SIPPING Working Group                                      V. Hilt (Ed.)
Internet-Draft                                  Bell Labs/Alcatel-Lucent
Intended status: Informational                          October 22, 2008
Expires: April 25, 2009

  Design Considerations for Session Initiation Protocol (SIP) Overload

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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.  SIP Overload Problem . . . . . . . . . . . . . . . . . . . . .  4
   3.  Explicit vs. Implicit Overload Control . . . . . . . . . . . .  4
   4.  System Model . . . . . . . . . . . . . . . . . . . . . . . . .  5
   5.  Degree of Cooperation  . . . . . . . . . . . . . . . . . . . .  7
     5.1.  Hop-by-Hop . . . . . . . . . . . . . . . . . . . . . . . .  8
     5.2.  End-to-End . . . . . . . . . . . . . . . . . . . . . . . .  9
     5.3.  Local Overload Control . . . . . . . . . . . . . . . . . . 10
   6.  Topologies . . . . . . . . . . . . . . . . . . . . . . . . . . 10
   7.  Explicit Overload Control Feedback . . . . . . . . . . . . . . 13
     7.1.  Rate-based Overload Control  . . . . . . . . . . . . . . . 13
     7.2.  Loss-based Overload Control  . . . . . . . . . . . . . . . 14
     7.3.  Window-based Overload Control  . . . . . . . . . . . . . . 15
     7.4.  Overload Signal-based Overload Control . . . . . . . . . . 16
     7.5.  On-/Off Overload Control . . . . . . . . . . . . . . . . . 16
   8.  Implicit Overload Control  . . . . . . . . . . . . . . . . . . 17
   9.  Overload Control Algorithms  . . . . . . . . . . . . . . . . . 17
   10. Security Considerations  . . . . . . . . . . . . . . . . . . . 17
   11. IANA Considerations  . . . . . . . . . . . . . . . . . . . . . 18
   Appendix A.  Contributors  . . . . . . . . . . . . . . . . . . . . 18
   12. Informative References . . . . . . . . . . . . . . . . . . . . 18
   Author's Address . . . . . . . . . . . . . . . . . . . . . . . . . 18
   Intellectual Property and Copyright Statements . . . . . . . . . . 19

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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 occurs 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 resources.

   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

   An overload control mechanism enables a SIP server to perform close
   to its capacity limit during times of overload.  Overload control is
   used by a SIP server if it is unable to process all SIP requests due
   to resource constraints.  There are other failure cases in which a
   SIP server can successfully process incoming requests but has to
   reject them for other reasons.  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 mechanisms do
   not apply in 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 and the Retry-
   After header.  However, this mechanism cannot prevent overload of a
   SIP server and it cannot prevent congestion collapse.  In fact, it
   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 Retry-After header 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.  SIP Overload Problem

   A key contributor to the SIP congestion collapse
   [I-D.ietf-sipping-overload-reqs] is the regenerative behavior of
   overload in the SIP protocol.  When SIP is running over the UDP
   protocol, it will retransmit messages that were dropped by a SIP
   server due to overload and thereby 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.  A congestion collapse can occur.

   While regenerative behavior under overload should ideally be avoided
   by any protocol and would lead to stable operation under overload,
   this is often difficult to achieve in practice.  For example,
   changing the SIP retransmission timer mechanisms can reduce the
   degree of regeneration during overload, however, these changes will
   impact the ability of SIP to recover from message losses.  Without
   any retransmission each message that is dropped due to SIP server
   overload will eventually lead to a failed call.

   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
   would be 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.

   Another key challenge for SIP overload control is that the rate of
   the true traffic source usually cannot be controlled.  Overload is
   often caused by a large number of UAs each of which creates only a
   single message.  These UAs cannot be rate controlled as they only
   send one message.  However, the sum of their traffic can overload a
   SIP server.

3.  Explicit vs. Implicit Overload Control

   The main differences between explicit and implicit overload control

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   is the way overload is signaled from a SIP server that is reaching
   overload condition to its upstream neighbors.

   In an explicit overload control mechanism, a SIP server uses an
   explicit overload signal to indicate that it is reaching its capacity
   limit.  Upstream neighbors receiving this signal can adjust their
   transmission rate as indicated in the overload signal to a level that
   is acceptable to the downstream server.  The overload signal enables
   a SIP server to steer the load it is receiving to a rate at which it
   can perform at maximum capacity.

