A constructive review of in network caching a core functionality of icn slides

A Constructive Review of In-Network
Caching: A Core Functionality of ICN*
Anshuman Kalla
1Anshuman Kalla
* A. Kalla and S. K. Sharma, "A constructive review of in-network caching: A core functionality
of ICN," 2016 International Conference on Computing, Communication and Automation
(ICCCA), Noida, 2016, pp. 567-574. DOI: 10.1109/CCAA.2016.7813785
Square brackets ‘[ ]’ denotes the reference number as per the reference list in the paper

Introduction
• ICN conceives caching at network layer as one of the
indispensable core functionalities of ICN
– beyond the premise of end-to-end principle
2Anshuman Kalla

Introduction
• Moreover, ICN advocates named-contents instead of
named-hosts
3Anshuman Kalla

Introduction
• Moreover, ICN advocates named-contents instead of
named-hosts
• Together the two functionalities result in content-
aware in-network caching is configured
4Anshuman Kalla

Introduction
• The idea is to allow caching at network layer
– That is routers are configured with Content Stores (cache facility)
that enable them to cache the contents traversing them
5Anshuman Kalla

Introduction
• The idea is to allow caching at network layer
– That is routers are configured with Content Stores (cache facility)
that enable them to cache the contents traversing them
• Thus every node, in addition to routing, buffering and
forwarding operations
– should perform caching of (traversing) contents
6Anshuman Kalla

Review of Literature
March 7, 2017 7Anshuman Kalla
Factors Affecting In-Network Caching
Aim of review of
In-Network Caching
Relevant Performance Metrics
Network Topologies Exploited
Traffic Patterns Fed
Simulators Available for Evaluation
Issues Related to In-Network Caching
Advantages of In-Network Caching

Issues Related to TCP/IP Networking [1],[2]
1. Data Dissemination & Service Access (prominent usage today)
– Current networking was tailored to share networking resources
Anshuman Kalla 8* See paper for all the references

2. Named Hosts (i.e. IP address do actually exist in current network)
– Content name (identifier) IP address (locator) i.e. DNS lookup

3. Mobility (was least imagined when TCP/IP was designed)
– Leads to intermittent connectivity results in change in IP

4. Availability (of content and/or service with min. possible latency)
– Dependent on node/link/server state

5. Security (implies comm. over secured channel & trusted server)
– So far implemented at network-level but missing at content-level

5. Security (implies comm. over secured channel & trusted server)
– So far implemented at network-level but missing at content-level
6. Flash Crowd leads to congestion, DoS, poor QoS etc.

The Trend For Problem Solving
• Dedicated patch(es) for each problem encountered (for ex.)
– CDN and P2P for data dissemination
– DNS for Named Host (i.e. to resolve any name to IP address)
– MobileIP for mobility
– DNSSec and IPSec for security
– Web caching or CDN for availability
Anshuman Kalla 14

• These patches/fixes are add-on (not integral)
– Thus transforming TCPIP networking into complex & delicate architecture
Anshuman Kalla 15

• Shift in primary usage of networking facility
– Instead sharing of network resources prime usage is content centric
Anshuman Kalla 16

• Shift in primary usage of networking facility
– Instead of sharing network resources prime usage is content centric
• Lately researchers realized need for clean-slate approach
– To reconcile all the issues (and shift in usage) in a unified manner
Anshuman Kalla 17

Core Functionalities of ICN
• Named content
• In-network caching
• Named based routing
• Data-level security
• Multi-path routing
• Hop-by-hop flow control
• Pull-based communication
• Adaptability to Multiple simultaneous connectivities
Anshuman Kalla 18

Core Functionalities of ICN
• Named content
• In-network caching
• Named based routing
• Data-level security
• Multi-path routing
• Hop-by-hop flow control
• Pull-based communication
• Adaptability to Multiple simultaneous connectivities
Anshuman Kalla 19

Types of In-Network Caching in ICN
In-Network Caching
Off-Path Caching Edge CachingOn-Path Caching
Hybrid Caching

• On-Path Caching
– Caches the retrieved contents at the intermediate nodes that fall on
the (symmetrical) way back from server to the requester
– Thus interest taps nodes falling on-the-path from requester to server

