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Cache Me If You Can
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You Are Here
Network
Encoder
Sender
Middlebox
Receiver
Decoder
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Cache Proxies for Web
A
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Hierarchical Caching
A
B
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Cooperative Caching
A B
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Distributed Caching
A B
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Streaming Media vs. Web Pages
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Video Access Pattern
by S. Acharya and B. Smith
Study at Lulea University, Sweden 55% complete, 45% stop very early High temporal locality
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Bimodal Distribution
10 30 50 70 90
% Played
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Zipf Distribution
log (Frequency)
log (rank)
Frequency = C/rankm
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Zipf Law
Frequency of English Words“the” “of” “to” “a”
City size
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Benefits of Caching
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Reduce Access Latency
:) :(
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Reduce Server Load
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Buy Some Time
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Reduce Client Buffer Size
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Type of Cache
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Types of Cache
Static caching
Dynamic cachingpatching buffer
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Static Caching
Cache “all or nothing” is badSplit video into segments of size
S
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If I am writing a survey Introduction
Differences between web and media caching
Video access pattern Benefits of caching
Different type of cache Proxy caching architecture
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Other Caching Issues
How to segment?Which segments to cache?When to fetch data?Who to fetch from?When cache is full, who to kick
out?How to measure popularity?Can cache adapt to popularity?
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Rest of the Lecture
Soccer – cooperative caching proxy
Silo, rainbow and cache token – distributed caching proxy
Mocha – with congestion control
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SOCCER
Self-organizing cooperative caching architecture
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How to segment?
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Effects of Size S
Large S : Low utilizationSmall S : Lots of gaps
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Prefix Caching Policy
1 Chunk = k segments
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Fetching Cache Data
B
A
Server
Client 2Client 1
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Option 2
B
A
Server
Client 2Client 1
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Option 3
B
A
Server
Client 2Client 1
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Issues
How to advertise?How to choose helper?
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How to Advertise?
Balance betweennetwork loadfreshness of information
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Scalable AdvertisementExpanding Ring Advertisement
163264128
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How to Choose Helper?Consideration for Static Cache
network distance (1,2,3,4)number of streams being served
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Static Cache
Cost for retrieving data from node X to node Y =
treamsCurrNumOfSreamsMaxNumOfSt
reamsMaxNumOfStYXDist
*),(
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Dynamic Caching
Need to consider the size of patching buffer
S
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Dynamic Caching
Nused
Nfetched = min(s, Nused + Δ)
S
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Dynamic Cache
Potential Waste = Nfetched/Nused
Integrate into overall cost
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Helper Selection
Helper ask other helpers to help if segments not found on local cache
Pick lowest cost helper
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If Static Cache
Retrieve to fill current gapMay pick different helpers for
different gaps
Should avoid frequent switching
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If Dynamic Cache
Stick to one helper
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Evaluations
SOCCER
Hierarchical Proxies
Single Proxy
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Silo, Rainbow and Cache Token
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Distributed Caching
B
A
Server
new clip!
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Distributed Caching
B
A
Server
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Distributed Caching
B
A
Server
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Distributed Caching
B
A
Server
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Cooperative vs DistributedCooperative caching caches
independentlyDistributed caching caches as a
team
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Problems
Who should cache what?
Which segment to kick out?
How to redistribute data?
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RCache
Np proxies
video of length Lv
divide into Ns equal segments
Each proxy caches each segment with a/Np probability
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Analysis
Probability that whole video is cached
Storage requirement aL
1ln
11
sNa
sN
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Two Parameters
How to divide video into segments?
What is the probability of storing each segment?
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Silo
segment size probabilityof storage
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Problems
Who should cache what?
Which segment to kick out?
How to redistribute data?
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Compute Popularity
For each videoFor each segment
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Rainbow Algorithm
less popular
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Problems
Who should cache what?
Which segment to kick out?
How to redistribute data?
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Data Redistribution
When popularity changes, need to redistribute.
Redistribute “on-demand” (lazy)
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Cache Token
Each segment have two bits(T,C)
T: I am suppose to have the segment C: I have the segment
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Data Redistribution
(T=1,C=1)(T=0,C=0)(T=1,C=0) (T=0,C=1)
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Silo, Rainbow and TokenDistributed Caching ArchitectureFault tolerantScalable
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Proxy Cache + Congestion Control
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Scenario (10am)
A
Server
Client 2
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Scenario (1am)
A
Server
Client 2
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Problem
Cache interfere with congestion control algorithm
Make cache adapt aware of quality adaptation
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Congestion Control ProtocolRAP: AIMD + Layered Coding
“sender-driven layered unicast”
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Solutions
Making cache “quality-aware”PrefetchReplacement Algorithm
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Cache Miss
A
Server
Client 2
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Cache Hit
A
Server
Client 2
repair +prefetch
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Peeking Inside the Cache
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Cache Hit: Repair
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Cache Hit: Prefetch
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Cache Hit: Prefetch
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Prefetch Algorithm
prefetchwindow
playbackpoint
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Proxy Request to ServerMultiple requests (for different
clients) are batched.
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Server Response
Missing segments are sent in decreasing priority
1
2
3 4
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Server Response
Send as many segments as possible until next prefetch request
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Solutions
Making cache “quality-aware”PrefetchReplacement Algorithm
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Goal of Replacement AlgorithmGoal: converge to efficient state
if a stream is popularaverage quality is highvariation in quality is low
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The Algorithm
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Trashing and Locking
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Choosing Victim
whit (weighted hit) =Tplay/Ttotal
Calculate whit for each layer in a stream over a popularity window
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Example
Popularity Lock? Name Layer
5.9 1 Nemo 0
4.3 1 Nemo 1
4.0 0 Matrix 2 0
3.9 0 Matrix 2 1
1.1 0 Gigli 0
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Evaluations
Two CriteriaCompletenessContinuity
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vs Request Number
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Different Popularity
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Summary
Proxy Caching for videoTechniques for segmentation,
replacement etc. Interactions with other aspect of
streaming