   Implicit overload control uses the absence of responses and packet
   loss as an indication of overload.  A SIP server that is sensing such
   a condition reduces the load it is forwarding a downstream neighbor.
   Since there is no explicit overload signal, this mechanism is robust
   as it does not depend on actions taken by the SIP server running into

   The ideas of explicit and implicit overload control are in fact
   complementary.  By considering implicit overload indications a server
   can avoid overloading an unresponsive downstream neighbor.  An
   explicit overload signal enables a SIP server to actively steer the
   incoming load to a desired level.

4.  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 ensures that the amount of traffic forwarded
      to the receiving entity meets the criteria of the throttle.  For
      example, a throttle may instruct the Actuator to not forward more
      than 100 INVITE messages per second.  The Actuator implements the
      algorithms to achieve this objective, e.g., using message gapping.

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      It also implements algorithms to select the messages that will be
      affected and determine whether they are rejected or redirected.

   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 7), the
   overload control algorithm (see Section 9) 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

   Figure 1 depicts a general system model for overload control.  In
   this diagram, one instance of the control function is on the sending
   entity (i.e., associated with the actuator) and one is on the
   receiving entity (i.e., associated with the monitor).  However, a
   specific mechanism may not require both elements.  In this case, one
   of two control function elements can be empty and simply passes along
   feedback.  E.g., if (F) is defined as a loss-rate (e.g., reduce
   traffic by 10%) there is no need for a control function on the
   sending entity as the content of (F) can be copied directly into (T).

   The model in Figure 1 shows a scenario with one sending and one
   receiving entity.  In a more realistic scenario a receiving entity
   will receive traffic from multiple sending entities and vice versa
   (see Section 6).  The feedback generated by a Monitor will therefore
   often be distributed across multiple Actuators.  An Actuator needs to
   be prepared to receive different levels of feedback from different
   receiving entities and throttle traffic to these entities

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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 Explicit Overload Control

5.  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 an explicit
   overload control mechanism 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 an
   Actuator on the sender.  In this case, the Control Functions
   associated with each Monitor have to cooperate to jointly determine
   the overall feedback for 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).  Local overload
   control is an internal overload control mechanism as the control loop
   is implemented internally on one server.  Hop-by-hop and end-to-end
   are external overload control mechanisms.  All three configurations

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   are shown in Figure 2.

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

         (a) hop-by-hop                   (b) end-to-end

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

           (c) local

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

              Figure 2: Degree of Cooperation between Servers

5.1.  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

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   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
   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 can avoid congestion collapse.  It is simple and scales
   well to networks with many SIP entities.  A key advantage is that it
   does not require feedback to be transmitted across multiple-hops,
   possibly crossing multiple trust domains.  Feedback is sent to the
   next hop only.  Furthermore, 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.

5.2.  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.
   These routing decisions can be highly variable and, for example,
   depend on call routing policies configured by the user, services
   invoked on a call, load balancing policies, etc.  The fact that a
   previous call to a target has been routed through an overload server
   does not necessarily mean the next call to this target will also be
   routed through the same server.

   Overall, the main problem of end-to-end path overload control is its
   inherent complexity since UAC or SIP servers need to monitor all

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   potential paths to a destination in order to determine which requests
   should be throttled and which requests may be sent.  Even if this
   information is available, it is not clear which path a specific
   request will take.  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).

   A key difference to transport protocols using end-to-end congestion
   control such as TCP is that the traffic exchanged by SIP servers
   consists of many individual SIP messages.  Each of these SIP messages
   has its own source and destination.  This is different from TCP which
   controls a stream of packets between a single source and a single

5.3.  Local Overload Control

   The idea of local overload control is to run the Monitor and Actuator
   on the same server.  This enables the server to monitor the current
   resource usage and to reject messages that can't be processed without
   overusing the local resources.  The fundamental assumption behind
   local overload control is that it is less resource consuming for a
   server to reject messages than to process them.  A server can
   therefore reject the excess messages it cannot process, stopping all
   retransmissions of these messages.

   Local overload control can be used in conjunction with an implicit or
   explicit overload control mechanism and provides an additional layer
   of protection against overload.  It is fully implemented on the local
   server and does not require any cooperation from upstream neighbors.
   In general, servers should use implicit or explicit overload control
   techniques before using local overload control as a mechanism of last

6.  Topologies

   The following topologies describe four generic SIP server
   configurations.  These topologies illustrate specific challenges for
   an overload control mechanism.  An actual SIP server topology is
   likely to consist of combinations of these generic scenarios.

