1. USITS ‘01 The Age Penalty and its effect on cache performance Edith Cohen AT&T Labs-Research Haim Kaplan Tel-Aviv University Presenting: Edith Cohen

2. USITS ‘01 Distribution of Web Content Origin server cache Content of URL can be modified by the origin. Copies are cached throughout

3. USITS ‘01 HTTP Freshness Control Cached copies have: –Freshness lifetime –Age (elapsed time since fetched from origin) TTL (Time to Live) = freshness lifetime – age Expired copies must be validated before they can be used. Body (content) header Cache-directives

4. USITS ‘01 HTTP Cache Serving a Request No cached copy  GET a fresh copy   Stale cached copy  If-Modified-Since GET a fresh copy “Not-Modified”  update header   “Modified”  update content and header   Fresh cached copy   GET www.cnn.com/WEATHER/

5. USITS ‘01 “hits” and “misses” hit-rate metric: c-hit/(c-hit+c-miss) latency (c-miss) > latency (f-miss) >> latency (f-hit)   “hit-rate” does not capture freshness freshness-rate: f-hit/c-hit f-hitf-missc-miss remote RTTs XX content-transfer X “traditional”: c-hit ( hit )( miss )

6. USITS ‘01 “Value” of a Cached Copy Frequency/pattern of requests Size (storage cost) Fetching cost (latency/bandwidth) Modification rate (likelihood of c-miss) Age (likelihood of f-miss) Important issues for: replacement and pre-fetching strategies cascaded caches

7. USITS ‘01 Origin Server to User www.cnn.com reverse proxy proxy cache AS

8. USITS ‘01 Issues for Cascaded Caches Path between Web server and end-user often includes 2 or more caches.  downstream cache sends older copies  more misses at upstream caches – more traffic between caches – increased user-perceived latency

9. USITS ‘01 1:00pm Freshness-lifetime= 10 H Age = 0 Distributing Copies Origin server downstream cache upstream cache 7:00pm Freshness-lifetime= 10 H Age = 6 H Freshness-lifetime= 10 H Age = 9:59 H 10:59pm

10. USITS ‘01 Modeling Sources of a Cache “Cache” misses are forwarded to a cache Cache-2 www.cnn.com Cache Cache-1 “Origin” misses are forwarded to authoritative (origin) server.

11. USITS ‘01 Source Models… origin: age(t) = 0 cache: age(t) = T - (t+ a ) mod T Object with freshness-lifetime = T. The age of copy retrieved at time t is: Theorem: miss_origin(S) < miss_cache(S) < 2*miss_origin(S) Request sequence S Age-Penalty Definition:

12. USITS ‘01 …Age-penalty Requests: cache T t TTL origin mf-mh m

13. USITS ‘01 Trace-driven Simulations log OriginCachepenalty NLANR UC52%43%21% NLANR SD47%38%24% freshness-rate for different configurations

14. USITS ‘01 CDN server Content Delivery Network www.cnn.com AS

15. USITS ‘01 Content Delivery Networks CDN servers are a system of reverse proxy caches, placed throughout the Internet. Proprietary, non-HTTP, freshness control between origin and CDN servers, allowing for longer TTL durations. CDN www.cnn.com Cache HTTP freshness control Proprietary freshness control

16. USITS ‘01 CDN Age-Handling Practices Practice: “Intact headers” CDN servers act as a cache, end-to-end headers are intact. (-3/2000). What are the implications? Practice: “emulate origin” CDN servers rewrite age to 0 (3/2000-present) Practice: “equate lifetime” CDN servers rewrite HTTP freshness lifetime is equated (extended) to “proprietary” freshness lifetime. How much can be gained?

17. USITS ‘01 …Implications of Intact Headers  Age = time on CDN server  copies often served with 0 TTL!

18. USITS ‘01 …Implications of Intact Headers CDNNLANR log %requestsFreshness-rate CDNorigin SandpiperUC0.4%5%76% SandpiperSD0.5%6%67% AkamaiUC1.7%5%61% AkamaiSD1.1%6%63%

19. USITS ‘01 …..Equating Lifetimes How much can be gained? We estimate about 20% of requests to CDN (Akamai) servers would be eliminated.

20. USITS ‘01 Conclusion Content-aging can have significant performance effect on cascaded Web caches (25% decrease in effectiveness of cache hits). Aging effects are not being carefully accounted for (see CDN practices). Content-aging warrants more awareness by practitioners, and more research...

21. USITS ‘01 Follow-up Work More “source” types (e.g., alternating between several downstream caches) Pre-term refreshes by downstream cache (sporadic updates by downstream cache may decrease performance, but this can be avoided) Longer lifetime durations at upstream caches (tradeoff of staleness and latency) Rejuvenation by downstream caches (refresh “fresh” popular copies to set their age to 0). Proper use can improve performance, but otherwise can decrease performance (!!!)…