Proposed Caching Management Scheme
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Transcript Proposed Caching Management Scheme
Authors: Jason Min Wang, Brahim Bensaou
Publisher: GLOBECOM 2012
Presenter: Chai-Yi Chu
Date: 2013/05/08
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Introduction
Proposed Caching Management Scheme
◦ Caching Decision Policy
◦ Replacement Strategies
Simulation
◦ Experimental Methodology
◦ Experiment Results
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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.
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Characteristics that have crucial influence on the
caching performance
1. Locality of references
2. Content popularity distribution
3. One-time referencing
4. 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.
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◦ 𝑑𝑝 : the number of interfaces saved in the PIT entry, that is,
from how many distinct interfaces requests for the same
namedchunk 𝑝 are aggregated.
◦ 𝑟𝑝 : 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 𝑝 is associated with a value 𝐻𝑝 .
𝐶𝑝 : the hop count needed to fetch the packet.
An “inflation” value 𝐿 = min 𝐻𝑞 .
𝑞
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◦ Intermediate nodes
Each cached chunk of data 𝑝 is associated with a value 𝐻𝑝 .
Interface 𝑓.
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Diversity information will be recorded in 𝑆𝑝 and 𝑆𝑝 is used
to leave breadcrumbs on the access statistics of 𝑝 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.
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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 𝐺 =
ℎ∈𝐻 𝑔ℎ
∗ 𝑛ℎ /
𝑖∈𝐶,𝑗∈𝑁𝑖 𝑠𝑗
∗ 𝑝𝑖𝑜𝑗
𝑔ℎ : the distance between node 𝑖 and the original content server.
𝑛ℎ : the amount of pending requests at edge nodes for the hitting
data.
𝑠𝑗 : the size of object 𝑗 (chunks).
𝑝𝑖𝑜𝑗 : the hop distance between node 𝑖 and the original content
server 𝑜𝑗 of object 𝑗.
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.
2.
alwayscache+LRU (the initial proposal of CCN
proposed PCP+heterogeneous replacement algorithms
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Impacts of cache size and content popularity
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Impact of request aggregation
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