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SIP Overload Control IETF Design Team Status. Volker Hilt volkerh@bell-labs.com Bell Labs/Alcatel-Lucent. SIP Overload Control Design Team Current Status. Team Members Eric Noel, Carolyn Johnson (AT&T Labs) Volker Hilt, Fangzhe Chang (Bell Labs/Alcatel-Lucent)
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SIP Overload ControlIETF Design Team Status Volker Hilt volkerh@bell-labs.com Bell Labs/Alcatel-Lucent
SIP Overload Control Design TeamCurrent Status • Team Members • Eric Noel, Carolyn Johnson (AT&T Labs) • Volker Hilt, Fangzhe Chang (Bell Labs/Alcatel-Lucent) • Charles Shen, Henning Schulzrinne (Columbia University) • Ahmed Abdelal, Tom Phelan (Sonus Networks) • Mary Barnes (Nortel) • Jonathan Rosenberg (Cisco) • Nick Stewart (British Telecom) • Four independent simulation tools • AT&T Labs, Bell Labs/Alcatel-Lucent, Columbia University, Sonus Networks • Bi-weekly conference calls.
draft-ietf-sipping-overload-design-00Status and Changes Status Submitted as SIPPING WG item. Changes to draft-hilt-sipping-overload-design-00 • Numerous clarifications throughout the text • Added separate section for problem description • Added an overload control mechanism: • Overload signal-based overload control • Discussion of implicit overload control in separate section.
draft-ietf-sipping-overload-design-00Next Steps Document investigates design choices and models. • Document is stable. • Simulation results are not included. Ready for WGLC?
Simulation Results Overload Control Feedback Types Rate-based Overload Control • Limit the request rate a server receives from an upstream element. • Feedback: X requests per second. Loss-based Overload Control • Reduce the request rate a server receives by a percentage X. • Feedback: reduce load by X%. Window-based Overload Control • Limit the number of request a server can receive without confirming a request. • Feedback: send X more requests. Overload Signal-based Overload Control • De-/increase of request rate until a target overload notification rate is reached. • Feedback: server overloaded (503 response without Retry–After header)
Simulation ResultsNo Overload Control Simulation Setup • Evaluate SIP overload performance under varying network conditions. • Network delay: 0 – 2 sec • Network loss: 0 – 50 % • Topology consists of 5 edge proxies and 2 core proxies. • Overall capacity: ~142 cps • Three levels of offered load: • Underload: 114 cps • Overload: 500 cps, 1000 cps Results • Delay and loss substantially decrease goodput even when there is no overload. • Confirmed by all simulators (AT&T Labs, Bell Labs/Alcatel-Lucent, Columbia University, Sonus Networks)
Simulation ResultsUpper Bound Estimation Delay and loss triggers retransmissions. • Increases the number of SIP messages needed to set up a call. • Causes the goodput of a server drops. Upper bound estimation • Determine increase in message count caused by delay/loss. • Example topology: UAC – proxy - UAS • Calculate resulting goodput. • Example result: 125 ms delay • Round trip delay exceeds 500ms. • One 200 OK/ACK retransmission and one BYE/200 OK retransmission triggered. • Messages per call increases from 7 to 11. Contributor: AT&T Labs
Simulation ResultsSelected Results on Overload Control (1) Rate-based Control Loss-based Control AT&T Labs Bell-Labs/Alcatel-Lucent
Simulation Results Selected Results on Overload Control (2) Window-based Control Overload Signal-based Control Columbia University Sonus Networks
Conclusions and Next Steps Conclusions • Large delay and loss rates can cause the goodput to drop substantially even in non-overloaded conditions. • Performance of all overload control mechanisms under evaluation is similar in steady state. • Varying network conditions do not reveal significant differences. • Next Steps • Evaluate additional scenarios. • Impact of different load distributions • Impact of varying upstream neighbor counts • Transient simulations. • Evaluate dynamic behavior of overload control mechanisms • Transition in/out of overload, impact of load peaks, etc. • Evaluate fairness of overload control mechanisms.
SIP Overload Control Design TeamPublications E. Noel, C. Johnson, “Initial Simulation Results That Analyze SIP Based VoIP Networks Under Overload”, International Teletraffic Congress (ITC’07), Ottawa, Canada, June 2007. C. Shen, H. Schulzrinne, E. Nahum, “Session Initiation Protocol (SIP) Server Overload Control: Design and Evaluation”, Principles, Systems and Applications of IP Telecommunications (IPTComm’08), Heidelberg, Germany, July 2008. • V. Hilt, I. Widjaja, “Controlling Overload in Networks of SIP Servers”, IEEE International Conference on Network Protocols (ICNP’08), Orlando, Florida, October 2008.