On sizing CCN content stores by exploiting topological information

D. Rossi (1, 2, 3) , Giuseppe Rossini (1, 2, 3)

1 LINCS - Laboratory of Information, Network and Communication Sciences
2 RMS - Réseaux, Mobilité et Services
3 INFRES - Département Informatique et Réseaux

In this work, we study the caching performance of Content Centric Networking (CCN), with special emphasis on the size of individual CCN router caches. Specifically, we consider several graph-related centrality metrics (e.g., betweenness, closeness, stress, graph, eccentricity and degree centralities) to allocate content store space heterogeneously across the CCN network, and contrast the performance to that of an homogeneous allocation. To gather relevant results, we study CCN caching performance under large cache sizes (individual content stores of 10 GB), realistic topologies (up to 60 nodes), a YouTube-like Internet catalog (108 files for 1PB video data). A thorough simulation campaign allow us to conclude that (i) , the gain brought by content store size heterogeneity is very limited, and that (ii) the simplest metric, namely degree centrality, already proves to be a “sufficiently good” allocation criterion. On the one hand, this implies rather simple rules of thumb for the content store sizing (e.g., “if you add a line card to a CCN router, add some content store space as well”). On the other hand, we point out that technological constraints, such as line- speed operation requirement, may however limit the applicability of degree-based content store allocation.

Domaines: Réseaux et télécommunications [cs.NI]

D. Rossi, Giuseppe Rossini. On sizing CCN content stores by exploiting topological information. IEEE INFOCOM, NOMEN Worshop,, Mar 2012, Orlando, United States. pp.280-285. ⟨hal-00795820⟩