Title :
A flow-driven fast forwarding architecture for content centric networks
Author :
Azgin, Aytac ; Ravindran, Ravishankar ; Wang, Guoqiang
Author_Institution :
Huawei Research Center, Santa Clara, CA, USA
Abstract :
Content-centric Networking (CCN) promises significant advantages over the current Internet architecture by replacing its host-centric design with a content-centric one, and enabling innetwork caching and name-based forwarding. However, despite its advantages, wire-speed forwarding in CCN remains a challenge, as CCN uses stateful forwarding and requires lookups on packets carrying hierarchically structured and variable-length content names. As a result, storage and computing requirements to support name-based forwarding in CCN typically determines the forwarding capacity. In this paper, to address the forwarding scalability concerns in CCN, we propose an overlay forwarding architecture that utilizes flow-driven adaptive forwarding and tradeoffs between flexibility and scalability. The proposed architecture exploits the correlations in user traffic to create active flow states in content routers to bypass the default CCN forwarding for future requests. We present an indepth study of the proposed architecture and provide demonstrative results on its performance proving its scalability and effectiveness.
Keywords :
Computer architecture; Data mining; Indexes; Next generation networking; Routing; Scalability; System-on-chip;
Conference_Titel :
Communications (ICC), 2015 IEEE International Conference on
Conference_Location :
London, United Kingdom
DOI :
10.1109/ICC.2015.7249207