging to
   achieve, changes to the SIP retransmission timer mechanisms can help
   to reduce the degree of regeneration during overload.  More work is
   needed to understand the impact of SIP retransmission timers on the
   regenerative overload behavior of SIP.

   For a SIP INVITE transaction to be successful a minimum of three
   messages need to be forwarded by a SIP server, often five or more.
   If a SIP server under overload randomly discards messages without
   evaluating them, the chances that all messages belonging to a
   transaction are passed on will decrease as the load increases.  Thus,
   the number of successful transactions will decrease even if the
   message throughput of a server remains up and the overload behavior
   is fully non-regenerative.  A SIP server might (partially) parse
   incoming messages to determine if it is a new request or a message
   belonging to an existing transaction.  However, after having spend
   resources on parsing a SIP message, discarding this message becomes
   expensive as the resources already spend are lost.  The number of
   successful transactions will therefore decline with an increase in
   load as less and less resources can be spent on forwarding messages.
   The slope of the decline depends on the amount of resources spent to
   evaluate each message.

   The main idea of a explicit overload control is to use an explicit
   overload signal to request a reduction in the offered load.  This
   enables a SIP server to adjust the offered load to a level at which
   it can perform at maximum capacity.

   Reducing the extent to which SIP server overload is regenerative and
   an efficient explicit overload control mechanism to control incoming
   load are two complementary approaches to improve SIP performance
   under overload.

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3.  System Model

   The model shown in Figure 1 identifies fundamental components of an
   explicit SIP overload control mechanism:

   SIP Processor:  The SIP Processor processes SIP messages and is the
      component that is protected by overload control.
   Monitor:  The Monitor measures the current load of the SIP processor
      on the receiving entity.  It implements the mechanisms needed to
      determine the current usage of resources relevant for the SIP
      processor and reports load samples (S) to the Control Function.
   Control Function:  The Control Function implements the overload
      control algorithm.  The control function uses the load samples (S)
      and determines if overload has occurred and a throttle (T) needs
      to be set to adjust the load sent to the SIP processor on the
      receiving entity.  The control function on the receiving entity
      sends load feedback (F) to the sending entity.
   Actuator:  The Actuator implements the algorithms needed to act on
      the throttles (T) and to adjust the amount of traffic forwarded to
      the receiving entity.  For example, a throttle may instruct the
      Actuator to reduce the traffic destined to the receiving entity by
      10%.  The algorithms in the Actuator then determine how the
      traffic reduction is achieved, e.g., by selecting the messages
      that will be affected and determining whether they are rejected or

   The type of feedback (F) conveyed from the receiving to the sending
   entity depends on the overload control method used (i.e., loss-based,
   rate-based or window-based overload control; see Section 6), the
   overload control algorithm (see Section 7) as well as other design
   parameters.  In any case, the feedback (F) enables the sending entity
   to adjust the amount of traffic forwarded to the receiving entity to
   a level that is acceptable to the receiving entity without causing

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          Sending                Receiving
           Entity                  Entity
     +----------------+      +----------------+
     |    Server A    |      |    Server B    |
     |  +----------+  |      |  +----------+  |    -+
     |  | Control  |  |  F   |  | Control  |  |     |
     |  | Function |<-+------+--| Function |  |     |
     |  +----------+  |      |  +----------+  |     |
     |     T |        |      |       ^        |     | Overload
     |       v        |      |       | S      |     | Control
     |  +----------+  |      |  +----------+  |     |
     |  | Actuator |  |      |  | Monitor  |  |     |
     |  +----------+  |      |  +----------+  |     |
     |       |        |      |       ^        |    -+
     |       v        |      |       |        |    -+
     |  +----------+  |      |  +----------+  |     |
   <-+--|   SIP    |  |      |  |   SIP    |  |     |  SIP
   --+->|Processor |--+------+->|Processor |--+->   | System
     |  +----------+  |      |  +----------+  |     |
     +----------------+      +----------------+    -+

                Figure 1: System Model for Overload Control

4.  Degree of Cooperation

   A SIP request is often processed by more than one SIP server on its
   path to the destination.  Thus, a design choice for overload control
   is where to place the components of overload control along the path
   of a request and, in particular, where to place the Monitor and
   Actuator.  This design choice determines the degree of cooperation
   between the SIP servers on the path.  Overload control can be
   implemented hop-by-hop with the Monitor on one server and the
   Actuator on its direct upstream neighbor.  Overload control can be
   implemented end-to-end with Monitors on all SIP servers along the
   path of a request and one Actuator on the sender.  In this case,
   Monitors have to cooperate to jointly determine the current resource
   usage on this path.  Finally, overload control can be implemented
   locally on a SIP server if Monitor and Actuator reside on the same
   server.  In this case, the sending entity and receiving entity are
   the same SIP server and Actuator and Monitor operate on the same SIP
   processor (although, the Actuator typically operates on a pre-
   processing stage in local overload control).  These three
   configurations are shown in Figure 2.

