TY  - JOUR
A1  - Sourlas, V
A1  - Psaras, I
A1  - Saino, L
A1  - Pavlou, G
KW  - Information-centric networks; Cache aware routing; Off-path in-network caching; Nodal clustering/partitioning; Hash routing
JF  - Computer Networks
UR  - http://dx.doi.org/10.1016/j.comnet.2016.04.001
SN  - 1389-1286
N2  - Hash-routing is a well-known technique used in server-cluster environments to direct content requests to the responsible servers hosting the requested content. In this work, we look at hash-routing from a different angle and apply the technique to Information-Centric Networking (ICN) environments, where in-network content caches serve as temporary storage for content. In particular, edge-domain routers re-direct requests to in-network caches, more often than not off the shortest path, according to the hash-assignment function. Although the benefits of this off-path in-network caching scheme are significant (e.g., high cache hit rate with minimal co-ordination overhead), the basic scheme comes with disadvantages. That is, in case of very large domains the off-path detour of requests might increase latency to prohibitive levels. In order to deal with extensive detour delays, we investigate nodal/domain clustering techniques, according to which large domains are split in clusters, which in turn apply hash-routing in the subset of nodes of each cluster. We model and evaluate the behaviour of nodal clustering and report significant improvement in delivery latency, which comes at the cost of a slight decrease in cache hit rates (i.e., up to 50% improvement in delivery latency for less than 10% decrease in cache hit rate compared to the original hash-routing scheme applied in the whole domain).
ID  - discovery1500862
N1  - Copyright © 2016 Elsevier B.V. All rights reserved. This is the preprint version of the article published in Computer Networks; the final Version of Record is available at http://dx.doi.org/10.1016/j.comnet.2016.04.001
AV  - public
SP  - 67
VL  - 103
Y1  - 2016/07/05/
EP  - 83
TI  - Efficient Hash-routing and Domain Clustering Techniques for Information-Centric Networks
ER  -