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CCNxCon2012: Poster Session:On a Novel Joint Replicating and Caching Strategy for Content-Centric Networks
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CCNxCon2012: Poster Session:On a Novel Joint Replicating and Caching Strategy for Content-Centric Networks


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On a Novel Joint Replicating and Caching Strategy for Content-Centric Networks …

On a Novel Joint Replicating and Caching Strategy for Content-Centric Networks
Leila Ghazzai, Yassine Hadjadj-Aoul, Adlen Ksentini (IRISA Lab.), Guillaume Bichot, Stephane Gouache (Technicolor), Abdelfettah Belghit (ENSI)

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  • 1. L.GHAZZAI 1 Y.HADJADJ-AOUL 1 A.KSENTINI 1 G.BICHOT 2 S.GOUACHE 2 A.BELGHIT 3 1 University of Rennes 1 2 Technicolor 3 University of ManoubaOn a novel joint replicating and caching strategy for content centric networks Portal Device  with  caching   ABSTRACT support  (e.g.  Router,   DSLAM,   ) STB  with  possible   caching  support The rise of popularity of video services has resulted in increased volumes of network traffic that, in turn, has created bottlenecks in the networks causing degradations of the perceived quality. CDN   The CCN paradigm is considered as one of the most surrogate prominent solution to address such issue. However, the cascaded LRU caches introduced by CCN presents some limits. In this work, we first analyze such limits. Then, we propose a new caching and replication strategy to optimize resources utilization and to maximize the number of different chunks existing within the intra domain. Fig.1  Intra-­‐Domain  Architecture Fig.2  Popularity  vs.  Number  of  Nodes Number of Nodes Content replication vs. caching in CCN 18 16Early, in-network caching was proposed as a mean to get the 14 contents closer to the end-users. With the shift towards 12 content-centric networking (CCN), this logic is pushed further. 10 CCN introduces two distinct techniques: contents caching and 8 replication. However, one should consider the mutual impact existing between these techniques. Indeed, the benefits of 6 contents replication can be completely cancelled with a 4 bad caching technique (see Fig. 3). 2 Popularity 0 0 5E-­‐11 1E-­‐10 1,5E-­‐10 2E-­‐10 2,5E-­‐10 Fig.3  Popularity  vs.  Delay 0,8 Limits of existing approaches Delay 0,7 0,6 CCNs allow popular content to be present in many nodes to make 0,5 the content closer to the end users (see Fig. 2). However, the 0,4 use of LRU as a caching strategy deceases the duration of 0,3 the contents presence in caches. 0,2 Some changes should be introduced to the classical CCN 0,1 architecture by focusing on: (i) reducing the amount of 0 replica in the intra-domain; (ii) storing as many various data Popularity 0 5E-­‐11 1E-­‐10 1,5E-­‐10 2E-­‐10 2,5E-­‐10 as possible. A Combined caching and replication Each CCN node, in the path to the destination, stores the chunk using this probability. technique The proposed caching technique, combines the benefits of Initially affect to each piece of data (i.e. chunk), to be Least Recently Used (LRU) and Least Frequently Used (LFU) transmitted, a nonzero storage probability depending notably on solutions. the chunk s popularity P. If a CCN node decides to store a particular chunk, it puts P0 = min [ max (( i) , 0) , 1] P= its storage probability to zero (or reduce the probability) to PK = min[max(PK-1 + S /N , 0) , 1]where i : popularity of the chunk i. S = 1 if the chunk have been avoid multiple duplication of the same content. Otherwise, stocked, 0 else. the probability is increased. Acknowledgement The work is partially supported by the national French project ANR VERSO ViPeer.