Online gaming is one of the most profitable businesses on the Internet. Among various threats to continuous player subscriptions, network lags are particularly notorious. It is widely known that frequent and long lags frustrate game players, but whether the players actually take action and leave a game is unclear. Motivated to answer this question, we apply survival analysis to a 1, 356-million-packet trace from a sizeable MMORPG, called ShenZhou Online. We find that both network delay and network loss significantly affect a player’s willingness to continue a game. For ShenZhou Online, the degrees of player “intolerance” of minimum RTT, RTT jitter, client loss rate, and server loss rate are in the proportion of 1:2:11:6. This indicates that 1) while many network games provide “ping time,” i.e., the RTT, to players to facilitate server selection, it would be more useful to provide information about delay jitters; and 2) players are much less tolerant of network loss than delay. This is due to the game designer’s decision to transfer data in TCP, where packet loss not only results in additional packet delays due to in-order delivery and retransmission, but also a lower sending rate.

1. On the Sensitivity of Online Game Playing Time to Network QoS Kuan-Ta Chen National Taiwan University Polly Huang Guo-Shiuan Wang Chun-Ying Huang Chin-Laung Lei Collaborators: INFOCOM 2006

4. Assessment of User Satisfaction Internet Which path can provide the best user experience? ? ? ? Satisfaction Good Average Poor 3 Poor Good Average 2 Average Loss Poor Delay Jitter Good Latency 1 Path

6. Our Conjecture Poor Network Quality Unstable Game Play Less Fun Shorter Game Play Time affects Verified by real-life game traces

9. Trace Collection (20 hours and 1,356 million packets) < 40 min Bottom 20% > 8 hours Top 20% 100 min Avg. Time 15,140 Session #

10. Round-Trip Times vs. Session Time y-axis is logarithmic

11. Delay Jitter vs. Session Time (std. dev. of the round-trip times)

12. Hypothesis Testing -- Effect of Loss Rate Null Hypothesis: All the survival curves are equivalent Log-rank test: P < 1e-20 We have > 99.999% confidence claiming loss rates are correlated with game playing times high loss low loss med loss The CCDF of game session times

13. Effect of QoS Factors -- Overview (significant: p-value < 0.01) N/A No Queueing Delay Negative Yes Server Packet Loss Negative Yes Client Packet Loss Negative Yes Delay Jitter Negative Correlation Yes Significant? Average RTT QoS Factor

16. The Logarithm Fits Better (client packet loss rate)

17. Final Model & Interpretation A: RTT = 200 ms B: RTT = 100 ms, other factors same as A Hazard ratio between A and B: exp((log(0.2) – log(0.1)) × 1.27 ) ≈ 2.4 A will more likely leave a game ( 2.4 times probability ) than B at any moment Interpretation < 1e-20 0.04 1.27 log(RTT) 0.01 0.01 0.03 Std. Err. 7e-13 0.09 log(sloss) < 1e-20 0.12 log(closs) < 1e-20 Signif. 0.68 Coef log(jitter) Variable

18. How good does the model fit? Observed average session times are almost within the 95% confidence band

22. Thank You! Kuan-Ta Chen