age-based cooperative caching in information-centric networks
TRANSCRIPT
Age-based Cooperative Caching
Age-based Cooperative Cachingin Information-Centric Networks
Junxiao ShiApr 17, 2012
Contents
Background Age-based Cooperative Caching scheme Simulation Discussion
Background
In-network Caching
One of the most important commonalities of ICN designs is the universal caching.
In-network caching would improve performance.● Network delay and publisher load can be reduced
by having content requests satisfied at network edge as much as possible.
● Popular contents should be cached near the users.
CDN
In IP network, CDN is widely deployed to deliver HTTP contents.● Content is cached for time specified in Cache-
Control header's max-age field.
NDN
Every NDN router can cache contents, like a CDN node.● CCNx protocol defines the FreshnessSeconds field,
which serves the same purpose as max-age.
Cache Replacement
There isn't enough cache storage to keep every piece of content until they expire.
Cache is full, new content is coming, should I:● Remove some old content, and cache this one?● Don't cache this one?
Ideal Choice
It is desirable to distribute contents hierarchically in the network.● Most popular contents at the edge.● Less popular contents near the edge.● Least popular contents even further.
In this way, the aggregated cache hit rate of the network will be maximized.
Least Recently Used
Least Recently Used (LRU)● Keep track of “last
used” time for each cached content
● Content with earliest “last used” time is replaced by new content
Problem with LRU
Age-based Cooperative Caching
The Scheme
Dynamically configure content's age in an implicit cooperation manner among ICN routers.● Each replica has an age.● The replica obtains its age when it is added into the
cache.● The replica is removed from the cache when the
age expires.● Routers implicitly collaborate by modifying the age.
The Scheme
Age obeys the following rules:● The closer a replica is to the network edge, the
longer age it has.● The more popular a replica is, the longer age it has.
How the scheme works?
Age-based cooperation
Age decision
N contents C1,C
2,...,C
N with associated
popularity P1,P
2,...,P
N
The popularity weights can be formulated as
● Total popularity weights of all contents in the system is 1.
Popularity weights
weight i=Pi
∑ j=1,. .. , NP j
A Case Study
LRU, least recently used
ABC, age-based cooperative caching
Case Study Results
C1 delay 2 6 2 4
C2 delay 6 2 4 2
Average delay 4 4 3 3t si
t ci2
t ci1
DABC=∑i=1
4
t si /4=7
DLRU=∑i=1
2
t si /2=8with better age increment strategy
DABC '=∑i=3
4
t si /2=6
Simulation
CERNET2 topology
wkdlife.comserver
Trace information
One-month trace in 2011
● 76414 requests sent by 36432 users from 20 cities 8369 distinct URLs, access count distribution follows the Pareto
Principle
Subscribers in Beijing contribute a majority of the population
Top 25 URLs
Simulation methodology
Each user generates content requests according to a Poisson process of intensity 0.1 req/s
Caching schemes: ABC, LRU, FIFO
Router cache capacity: 100M
Size of content: 1M
Link delay: 10ms per hop
ABC: BASE_AGE=10 sec, MAX_AGE=60 sec
Result: aggregated network delay
∑i=1
UserCount
DelayOfUser i
UserCount
Result: end user delay
∑i=1
SimTime
∑j=1
rc i
DelayOfRequest j /rci
SimTime
Result: publisher load
Summary
There are significant gains through using ABC. The users will benefit from ABC as the total
download latency will be lowered. Content providers will be able to greatly reduce
the traffic to save bandwidth and computing resources.
Discussion
Consistency
CDN refresh API● POST http://ccms.chinacache.com/index.jsp
with a list of URLs to remove from caches
Internet contents are mostly static● Streaming service: contents will remain static during
their lifetime● Non-streaming service: a large portion of contents
do not change with time● Time critical applications: set a short, non-
increasing age
Paper shortcomings
Popularity weights is not known and cannot be accurately estimated, by network or publisher.
Case study and simulation is limited to one publisher and one user distribution.