• On-Path Caching
• Off-Path Caching
– Appoints node(s) as a dedicated cache(s) for a retrieved content
– Selected caches have no contrived correlation with the nodes that
fall on the path being followed by interest to reach the server

• On-Path Caching
• Off-Path Caching
– Appoints node(s) as a dedicated cache(s) for a retrieved content
– Selected caches have no contrived correlation with the nodes that
fall on the path being followed by interest to reach the server
• Edge Caching
– Opposes pervasive in-network caching
– Only the nodes at the boundary of a network are enabled with
caching capability

Interest Packet
Data Packet
R8 R7 R6
R1
R2
R3R4
R5
R1
R2
R3R4
R5
R8 R7 R6
R1
R2
R3R4
R5R8 R7 R6
Nodes that could cache data
On-Path Caching
(R1, R2, R3, R6 – On-Path Caches)
Off-Path Caching
(R4 – Designated Off-Path Cache)
Edge Caching
(R6 – Edge Cache)

Advantages of In-Network Caching in ICN
1. Cost Effective Data Retrieval
– Minimizes delegation of traffic for cached contents over egress links
– Thereby minimizes traffic over expensive external links and server load

2. Reduction in Latency
– Since contents are cached at comparatively closer intermediate nodes
– Thereby improves Quality-of-Service (QoS) perceived by users

3. Heavy Load Handling
– Caching transforms nodes into legitimate proxies of origin server
– Thereby inherently tackles heavy load situations like flash crowd

3. Heavy Load Handling
– Caching transforms nodes into legitimate proxies of origin server
– Thereby inherently tackles heavy load situations like flash crowd
4. Efficient Retransmissions
– Caching allows retransmission of content’s cached copy from closest node
– Thereby ensures better resiliency to packet losses

5. Higher Availability
– More legitimate proxies of server i.e. caches improves content availability
– Thereby reduces the probability of Denial of Service (DoS) attack

5. Higher Availability
– More legitimate proxies of server i.e. caches improves content availability
– Thereby reduces the probability of Denial of Service (DoS) attack
6. Buoyancy to Intermittent Connectivity
– Caching inherently allows to sustain intermittent connectivity
– Also allows mobile nodes to act as a network medium for areas
uncovered by network

Issues Related to In-Network Caching in ICN
1. Cache Placement or Allocation
– Where to place the caches (i.e. content stores)?
– That is caching facility at all or selected nodes in a network
– Edge nodes / core nodes / central nodes / strategically selected nodes

2. Cache Size Dimensioning
– What should be the size of caches?
– That is allowing homogeneous or heterogeneous caches
– In case of heterogeneous where to boost cache size comparatively

2. Cache Size Dimensioning
– What should be the size of caches?
– That is allowing homogeneous or heterogeneous caches
– In case of heterogeneous where to boost cache size comparatively
3. Content Placement
– Where to cache a retrieved content within a network?
– That is where to cache the retrieved content to improve performance
– Centralized or decentralized manner (explicit or implicit coordination)

4. Content Selection
– What to cache out of huge flow of contents?
– That is to identify profitable contents from content catalog for caching
– Could be performed event after content placement if the placement
mechanism is oblivious of content’s utility characteristics

4. Content Selection
– What to cache out of huge flow of contents?
– That is to identify profitable contents from content catalog for caching
– Could be performed event after content placement if the placement
mechanism is oblivious of content’s utility characteristics
5. Replacement policy
– Which cached-content should be evicted to accommodate an incoming
content?
– That is when cache is full then which residing content to be evicted to
cache the retrieved content

Factors Affecting In-Network Caching in ICN
1. Network topology
– Its cognizance might be crucial for performing caching

1. Network topology
2. Size of Content Population (Content Catalog)
– Total number of distinct contents for which request could be received

1. Network topology
3. Popularity Distribution
– Plays vital role but popularity estimation is itself a challenging task

1. Network topology
4. Popularity Dynamics
– Percentage and/or frequency of change in popularity of contents

1. Network topology
4. Popularity Dynamics
– Percentage and/or frequency of change in popularity of contents
5. Latency
– In terms of hop-count or distance, used to trigger caching decision

