Progressive caching in ccn
This presentation is the property of its rightful owner.
Sponsored Links
1 / 20

Progressive Caching in CCN PowerPoint PPT Presentation


  • 68 Views
  • Uploaded on
  • Presentation posted in: General

Progressive Caching in CCN. Authors: Jason Min Wang, Brahim Bensaou Publisher: GLOBECOM 2012 Presenter: Chai-Yi Chu Date : 2013/05/08. Outline. Introduction Proposed Caching Management Scheme Caching Decision Policy Replacement Strategies Simulation Experimental Methodology

Download Presentation

Progressive Caching in CCN

An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -

Presentation Transcript


Progressive caching in ccn

Progressive Caching in CCN

Authors: Jason Min Wang, Brahim Bensaou

Publisher:GLOBECOM 2012

Presenter: Chai-Yi Chu

Date: 2013/05/08


Outline

Outline

  • Introduction

  • Proposed Caching Management Scheme

    • Caching Decision Policy

    • Replacement Strategies

  • Simulation

    • Experimental Methodology

    • Experiment Results


Introduction

Introduction

  • 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.


Progressive caching in ccn

  • Characteristics that have crucial influence on the caching performance

  • Locality of references

  • Content popularity distribution

  • One-time referencing

  • Heavily-tailed object size distribution


Proposed caching management scheme

Proposed Caching Management Scheme

  • 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.


Progressive caching in ccn

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

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


Progressive caching in ccn

  • 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 .


Progressive caching in ccn

  • 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.


Simulation

Simulation

  • 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.


Progressive caching in ccn

  • Experimental Methodology

    • Network topology


Progressive caching in ccn

  • Workloads

    • The synthetic Web workload generator ProWGen is used to generate workloads for the two content servers.


Progressive caching in ccn

  • 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.


Progressive caching in ccn

  • 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

      • alwayscache+LRU(the initial proposal of CCN

      • proposed PCP+heterogeneousreplacement algorithms


Experiment results

Experiment Results

  • Impacts of cache size and content popularity


Progressive caching in ccn

  • Impact of request aggregation


  • Login