Time-Shifted TV in Content Centric Networks: the Case for Cooperative In-Network Caching

Time-Shifted TV in
Content Centric
Networks
the Case for Cooperative
In-Network Caching
Zhe LI and Gwendal SIMON

Context
Routers with cache (or Content Routers or CR)
an opportunity to revisit content delivery
a key element of content centric network

2 / 11 Z. Li and G. Simon Time-shifted TV in content-centric networks

Context
Routers with cache (or Content Routers or CR)
an opportunity to revisit content delivery
a key element of content centric network

Motivations for ISP :
minimize incoming video traﬃc
enter the Content Delivery Network game
reduce overall traﬃc on intra-ISP links


Our Focus : Time-shifted TV
Principles :
a show broadcasted at t is available at any t + x
let’s surf the TV channel
the killer app of connected TV


Our Focus : Time-shifted TV
Principles :
a show broadcasted at t is available at any t + x
let’s surf the TV channel
the killer app of connected TV

A nightmare for TV broadcasters
clients skip ads
the cost of servers that both ingest and deliver
a service that is (yet) not well mastered by CDN


Objective : maximize in-network hit-ratio
Inputs (or hypothesis) :
TV channel : a series of chunks (e.g. 1 min video)
each CR reserves storage for time-shifted service
CCN implemented !


Objective : maximize in-network hit-ratio
Inputs (or hypothesis) :
TV channel : a series of chunks (e.g. 1 min video)
each CR reserves storage for time-shifted service
CCN implemented !

Constraints on in-network caching policies
distributed and based on local information
deployed (but not managed) by network operators
dealing with many small storage capacities
not aﬀecting the simplicity of CCN routing

Our idea
Least Recently Used (LRU) → collaborative LRU
every CR manages one chunk every k chunks
cooperation among linked CRs

CCN with LRU CCN with collaborative cache


Our contributions
A distributed algorithm : assigning “labels” to CRs
a NP-complete problem
a 3 k − 2 approximate algorithm
2
5


Our contributions
A distributed algorithm : assigning “labels” to CRs
a NP-complete problem
a 3 k − 2 approximate algorithm
2
5

A set of simulations from an augmented CCN
the description of the new CCN protocol
the evaluation of performances


Initialization phase : assign labels to CR

sorted list nearest neighbors
2 1,4,5
3 1,8,16
1 2,3,16
6 8 3,11,12
7 5 1,2,4
11 8,12,13
10 4 2,5,7
16 1,3,5
13 4 12 8,9,11
15 2
15 1,10,11
5 10 2,6,15
1 18 14 3,16,17
11
17 5,14,16
8 3 13 11,12,15
16 7 2,4,6
12
6 2,7,10
9 8,12,14
17 18 4,5,17
14
9



2 1,4,5
3 1,8,16
1 2,3,16
6 8 3,11,12
7 5 1,2,4
11 8,12,13
10 optimized 4
16
2,5,7
1,3,5
13 4 12 8,9,11
15 2
15 1,10,11
5 10 2,6,15
1 18 14 3,16,17
11
17 5,14,16
8 3 13 11,12,15
16 7 2,4,6
12
6 2,7,10
9 8,12,14
17 18 4,5,17
14
9



2 1,4,5
3 1,8,16
1 2,3,16
6 8 3,11,12
7 5 1,2,4
11 8,12,13
10 4 2,5,7
16 1,3,5
13 4 12 8,9,11
15 2
15 1,10,11
5 10 2,6,15
1 18 14 3,16,17
11

8 3
optimized 17
13
5,14,16
11,12,15
16 7 2,4,6
12
6 2,7,10
9 8,12,14
17 18 4,5,17
14
9



2 1,4,5
conﬂict 3 1,8,16
1 2,3,16
6 8 3,11,12
7 5 1,2,4
11 8,12,13
10 4 2,5,7
16 1,3,5
13 4 12 8,9,11
15 2
15 1,10,11
5 10 2,6,15
1 18 14 3,16,17
11
17 5,14,16
8 3 13 11,12,15
16 7 2,4,6
12
6 2,7,10
9 8,12,14
17 18 4,5,17
14
9

saved but colored


2 1,4,5
conﬂict 3 1,8,16
1 2,3,16
6 8 3,11,12
7 5 1,2,4
11 8,12,13
10 4 2,5,7
16 1,3,5
13 4 12 8,9,11
15 2
15 1,10,11
5 10 2,6,15
1 18 14 3,16,17
11
17 5,14,16
8 3 13 11,12,15
16 7 2,4,6
12
6 2,7,10
9 8,12,14
17 18 4,5,17
14
9

saved and uncolored


2 1,4,5
3 1,8,16
1 2,3,16
6 8 3,11,12
7 5 1,2,4
11 8,12,13
10 4 2,5,7
16 1,3,5
13 4 12 8,9,11
15 2
15 1,10,11
5 10 2,6,15
1 18 14 3,16,17
11
17 5,14,16
8 3 13 11,12,15
16 7 2,4,6
12
6 2,7,10
9 8,12,14
17 18 4,5,17
14
9

colored by node 10


2 1,4,5
3 1,8,16
1 2,3,16
6 8 3,11,12
7 5 1,2,4
11 8,12,13
10 4 2,5,7
16 1,3,5
13 4 12 8,9,11
15 2
15 1,10,11
5 10 2,6,15
1 18 14 3,16,17
11
17 5,14,16
8 3 13 11,12,15
16 7 2,4,6
12
6 2,7,10
9 8,12,14
17 18 4,5,17
14
9

only node uncolored


2 1,4,5
3 1,8,16
1 2,3,16
6 8 3,11,12
7 5 1,2,4
11 8,12,13
10 4 2,5,7
16 1,3,5
13 4 12 8,9,11
15 2
15 1,10,11
5 10 2,6,15
1 18 14 3,16,17
11
17 5,14,16
8 3 13 11,12,15
16 7 2,4,6
12
6 2,7,10
9 8,12,14
17 18 4,5,17
14
9

choose farthest color

Simulation environment
ISP network conﬁguration :
rocketfuel E-bone topology with 87 CR
5 servers located near Point of Presence routers
130 chunks in every CR
augmented CCN protocol

Time-shifted TV streaming :
200 clients and 6 channels
usage extracted from Nielsen measurements 1
1. Three Screen Report Q1, Nielsen Company, June 2010.

Diversity of chunks into the whole network

With k = 6, the system caches 60% more diﬀerent chunks than basic LRU.


ISP Friendliness

The overall cross-domain traﬃc is reduced by 60%.


Future Works
Improve the evaluation
deploy the augmented CCN on network platforms
use real traces of time-shifters


Future Works
Improve the evaluation
deploy the augmented CCN on network platforms
use real traces of time-shifters

Toward new in-network caching policies
theoretical framework for policy analysis
play with CR : behavior and capacity


Time-Shifted TV in Content Centric Networks: the Case for Cooperative In-Network Caching

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Time-Shifted TV in Content Centric Networks: the Case for Cooperative In-Network Caching