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Aging Through Cascaded Caches: Performance Issues in the Distribution of Web Content. Edith Cohen AT&T Labs-research. Haim Kaplan Tel-Aviv University. HTTP Freshness Control. Cached copies have: Freshness lifetime Age (elapsed time since fetched from origin) TTL (Time to Live) =

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Aging Through Cascaded Caches:Performance Issues in the Distribution of Web Content.

Edith Cohen

AT&T Labs-research

Haim Kaplan

Tel-Aviv University

Stanford Networking Seminar


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 (request constitutes a ”cache miss”).

Cache-directives

header

Body

(content)

Stanford Networking Seminar


Aging of Copies

8:00am

Origin server

Age = 0

TTL = 10

Freshness Lifetime

= 10 hours

Stanford Networking Seminar


Aging of Copies

12:00pm

3:00pm

Origin server

Age = 4

TTL = 6

Age = 7

TTL = 3

9:00am

Age = 1

TTL = 9

Freshness Lifetime

= 10 hours

Stanford Networking Seminar


Aging of Copies

Origin server

Age = 10

TTL = 0

6:00pm

Freshness Lifetime

= 10 hours

Stanford Networking Seminar


Aging thru Cascaded Caches

8:00am

origin server

Age = 0

TTL = 10

proxy caches

reverse-proxy cache

Stanford Networking Seminar


Aging thru Cascaded Caches

origin server

proxy caches

5:00pm

reverse-proxy cache

Age = 9

TTL = 1

Stanford Networking Seminar


Aging thru Cascaded Caches

origin server

Age = 10

TTL = 0

proxy caches

6:00pm

reverse-proxy cache

!! !!

Stanford Networking Seminar


Aging thru Cascaded Caches

origin server

Age = 0

TTL = 10

proxy caches

6:00pm

reverse-proxy cache

Stanford Networking Seminar


TTL of a Cached Copy

M

M

M

TTL

From Origin

M

M

From Cache

Freshness-lifetime

Requests

at client

cache:

t

Stanford Networking Seminar


Age-Induced Performance Issues for Cascaded Caches

  • Caches are often cascaded (path between web server and end-user includes 2 or more caches.).

  • Copies obtained thru a cache are less effective than copies obtained thru an origin server.

    Reverse proxies increase validation traffic !!

  • More misses at downstream caches mean:

    • Increased traffic between cascaded caches.

    • Increased user-perceived latency.

Stanford Networking Seminar


Research Questions

  • How does miss-rate depend on the configuration of upstream cache(s) and on request patterns ?

  • Can upstream caches improve performance by proactively reducing content age ? how?

  • Can downstream caches improve performance by better selection or use of a source?

Our analysis:

  • Request sequences: Arbitrary, Poisson, Pareto, fixed-frequency, Traces.

  • Models for Cache/Source/Object relation: Authoritative, Independent, Exclusive.

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Basic Relationship Modelscache/source/object

www.cnn.com

Cache-A

Cache-B

Cache-C

Cache-D

Cache-3

Cache-2

Cache-1

  • Authoritative: “Origin server:” 0 age copies.

  • Exclusive: all misses directed to the same cache.

  • Independent: each miss is directed to a different independent upstream cache.

Stanford Networking Seminar


Basic Models…

Object has fixed freshness-lifetime of T. Miss at time t results in a copy with age:

  • Authoritative age(t) = 0

  • Exclusive age(t) = T - (t+a) mod T

  • Independent age(t) e U[0,T]

Theorem:On all sequences, the number of misses obeys:

Authoritative<Exclusive<Independent

Theorem: Exclusive< 2*Authoritative

Independent < e*Authoritative

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TTL of “Supplied” Copy

Authoritative

Exclusive

Independent

Source:

TTL

Freshness-lifetime

Requests

Received

at source:

t

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How Much More Traffic?

Miss-rate for different configurations

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Rejuvenation at Source Caches

client

no rejuv.

Rejuvenation: refresh your copy pre-term once its TTL drops below a certain fraction v of the Lifetime duration.

TTL

v=0.5

source

24h

12h

t

Requests at client:

Stanford Networking Seminar


Rejuvenation’s Basic Tradeoff:

  • Increases traffic between upstream cache and origin (fixed cost)

  • Decreases traffic to client caches (larger gain with more clients)

Downstream

Client caches

Upstream

cache

origin

Is increase/decrease monotone in V (?)

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Interesting Dependence on V…

  • Independent(v) <> Exclusive(v)

  • Independent(v) is monotone: if v1 > v2,

  • Independent(v1)>Independent(v2)

  • Exclusive(v) is not monotone

    • (miss-rate can increase !!)

  • Integral1/v (synchronized rejuvenation): Exclusive(v) < Independent(v) and is monotone (Pareto, Poisson, not with fixed-frequency).

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Stanford Networking Seminar


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How Can Non-integral 1/v Increase Client Misses?

Requests at

Client cache:

Copy at client is not synchronized with source.

When it expires, the rejuv source has an aged copy.

TTL

Upstream Cache

Downstream Client Cache

Pre-term

refreshes

Freshness-lifetime

t

Stanford Networking Seminar


Why Integral 1/v Works Well?

Requests at

Upstream cache:

Cached copies remain synchronized

TTL

Upstream Cache

v=0.5

Downstream Client Cache

Pre-term

refreshes

Freshness-lifetime

t

Stanford Networking Seminar


Some Conclusions

  • Configuration: Origin (“Authoritative”) is best. Otherwise, use a consistent upstream cache per object (“Exclusive”).

  • “No-cache” request headers: resulting sporadic refreshes may increase misses at other client caches. (But it is possible to compensate…).

  • Rejuvenation: potentially very effective, but a good parameter setting (synchronized refreshes) is crucial.

  • Behavior patterns: Similar for Poisson, Pareto, traces, (temporal locality). Different for fixed-frequency.

  • For more go tohttp://www.research.att.com/~edith

    Full versions of: Cohen, Kaplan SIGCOMM 2001

    Cohen, Halperin, Kaplan, ICALP 2001

Stanford Networking Seminar


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