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                         +-+                    +---------+
                         v |           +------+ |         |
    +-+      +-+        +---+          |      | |        +---+
    v |      v |    //=>| C |          v      | v    //=>| C |
   +---+    +---+ //    +---+       +---+    +---+ //    +---+
   | A |===>| B |                   | A |===>| B |
   +---+    +---+ \\    +---+       +---+    +---+ \\    +---+
                    \\=>| D |                   ^    \\=>| D |
                        +---+                   |        +---+
                         ^ |                    |         |
                         +-+                    +---------+

           (a) local                      (b) hop-by-hop

      |       ^          |
      |       |         +---+
      v       |     //=>| C |
   +---+    +---+ //    +---+
   | A |===>| B |
   +---+    +---+ \\    +---+
      ^       |     \\=>| D |
      |       |         +---+
      |       v          |

         (c) end-to-end

    ==> SIP request flow
    <-- Overload feedback loop

              Figure 2: Degree of Cooperation between Servers

4.1.  Hop-by-Hop

   The idea of hop-by-hop overload control is to instantiate a separate
   control loop between all neighboring SIP servers that directly
   exchange traffic.  I.e., the Actuator is located on the SIP server
   that is the direct upstream neighbor of the SIP server that has the
   corresponding Monitor.  Each control loop between two servers is
   completely independent of the control loop between other servers
   further up- or downstream.  In the example in Figure 2(b), three
   independent overload control loops are instantiated: A - B, B - C and
   B - D. Each loop only controls a single hop.  Overload feedback
   received from a downstream neighbor is not forwarded further
   upstream.  Instead, a SIP server acts on this feedback, for example,
   by re-routing or rejecting traffic if needed.  If the upstream

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   neighbor of a server also becomes overloaded, it will report this
   problem to its upstream neighbors, which again take action based on
   the reported feedback.  Thus, in hop-by-hop overload control,
   overload is always resolved by the direct upstream neighbors of the
   overloaded server without the need to involve entities that are
   located multiple SIP hops away.

   Hop-by-hop overload control reduces the impact of overload on a SIP
   network and, in particular, can avoid congestion collapse.  In
   addition, hop-by-hop overload control is simple and scales well to
   networks with many SIP entities.  It does not require a SIP entity to
   aggregate a large number of overload status values or keep track of
   the overload status of SIP servers it is not communicating with.

4.2.  End-to-End

   End-to-end overload control implements an overload control loop along
   the entire path of a SIP request, from UAC to UAS.  An end-to-end
   overload control mechanism consolidates overload information from all
   SIP servers on the way including all proxies and the UAS and uses
   this information to throttle traffic as far upstream as possible.  An
   end-to-end overload control mechanism has to be able to frequently
   collect the overload status of all servers on the potential path(s)
   to a destination and combine this data into meaningful overload

   A UA or SIP server only needs to throttle requests if it knows that
   these requests will eventually be forwarded to an overloaded server.
   For example, if D is overloaded in Figure 2(c), A should only
   throttle requests it forwards to B when it knows that they will be
   forwarded to D. It should not throttle requests that will eventually
   be forwarded to C, since server C is not overloaded.  In many cases,
   it is difficult for A to determine which requests will be routed to C
   and D since this depends on the local routing decision made by B.

   The main problem of end-to-end path overload control is its inherent
   complexity since UAC or SIP servers need to monitor all potential
   paths to a destination in order to determine which requests should be
   throttled and which requests may be sent.  In addition, the routing
   decisions of a SIP server depend on local policy, which can be
   difficult to infer for an upstream neighbor.  Therefore, end-to-end
   overload control is likely to only work well in simple, well-known
   topologies (e.g., a server that is known to only have one downstream
   neighbor) or if a UA/server sends many requests to the exact same

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4.3.  Local Overload Control

   Local overload control does not require an explicit overload signal
   between SIP entities as it is implemented locally on a SIP server.
   It can be by a SIP server to determine when to reject incoming
   requests instead of forwarding them based on current resource usage.
   Local overload control can be used in conjunction with an explicit
   overload control mechanisms and provides an additional layer of
   protection against overload, for example, when upstream servers do
   not support explicit overload control.  In general, servers should
   use an explicit mechanisms if available to throttle upstream
   neighbors before using local overload control as a mechanism of last

5.  Topologies

   The following topologies describe four generic SIP server
   configurations, which each poses specific challenges for an overload
   control mechanism.