6. Bandwidth
– Available over retrieval path is another factor used for caching decision

6. Bandwidth
7. Cache size per node
– Homo or heterogeneous sized caches to analyze caching performance

6. Bandwidth
8. Granularity of content
– Entire object or packet or chunk – granularity may affect performance

6. Bandwidth
9. Size of Content
– Homogeneous (small or large sized) or heterogeneous sized contents

6. Bandwidth
9. Size of Content
– Homogeneous (small or large sized) or heterogeneous sized contents
10.Pricing (Cost involved in fetching contents)
– In order to prioritize caching of costlier contents

11. Mobility
– Movement tendency of users for pre-fetching based caching

11. Mobility
12. Routing
– Multipath routing affects the caching performance differently

11. Mobility
12. Routing
13. Spatial Locality
– Accessing tendency of user in a geographical area for caching decisions

11. Mobility
12. Routing
13. Spatial Locality
– Accessing tendency of user in a geographical area for caching decisions
14. Social Networking
– Caching of contents accessed or produced by socially active & influential
users

Performance Metrics For In-Network Caching
1. Hit Ratio
– Number of satisfied requests by caching to total number of requests
– Higher is hit ratio better is the caching performance

1. Hit Ratio
2. Bandwidth Usage
– Implies usage of expensive external links as well as internal links
– Lower bandwidth usage implies better caching performance

1. Hit Ratio
2. Bandwidth Usage
3. Cache Load
– Number of contents to be cached by a content store
– Homo or heterogeneously loaded cached
– Later leads to unbalanced caches & creation of hot spots

1. Hit Ratio
2. Bandwidth Usage
3. Cache Load
– Number of contents to be cached by a content store
– Homo or heterogeneously loaded cached
– Later leads to unbalanced caches & creation of hot spots
4. Server Load
– Number of content-requests arriving at original server
– Lower the server load better will be service providedAnshuman Kalla 53

5. Latency
– Implies delay encountered in retrieving a requested content
– Lower latency boosts Quality-of-Experience (QoE) perceived by users
– Thus reduction in latency achieved is used to gauge caching performance

5. Latency
6. Cache Diversity
– Implies number of unique contents residing in network caches
– Higher cache diversity improves overall performance

5. Latency
6. Cache Diversity
7. Complexity & Overheads
– Caching needs to be simple, light-weight and practically deployable

5. Latency
6. Cache Diversity
7. Complexity & Overheads
– Caching needs to be simple, light-weight and practically deployable
8. Fairness
– In terms of content selection fairness, link load fairness, popularity
estimation fairness etc.

9. Resiliency to DoS Attack
– Network caching transforms caches into legitimate proxies of origin server
– Thus caches collectively handles DoS attack by divide-and-conquer rule

Real Network Topologies
• Abilene [14]
• Rocketfuel [12]
• CERNET2 [9]
• CAIDA [10]
• CRAWDAD [15]
• CERNET [16]
Anshuman Kalla 59
• GEANT [17]
• Tiger [18]
• GARR [19]
• WIDE [20]
• PlanetLab [21]
* See paper for all the references

Fabricated Network Topologies
• Barabasi-Albert (BA) Power Law Model [11]
• Watts-Strogatz (WS) Model [13]
• Boston university Representative Internet Topology
gEnerator (BRITE) Tool [22]
• Gorgia Tech -Internetwork Topology Models (GT-ITM)Tool
[23]
• Internet Topology Generator (INET) Tool [24]

Traffic Patterns
• Synthetic traffic workload have been generated using
– Zipf distribution (α ranging between 0.6 to 1.8) and
– Zipf-Mandelbrot distribution (with different value of α and q)
• Real traffic traces that have been used are
– P2P Workload [36]
– LastFM [32]
– Facebook data [33]

Network Simulators For ICN
• ccnSim simulator [25]
• CCNx simulator [26]
• OPNET simulator [27]
• CCNPL simulator [28]
• OMNET++ simulator [29]
• ICARUS simulator [30]
• NEPI simulator [31]

References
The reference list remains the same that is used in the original paper

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