   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

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   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
   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"

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                   +---+              +---+
                /->| 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).
   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.
   The Retry-After header can be used in 503 (Service Unavailable)
   responses to ask UAs to wait a given number of seconds before trying

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   the call again.  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.

7.  Explicit Overload Control Feedback

   Explicit overload control feedback enables a receiver to indicate how
   much traffic it wants to receive.  Explicit overload control
   mechanisms can be differentiated based on the type of information
   conveyed in the overload control feedback.

7.1.  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.

   An example algorithm for the Actuator in a sending entity to
   implement a rate cap 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 neighbor.  Requests that
   arrive during the waiting period are not forwarded and are either
   redirected, rejected or buffered.

   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.  Rate-based overload control protects a SIP
   server against overload even during load spikes assuming there are no
   new upstream neighbors that start sending traffic.  New upstream
   neighbors need to be considered in all rate caps currently assigned
   to upstream neighbors.  The current overall rate cap of a SIP server
   is determined by an overload control algorithm, e.g., based on system

   Rate-based overload control requires a SIP server to assign a rate
   cap to each of its upstream neighbors while it is activated.
   Effectively, a server needs to assign a share of its overall capacity
   to each upstream neighbor.  A 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

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   the rate cap if a new upstream neighbor appears or an existing
   neighbor stops transmitting.  For example, if the capacity of the
   server is X and this server is receiving traffic from two upstream
   neighbors, it can assign a rate of X/2 to each of them.  If a third
   sender appears, the rate for each sender is lowered to X/3.  If the
   rate cap assigned to upstream neighbors is too high, a server may
   still experience overload.  If the cap is too low, the upstream
   neighbors will reject requests even though they could be processed by
   the server.

   An approach for estimating a rate cap for each upstream neighbor is
   using a fixed proportion of a 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.  In this
   approach, the server only has to measure the aggregate arrival rate,
   however, since the overall rate cap is usually higher than the actual
   capacity, brief periods of overload may occur.

7.2.  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
   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

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   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.

   Loss-based overload control requires that the throttle percentage is
   adjusted to the current overall 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.

7.3.  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.  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

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   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 do not have these

   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.

7.4.  Overload Signal-based Overload Control

   The key idea of overload signal-based overload control is to use the
   transmission of a 503 (Service Unavailable) response as a signal for
   overload in the downstream neighbor.  After receiving a 503 (Service
   Unavailable) response, the sender reduces the load forwarded to the
   downstream neighbor to avoid triggering more 503 (Service
   Unavailable) responses.  The sender reduces the load further if more
   503 (Service Unavailable) responses are returned.  This scheme is
   based on the use of 503 (Service Unavailable) responses without
   Retry-After header as the Retry-After header would require a sender
   to stop forwarding requests.

   A sender which has not received 503 (Service Unavailable) responses
   for a while but is still throttling traffic can start to increase the
   offered load.  By slowly increasing load a sender can detect that
   overload in the downstream neighbor has been resolved and more load
   can be forwarded.  The load is increased until the sender again
   receives another 503 (Service Unavailable) response or is forwarding
   all requests it has.

   A possible algorithm for adjusting traffic is additive increase/
   multiplicative decrease (AIMD).

7.5.  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 with Retry-After header 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.,

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   by setting the allowed rate to either zero or unlimited.

8.  Implicit Overload Control

   Implicit overload control ensures that the transmission of a SIP
   server is self-limiting.  It slows down the transmission rate of a
   sender when there is an indication that the receiving entity is
   experiencing overload.  Such an indication can be that the receiving
   entity is not responding within the expected timeframe or is not
   responding at all.  The idea of implicit overload control is that
   senders should try to sense overload of a downstream neighbor even if
   there is no explicit overload control feedback.  It 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.  All other
   explicit overload control schemes described above do not have this
   property and require additional implicit controls to limit
   transmissions in case an overloaded downstream neighbor does not
   generate explicit feedback.

9.  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 to a SIP server needs to be decreased and
   when it can be increased.  In terms of the model described in
   Section 4 the control algorithm takes (S) as an input value and
   generates (T) as a result.

   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

10.  Security Considerations


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11.  IANA Considerations

   This document does not require any IANA considerations.

Appendix A.  Contributors

   Contributors to this document are: Ahmed Abdelal (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), Fangzhe
   Chang (Bell Labs/Alcatel-Lucent).  Many thanks!

12.  Informative References

              Rosenberg, J., "Requirements for Management of Overload in
              the Session Initiation Protocol",
              draft-ietf-sipping-overload-reqs-05 (work in progress),
              July 2008.

   [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


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