Evaluation of Cooperative Web Caching with Web Polygraph

1. Evaluation of Cooperative Web Caching with Web Polygraph Ping Du and Jaspal Subhlok Department of Computer Science University of Houston presented at WCW 02, Aug 14

2. Parent Web Cache parent-child relationship To Origin Server sibling-sibling relationship ICP Queries Child Web Cache Request Web Cache Hierarchy

3. Motivation and Goals • No practical methods to evaluate cache hierarchies under specific workload and network conditions • Important for designing a “caching solution” • Criteria for evaluation system • Model reality well • Applicable to different protocols & structures • Experiments should be repeatable • Use both hit rate and user response time as metrics • Solution based on Web Polygraph

4. Cache Evaluation with Web Polygraph Polysrv Polysrv Polysrv • Synthetic HTTP clients and servers on real machines on a LAN • Workload parameterized by size, distribution, popularity, load and many others Proxy Cache Polyclt Polyclt Polyclt

5. Network Delay Hierarchy Evaluation with Web Polygraph Polysrv Polysrv Polysrv Proxy Cache Proxy Cache Proxy Cache Polyclt Polyclt Polyclt

6. Evaluation Framework • Web Polygraph • Reports throughput, response time, hit ratio etc. from client’s viewpoint (but unaware of hierarchy) • Dummynet • Used to simulate networks of different capabilities by controlling bandwidth, latency and packet loss. • Squid cache and Squeezer log analysis tool • Captures cache cooperation info • Modified to monitor specific polygraph phases • Squeezer and Polygraph info has to be reconciled

7. Experimental Setup • Experiments performed on different cache hierarchies of two, three & four Squid caches. • Hardware configuration of all Squid machines is the same (800MHz, 256MB, 4 30GB disks) • Polygraph machines and caches on same 100Mbps switched ethernet network • Balanced workload • Cache “fill-up” phase not measured

8. List of Experiments • Performance with different cache hierarchies • Influence of network latency • Influence of cache size • Influence of the document sharing pattern • One big cache compared to multiple caches Virtually unlimited experiment space with many parameters (e.g., request rate, public interest, cache, memory size etc.)

9. List of Cache Hierarchies Cache Client 2OY 2SY 3OY Sibling-sibling Parent-child 3SY 1ON-2OY 1ON-2SY Same memory, disk per cache, fixed total request rate, no network delay 2SY-1OY 1OY-2SY 2OY-1OY

10. Benefit of peering Improved hit ratio Simulation Results - Different Hierarchies • Improved hit ratio overcomes overheads of peering • Parents appear less important than siblings

11. List of Experiments • Performance with different cache hierarchies • Influence of network latency • 2 and 3 Squid caches independent or as siblings • Network delay of 0 msecs, 40 msecs, or 80 msecs between caches • Influence of cache size • Influence of the document sharing pattern • One big cache compared to multiple caches

12. Impact of Network Latency • Hit ratio unaffected by latency • Hit and Miss response times increase with latency • Some increase in response time going from 0 to 40 to 80 msec • Cache cooperation is helpful even with modest network delay

13. Conclusion • Web Polygraph based framework to evaluate cooperative caching: • Flexible • Works on a real network • Workload characteristics are easy to specify. • Repeatable experiments • Hit ratio and user response time based metrics • Captures actual cooperation overheads

14. Future Work • Make the toolset easily usable by the community – currently a recipe type help available • Evaluation of large hierarchies may need a combination of experimental and analytical methods • More results from the performance of different kinds of hierarchies in different scenarios