Class Presentation, Distributed System

1. Caching in Information Centric
Network (ICN)
Presented by: Priagung Khusumanegara

2. Outline
 Introduction
 Characteristics of caching in ICN
 Transparent
 Ubiquitous
 Fine Granularity
 Caching optimization in ICN
 Dimensioning
 Decision policy
 Challenges and future research2

3. Introduction
One of the important features of ICN is
caching
 Speed up content distribution
 Improve network resource utilization
Characteristics of caching in ICN
 Transparent
 Ubiquitous
 Fine granularity3

4. Transparent
 Making its routing and caching decisions on unified content
names, essentially making these names network aware.
 Several Challenges:
 Inconsistency between caching objective
 ICN should make reasonable choice of its caching objective to
balance between diverse traffic types.
 Cross-application competitive sharing of cache space
 Different types of traffic differ significantly in their population
scale, object size and object popularity.
 ICN have to be able to efficiently share cache resources
between different traffic types.
 Line rate operation of caches
 The cache management quite different from traditional disk-
based management.
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5. Ubiquitous
 Topology of the cache network evolves from hierarchical trees to arbitrary
graphs.
 ICN more dynamics because its general cache network topology, ubiquity of
in network caches and volatility of cached content.
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Traditional Caching System
Focus on
Hierarchical Tree
Evolution
Information Centric Network
Focus on
Arbitrary Graph

6. Fine Granularity
 Different options for the granularity of caching:
 File-level
o Caching individual files as transmitted through the network
o Typical size 1.5 Kb each – as proposed by CNN
 Chunk-level
o Caching information chunks
o An information object is split into a number of fixed-size
information chucks – as proposed by ICN
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7. Fine Granularity (Cont’d)
Change of cache unit raises the following issues:
 Change of popularity
o Different chunks of a single file can have different access frequencies.
 Failure of independent reference assumption
o Traditional file-based caches are based on independent reference
model
o Requests for different chunks of the same file are often correlated, e.g.
in sequential order
 Opportunity for more efficient use of the cache space
o It possible to retrieve different parts of the same file from different
nodes, which speeds up the retrieval rate and improves the space
utilization.
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8. Techniques for ICN performance
optimization
 Focus on:
– Cache dimensioning
– Cache decision policy
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9. Cache Dimensioning
- Since ICN cache should operate at line rate, the cache
size that can be installed at each caching node is thus
limited.
- There are two issues that remain to be addressed:
 How large the cache space should be to have noticeable
performance improvement?
o Preferred to configure the cache size based on the router’s
performance disparity.
 How to allocate the storage resource across different cache nodes?
o Degree based allocation: the cache capacity allocated to a node
is proportional to its node degree.
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10. Cache Decision Policy
 Cache decision policy
– It determines which objects are to be placed at
which cache nodes.
– Two kinds of cache decision policy
 Explicit cache coordination decision
 Implicit cache coordination
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11. Explicit Cache Coordination
 Object access pattern, cache network topology and
each cache’s state as input for the calculation of the
placement position of each object.
 Common approaches can be classified into
three categories:
– Global
– Path
– Neighborhood
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12. Explicit Cache Coordination
(Cont’d)
 Global coordination
– Involves all cache nodes
– Object placement based on network distance between
cache nodes and object access frequencies at each cache
node
 Path coordination
– Only involves the cache nodes along the path from the
request hit place to the requesting client
– e.g.: en-route web caching
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13. Explicit Cache Coordination
(Cont’d)
 Neighborhood coordination
– Coordination takes place among a node’s
neighborhood.
– E.g.: Cooperative In-Network Caching (CINC)
13 Figure: The operation of coordination in network caching (CINC)

14. Implicit Cache Coordination
 Each node does not need to know the state
information of other cache nodes
 LCE (leave copy everywhere)
– Copy the object at each node along the
downloading path
– Disadvantage: Degrade the performance of the
network and underutilize some of the network
resources.
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15. Implicit Cache Coordination
(Cont’d)
 Leave Copy Down (LCD):
– When a cache hit occurs, this scheme only
caches the object at the direct downstream node
– Avoid a large number of copies of the same
object15
Figure: LCD (Leave Copy Down)

16. Implicit Cache Coordination
(Cont’d)
 Move Copy Down (MCD):
– This scheme moves the object from the hit node
to its direct downstream node, and deletes the
object from the hit node.
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Figure: MCD (Move Copy Down)

17. Implicit Cache Coordination
(Cont’d)
 Copy with Probability
- The requested object is copied with a given
probability p at each node along the returning
path
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Figure: Copy with Probability

18. Implicit Cache Coordination
(Cont’d)
 Random Copy One
- The requested object is copied at one random
node along the returning path
18 Figure: Random Copy One

19. Implicit Cache Coordination
(Cont’d)
 Probability Cache
- The requested object is copied at each node with
a probability. But, for each node, the probability
varies.
19 Figure: Probability Cache

20. Correlation Between Cache
Decisions
- WAVE adjusts the number of chunks cached at
each node based on the file’s popularity
- When the number of requests for a file increases,
WAVE reacts with exponential increase in the
number of chucks cached for this file.
- A content router in WAVE explicitly sets the cache
indication mark
- Once the chunk is cached, the cache indication
mark is cleared.
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Figure: Operation of WAVE

21. Challenges and Future Direction
 Cache object popularity
– Establish the chunk- level object popularity model from prior knowledge
– Measure the chunk-level object popularity directly
 Correlation between requests and correlation-based
cache decision
– What is the inherent correlation between different requests,
– How to model this correlation, and
– How to optimize the cache decision policy based on the request
correlation,
 ICN friendly network topology
– What kind of network topology is suitable for ICN network.
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