   In the "load balancer" configuration shown in Figure 3(a) a set of
   SIP servers (D, E and F) receives traffic from a single source A. A
   load balancer is a typical example for such a configuration.  In this
   configuration, overload control needs to prevent server A (i.e., the
   load balancer) from sending too much traffic to any of its downstream
   neighbors D, E and F. If one of the downstream neighbors becomes
   overloaded, A can direct traffic to the servers that still have
   capacity.  If one of the servers serves as a backup, it can be
   activated once one of the primary servers reaches overload.

   If A can reliably determine that D, E and F are its only downstream
   neighbors and all of them are in overload, it may choose to report
   overload upstream on behalf of D, E and F. However, if the set of
   downstream neighbors is not fixed or only some of them are in
   overload then A should not use overload control since A can still
   forward the requests destined to non-overloaded downstream neighbors.
   These requests would be throttled as well if A would use overload
   control towards its upstream neighbors.

   In the "multiple sources" configuration shown in Figure 3(b), a SIP
   server D receives traffic from multiple upstream sources A, B and C.
   Each of these sources can contribute a different amount of traffic,
   which can vary over time.  The set of active upstream neighbors of D
   can change as servers may become inactive and previously inactive
   servers may start contributing traffic to D.

   If D becomes overloaded, it needs to generate feedback to reduce the

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   amount of traffic it receives from its upstream neighbors.  D needs
   to decide by how much each upstream neighbor should reduce traffic.
   This decision can require the consideration of the amount of traffic
   sent by each upstream neighbor and it may need to be re-adjusted as
   the traffic contributed by each upstream neighbor varies over time.

   In many configurations, SIP servers form a "mesh" as shown in
   Figure 3(c).  Here, multiple upstream servers A, B and C forward
   traffic to multiple alternative servers D and E. This configuration
   is a combination of the "load balancer" and "multiple sources"

                   +---+              +---+
                /->| D |              | A |-\
               /   +---+              +---+  \
              /                               \   +---+
       +---+-/     +---+              +---+    \->|   |
       | A |------>| E |              | B |------>| D |
       +---+-\     +---+              +---+    /->|   |
              \                               /   +---+
               \   +---+              +---+  /
                \->| F |              | C |-/
                   +---+              +---+

       (a) load balancer             (b) multiple sources

       | A |---\                        a--\
       +---+-\  \---->+---+                 \
              \/----->| D |             b--\ \--->+---+
       +---+--/\  /-->+---+                 \---->|   |
       | B |    \/                      c-------->| D |
       +---+---\/\--->+---+                       |   |
               /\---->| E |            ...   /--->+---+
       +---+--/   /-->+---+                 /
       | C |-----/                      z--/

             (c) mesh                   (d) edge proxy

                           Figure 3: Topologies

   Overload control that is based on reducing the number of messages a
   sender is allowed to send is not suited for servers that receive
   requests from a very large population of senders, each of which only
   infrequently sends a request.  This scenario is shown in Figure 3(d).

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   An edge proxy that is connected to many UAs is a typical example for
   such a configuration.

   Since each UA typically only contributes a few requests, which are
   often related to the same call, it can't decrease its message rate to
   resolve the overload.  In such a configuration, a SIP server can
   resort to local overload control by rejecting a percentage of the
   requests it receives with 503 (Service Unavailable) responses.  Since
   there are many upstream neighbors that contribute to the overall
   load, sending 503 (Service Unavailable) to a fraction of them can
   gradually reduce load without entirely stopping all incoming traffic.
   Using 503 (Service Unavailable) towards individual sources can,
   however, not prevent overload if a large number of users places calls
   at the same time.

      Note: The requirements of the "edge proxy" topology are different
      than the ones of the other topologies, which may require a
      different method for overload control.

6.  Type of Overload Control Feedback

   The type of feedback generated by a receiver to limit the amount of
   traffic it receives is an important aspect of the design.  We discuss
   the following three different types of overload control feedback:
   rate-based, loss-based and window-based overload control.

6.1.  Rate-based Overload Control

   The key idea of rate-based overload control is to limit the request
   rate at which an upstream element is allowed to forward to the
   downstream neighbor.  If overload occurs, a SIP server instructs each
   upstream neighbor to send at most X requests per second.  Each
   upstream neighbor can be assigned a different rate cap.

