Analysis of SIP retransmission probability using a Markov-Modulated Poisson Process model

As a main signaling protocol for multimedia sessions in the Internet, SIP (Session Initiation Protocol) introduces a retransmission mechanism to maintain the reliability for its realtime transmission. However, retransmission will make the server overload worse. Recent collapse of SIP servers due to emergencyinduced call volume indicates that the built-in SIP overload control mechanism cannot prevent the server from overload collapse under heavy load. In this paper, we apply a MMPP (Markov-Modulated Poisson Process) model to analyze the queuing mechanism of SIP server under two typical service states. The MMPP model allows us to investigate the probability of SIP retransmissions. By performing numerous experiments statistically to verify SIP retransmission probability calculated by MMPP model, we find that high retransmission probability caused by short demand surge or reduced server processing capacity during maintenance period may overload and crash a server. We run simulations using time-series directly to observe and analyze the system performance of an overloaded SIP server. This is much faster than event-driven simulation. Numerical results demonstrate that low resource utilization corresponds to low retransmission probability. However, a utilization as low as 20% cannot always guarantee a SIP system stability upon a temporal server slowdown or a short period of demand burst.