SIP Overload Control IETF Design Team Status Volker

SIP Overload Control IETF Design Team Status Volker Hilt volkerh@bell-labs. com Bell Labs/Alcatel-Lucent

SIP Overload Control Design 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. 2

draft-ietf-sipping-overload-design-01 Changes to -00 Added new sections on: Fairness Introduces fairness categories. Performance Metrics Discusses metrics to compare overload control mechanisms Message Priorization Selection of messages in overload condition. Added text to Security Considerations section. Minor edits throughout the text. 3

draft-ietf-sipping-overload-design-00 Next Steps Discussion of overload control mechanisms needs to be structured along the identified performance metrics. Document is close to completion. 4

SIP Overload Control Design Team Simulation Results Four types of overload control Rate-based Overload Control Loss-based Overload Control Window-based Overload Control Overload Signal-based Overload Control Summary of Steady-State Evaluation (presented at IETF ’ 73) Performance of all overload control mechanisms under evaluation is similar in steady state. Varying network conditions (i. e. , delay, loss-rate) do not reveal significant differences. Results for Transient Scenarios Evaluation of transient behavior with respect to Changes in offered load changes in the number of neighbors Fairness 5

Changes in Offered-Load (AT&T Labs) Rate-based and Window-based Overload Control Simulations use the following overload control feedback types and algorithms: Rate-based: queue delay Loss-based: SRED Window-based Feedback conveyed in SIP responses. Result: rate-, loss- and window-based controls respond well to transient stimulus. 6

CPS Changes in Offered-Load (Bell Labs/Alcatel-Lucent) Loss-based and Rate-based Overload Control Time Overload control feedback type and algorithms used: SRED algorithm Loss- vs. rate-based feedback SIP responses convey feedback from core to edge proxies. Result: loss- and rate-based overload control perform well. 7 Time

Changes in Offered-Load (Columbia University) Window-based and Rate-based Overload Control Window- and rate-based controls perform well. 8 03/27/09 Slide 8

Changes in Offered-Load (Sonus Networks) Loss-based and Overload-Signal-based Overload Control Target Overload Signal Rate =10 Overload Signals /Sec 9

Changes in the Number of Senders (Bell Labs/Alcatel-Lucent) Loss-based and Rate-based Overload Control Edge proxies are turned on/off sequentially. Each edge proxy sends the same amount of load while active. Feedback-type and algorithms: Rate-fixed: core proxies are configured with a fixed number of senders. The overall rate of a core proxy is divided through the sender number. Rate-aware: core proxies estimate the number of senders. The overall rate of a core proxy is divided through the sender estimate. Loss-based: same loss rate is sent to all edge proxies. All simulations use SRED algorithm. 10

Fairness (Columbia University) Rate-based Overload Control Provider-centric fairness: each source gets the same share User-centric fairness: each source gets a share proportional to its original incoming load 11 Slide 11

Conclusion & Next Steps Simulation Results The overload control performance seems to differ little between the type of feedback: Rate-, Loss-, Window- and Signal-based mechanisms all performed well in steady-state as well as transient evaluations. Of course, the performance does vary depending on the overload control algorithms used and parameter settings of these algorithms. But: algorithms and parameter settings are likely to be out of scope for an overload control protocol specification. Next Steps Evaluate additional transient scenarios. Finalize draft-ietf-sipping-overload-design-01 Work on a solution!! 12

A Session Initiation Protocol (SIP) Load Control Event Package draft-shen-sipping-load-control-event-package-01 Charles Shen, Henning Schulzrinne, Arata Koike Session Initiation Protocol (SIP) Overload Control draft-hilt-sipping-overload-06 Volker Hilt, Indra Widjaja, Henning Schulzrinne

Filter-based SIP Server Overload Control draft-shen-sipping-load-control-event-package-01 Enterprise Network A Hotline Callee 212 -555 -1234 9 am-10 am, 2009 -1 -1 Service Provider A Enterprise Network B Service Provider B Charles Shen, Henning Schulzrinne, Arata Koike, A Session Initiation Protocol (SIP) Load Control Event Package, draft-shen-sipping-load-control-event-package-01. txt, IETF SIPPING Working Group, Work in Progress. Nov 3, 2008 14 14

Session Initiation Protocol (SIP) Overload Control draft-hilt-sipping-overload-06 Reduces load Server S 1 Server S 2 Overload Via: SIP/2. 0/TCP ss 1. example. com: 5060 ; oc=20; oc_validity=500 Overload control mechanism Enables proxies to send overload control feedback to upstream neighbors. Feedback is conveyed in SIP responses New Via Header Parameters Supports different types of feedback. Currently defined: loss-based. Specifies the protocol semantics. Open to different overload control algorithms. 15