Web Proxy Caching: The Devil is in the Details Ramon Caceres, Fred Douglis, Anja Feldmann

1. Web Proxy Caching: The Devil is in the DetailsRamon Caceres, Fred Douglis, Anja Feldmann Proceedings of the Workshop on Internet Server Performance, Madison, WI, June 23 1998 Young-Ho Suh Network Computing Lab. KAIST

2. Contents • Introduction • Previous work • Solution approach • Simulation • Concluding remarks Internet Server Class

3. Servers Clients Proxy Internal Latency 23% External Latency 77% Introduction Proxy Caching Goals or Benefits? Internet Server Class

4. Introduction (Cont’d) • Expected benefits of Proxy Caching • Can reduce the user-perceived latency • Can lower the network traffic • Can reduce the service demands on content providers • Is really true? If then, how much? requires Performance Evaluation Internet Server Class

5. Previous work • Limitations • Fails to accurately reflect • Hit ratios • Bandwidth savings • User-perceived latency • Due to • Just considering high-level details • ex) cookies/ aborted request / TCP connection setup time, slow start phase • So they argue that “The Devil is …” Internet Server Class

6. Solution approach • Motivation • To judge the performance impact of proxy caches • Low-level details should be considered such as • Interaction b/w HTTP and TCP • Network environment • Other possible factor (e.g cacheability, connection abortion etc.) • Developed a new and more realistic proxy cache simulator - PROXIM Internet Server Class

7. 450 Modem banks FDDI ring Internet 2 terminal servers 18,000 dialup users • 500-MHz Alpha WS • 12days in mid-August, 1997 • 17,964 users • => 154,260 sessions • => maximum 421 simultaneous sessions Simulation – input(AT&T Worldnet) Law packet traces (150Million/day) Process them to final trace compactly Internet Server Class

8. Simulation – input (Cont’d) • Final Trace contains • TCP events • Timestamps, sequence numbers and acks for all packets with SYN, FIN, or RST bit set • HTTP events • Timestamps for HTTP requests/responses, and last packet for each direction • HTTP headers • Complete HTTP headers for both requests/responses • Byte counts • Bytes sent/responses • Input is ready… Internet Server Class

9. Simulation - PROXIM Simulated Cache Network Connections Document Transfer Latency Calculations Internet Server Class

10. Simulation - result • Hit Ratio • Only a secondary measure • Correlation with other metrics is low • Emulate full behavior of proxies • 30% of all requests had a cookie • If ignores cookie => 54.5% • Else => 35.2% • Byte hit ratio : 40.9% => 30.42% • Caching documents with cookie • Delta encoding • Client-side HTML macro-preprocessing Internet Server Class

11. Simulation – result (Cont’d) • Bandwidth Savings • Proxy can actually increase traffic • In case clients abort request • Due to BW mismatch b/w Client->Proxy and Proxy -> Server • The exact effect depends on the proxies • One extreme : continue to download • 49.8GB => 58.7GB : +18% • The other extreme : abort the download immediately • Depends on the proxy to server BW • 45Mbps : 49.8GB => 53.7GB (+8%) • 1.5Mbps : 49.8GB => 50.7GB (+2%) • 0.5Mbps : 49.8GB => 46.9GB (-6%, byte hit ratio : 30.42%) Internet Server Class

12. Simulation – result (Cont’d) • Latency Reduction • Mean : 3.4%, Median : 4.2% • cf)Upper bound : 26% (by Kroeger et al.) • due to • High latency of connection set-up • the effect of cookies • Modem BW (28.8Kbps) • Suggest Connection cache • Maintain persistent connection • If all connections are persistent => -24% • Else specified in the requests=> 13% • The rate of re-use of connection(hit ratio) : 30sec Time Out • Client -> Proxy : 81.5%, Proxy->Server : 79.5% • Maximum simultaneous connections : 238 Internet Server Class

13. Concluding remarks • Lesson learned • Low level details has a significant effect on all aspects of system performance • Hit ratios • Bandwidth savings • User-perceived latency • Critique • Interesting result • Not general environment • Other details? : prefetching, etc. Internet Server Class