   The rate cap ensures that the number of requests received by a SIP
   server never increases beyond the sum of all rate caps granted to
   upstream neighbors.  It can protect a SIP server against overload
   even during load spikes if no new upstream neighbors start sending
   traffic.  New upstream neighbors need to be factored into the rate
   caps assigned as soon as they appear.  The current overall rate cap
   used by a SIP server is determined by an overload control algorithm,
   e.g., based on system load.

   An algorithm for the sending entity to implement a rate cap of a
   given number of requests per second X is request gapping.  After
   transmitting a request to a downstream neighbor, a server waits for
   1/X seconds before it transmits the next request to the same

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   neighbor.  Requests that arrive during the waiting period are not
   forwarded and are either redirected, rejected or buffered.

   A drawback of this mechanism is that it requires a SIP server to
   assign a certain rate cap to each of its upstream neighbors during an
   overload condition based on its overall capacity.  Effectively, a
   server assigns a share of its capacity to each upstream neighbor
   during overload.  The server needs to ensure that the sum of all rate
   caps assigned to upstream neighbors is not (significantly) higher
   than its actual processing capacity.  This requires a SIP server to
   keep track of the set of upstream neighbors and to adjust the rate
   cap if a new upstream neighbor appears or an existing neighbor stops
   transmitting.  If the cap assigned to upstream neighbors is too high,
   the server may still experience overload.  However, if the cap is too
   low, the upstream neighbors will reject requests even though they
   could be processed by the server.

   A SIP server can evaluate the amount of load it receives from each
   upstream neighbor and assign a rate cap that is suitable for this
   neighbor without limiting it too much.  This way, the SIP server can
   allocate resources that are not used by one upstream neighbor because
   it is sending less requests than allowed by the rate cap to another

   An alternative technique to allocate a rate cap to each upstream
   neighbor is using a fixed proportion of some control variable, X,
   where X is initially equal to the capacity of the SIP server.  The
   server then increases or decreases X until the workload arrival rate
   matches the actual server capacity.  Usually, this will mean that the
   sum of the rate caps sent out by the server (=X) exceeds its actual
   capacity, but enables upstream neighbors who are not generating more
   than their fair share of the work to be effectively unrestricted.  An
   advantage of this approach is that the server only has to measure the
   aggregate arrival rate, and that the calculation of the individual
   rate caps is fairly trivial.

6.2.  Loss-based Overload Control

   A loss percentage enables a SIP server to ask an upstream neighbor to
   reduce the number of requests it would normally forward to this
   server by a percentage X. For example, a SIP server can ask an
   upstream neighbor to reduce the number of requests this neighbor
   would normally send by 10%.  The upstream neighbor then redirects or
   rejects X percent of the traffic that is destined for this server.

   An algorithm for the sending entity to implement a loss percentage is
   to draw a random number between 1 and 100 for each request to be
   forwarded.  The request is not forwarded to the server if the random

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   number is less than or equal to X.

   An advantage of loss-based overload control is that, the receiving
   entity does not need to track the set of upstream neighbors or the
   request rate it receives from each upstream neighbor.  It is
   sufficient to monitor the overall system utilization.  To reduce
   load, a server can ask its upstream neighbors to lower the traffic
   forwarded by a certain percentage.  The server calculates this
   percentage by combining the loss percentage that is currently in use
   (i.e., the loss percentage the upstream neighbors are currently using
   when forwarding traffic), the current system utilization and the
   desired system utilization.  For example, if the server load
   approaches 90% and the current loss percentage is set to a 50%
   traffic reduction, then the server can decide to increase the loss
   percentage to 55% in order to get to a system utilization of 80%.
   Similarly, the server can lower the loss percentage if permitted by
   the system utilization.

   The main drawback of percentage throttling is that the throttle
   percentage needs to be adjusted to the current number of requests
   received by the server.  This is in particular important if the
   number of requests received fluctuates quickly.  For example, if a
   SIP server sets a throttle value of 10% at time t1 and the number of
   requests increases by 20% between time t1 and t2 (t1<t2), then the
   server will see an increase in traffic by 10% between time t1 and t2.
   This is even though all upstream neighbors have reduced traffic by
   10% as told.  Thus, percentage throttling requires an adjustment of
   the throttling percentage in response to the traffic received and may
   not always be able to prevent a server from encountering brief
   periods of overload in extreme cases.

6.3.  Window-based Overload Control

   The key idea of window-based overload control is to allow an entity
   to transmit a certain number of messages before it needs to receive a
   confirmation for the messages in transit.  Each sender maintains an
   overload window that limits the number of messages that can be in
   transit without being confirmed.

   Each sender maintains an unconfirmed message counter for each
   downstream neighbor it is communicating with.  For each message sent
   to the downstream neighbor, the counter is increased by one.  For
   each confirmation received, the counter is decreased by one.  The
   sender stops transmitting messages to the downstream neighbor when
   the unconfirmed message counter has reached the current window size.

