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Progressive Caching in CCNAuthors: Jason Min Wang, Brahim BensaouPublisher: GLOBECOM 2012Presenter: Chai-Yi ChuDate: 2013/05/08

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Introduction Proposed Caching Management Scheme◦Caching Decision Policy◦Replacement Strategies

Simulation◦ Experimental Methodology◦ Experiment Results

Outline

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propose a new caching scheme for such CCN networks and evaluate the in-network caching performance of this policy by comparing it with that of the default proposed policy via simulation.

Introduction

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Characteristics that have crucial influence on the caching performance

1. Locality of references2. Content popularity distribution3. One-time referencing4. Heavily-tailed object size distribution

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Caching Decision Policy◦Resemblance to the LCD algorithm (Leave Copy Down)◦Choosing the immediate downstream node of the cache hit

point as the primary candidate place to replicate the data packet.

Proposed Caching Management Scheme

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◦ : the number of interfaces saved in the PIT entry, that is, from how many distinct interfaces requests for the same namedchunk are aggregated.

◦ : the actual number of individual requests for p at an edge node.

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Replacement Strategies◦ Edge nodes

A modification of the Greedy Dual-size algorithm. Each cached chunk of data is associated with a value . : the hop count needed to fetch the packet. An “inflation” value .

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◦ Intermediate nodes Each cached chunk of data is associated with a value . Interface Diversity information will be recorded in and is used to leave

breadcrumbs on the access statistics of after it has been cached.

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Implemented a simplified CCN model on top of Omnet++◦ simulation model includes three basic components of CCN

i.e., CS, PIT and FIB◦ other features of CCN (e.g., hierarchical naming, routing,

security issues and so on) are not taken into account.

Simulation

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Experimental Methodology◦Network topology

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◦Workloads The synthetic Web workload generator ProWGen is used to

generate workloads for the two content servers.

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◦ Performance metric systematic hit gain : the distance between node and the original content server. : the amount of pending requests at edge nodes for the hitting

data. : the size of object (chunks). : the hop distance between node and the original content server

of object . The closer the value of G is to 1, the better the in-network

caching system performs.

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◦Methodology cache size

varied uniformly from 100 to 8,000 chunks for all nodes. The chunk size is set 10KB

request aggregation request aggregation time can change the observed access pattern

and thus impact the hit rates of the nodes. cache management scheme

1. alwayscache+LRU (the initial proposal of CCN2. proposed PCP+heterogeneous replacement algorithms

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Impacts of cache size and content popularity

Experiment Results

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Impact of request aggregation