   A crucial parameter for the performance of window-based overload
   control is the window size.  The windows size together with the

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   round-trip time between sender and receiver determines the effective
   message rate that can be achieved.  Each sender has an initial window
   size it uses when first sending a request.  This window size can be
   changed based on the feedback it receives from the receiver.

   The sender adjusts its window size as soon as it receives the
   corresponding feedback from the receiver.  If the new window size is
   smaller than the current unconfirmed message counter, the sender
   stops transmitting messages until more messages are confirmed and the
   current unconfirmed message counter is less than the window size.

   A sender should not treat the reception of a 100 Trying response as
   an implicit confirmation for a message. 100 Trying responses are
   often created by a SIP server very early in processing and do not
   indicate that a message has been successfully processed and cleared
   from the input buffer.  If the downstream neighbor is a stateless
   proxy, it will not create 100 Trying responses at all and instead
   pass through 100 Trying responses created by the next stateful
   server.  Also, 100 Trying responses are typically only created for
   INVITE requests.  Explicit message confirmations via an overload
   feedback mechanism do not have these problems.

   The behavior and issues of window-based overload control are similar
   to rate-based overload control, in that the total available receiver
   buffer space needs to be divided among all upstream neighbors.
   However, unlike rate-based overload control, window-based overload
   control can ensure that the receiver buffer does not overflow under
   normal conditions.  The transmission of messages by senders is
   effectively clocked by message confirmations received from the
   receiver.  A buffer overflow can occur if a large number of new
   upstream neighbors arrives at the same time.

6.4.  On-/Off Overload Control

   On-/off overload control feedback enables a SIP server to turn the
   traffic it is receiving either on or off.  The 503 (Service
   Unavailable) response implements on-/off overload control.  On-/off
   overload control is less effective in controlling load than the fine
   grained control methods above.  In fact, the above methods can
   realize on/-off overload control, e.g., by setting the allowed rate
   to either zero or unlimited.

7.  Overload Control Algorithms

   An important aspect of the design of an overload control mechanism is
   the overload control algorithm.  The control algorithm determines
   when the amount of traffic a SIP server receives needs to be

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   decreased and when it can be increased.

   Overload control algorithms have been studied to a large extent and
   many different overload control algorithms exist.  With many
   different overload control algorithms available, it seems reasonable
   to define a baseline algorithm and allow the use of other algorithms
   if they don't violate the protocol semantics.  This will also allow
   the development of future algorithms, which may lead to a better

8.  Self-Limiting

   An important design aspect for an overload control mechanism is that
   it is self limiting.  I.e., an overload control mechanism should stop
   a sender if the sender does not receive any feedback from the
   receiver.  This avoids that an overloaded server, which has become
   unable to generate overload control feedback, will be overwhelmed
   with requests.

   Window-based overload control is inherently self-limiting since a
   sender cannot continue without receiving confirmations.  Servers
   using Rate- or Loss-based overload control need to be configured to
   stop transmitting if they do not receive any feedback from the

9.  Security Considerations


10.  IANA Considerations


Appendix A.  Contributors

   Contributors to this document are: Ahmed Abd el al (Sonus Networks),
   Mary Barnes (Nortel), Carolyn Johnson (AT&T Labs), Daryl Malas
   (CableLabs), Eric Noel (AT&T Labs), Tom Phelan (Sonus Networks),
   Jonathan Rosenberg (Cisco), Henning Schulzrinne (Columbia
   University), Charles Shen (Columbia University), Nick Stewart
   (British Telecommunications plc), Rich Terpstra (Level 3), Indra
   Widjaja (Bell Labs/Alcatel-Lucent).  Many thanks!

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11.  Informative References

              Rosenberg, J., "Requirements for Management of Overload in
              the Session Initiation Protocol",
              draft-rosenberg-sipping-overload-reqs-02 (work in
              progress), October 2006.

   [RFC3261]  Rosenberg, J., Schulzrinne, H., Camarillo, G., Johnston,
              A., Peterson, J., Sparks, R., Handley, M., and E.
              Schooler, "SIP: Session Initiation Protocol", RFC 3261,
              June 2002.

   [RFC4412]  Schulzrinne, H. and J. Polk, "Communications Resource
              Priority for the Session Initiation Protocol (SIP)",
              RFC 4412, February 2006.

Author's Address

   Volker Hilt (Ed.)
   Bell Labs/Alcatel-Lucent
   791 Holmdel-Keyport Rd
   Holmdel, NJ  07733

   Email: volkerh@bell-labs.com

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