Stream Reasoning-Based Control of Caching Strategies in CCN Routers
This work addresses caching inefficiencies in CCN routers for network engineers and researchers, though it appears incremental as it builds on existing strategies and frameworks.
The paper tackles the problem of caching strategies in Content-Centric Networking (CCN) routers by employing rule-based stream reasoning to autonomously switch between strategies in response to changing content request patterns, resulting in significant performance gains as shown in an empirical evaluation.
Content-Centric Networking (CCN) research addresses the mismatch between the modern usage of the Internet and its outdated architecture. Importantly, CCN routers may locally cache frequently requested content in order to speed up delivery to end users. Thus, the issue of caching strategies arises, i.e., which content shall be stored and when it should be replaced. In this work, we employ novel techniques towards intelligent administration of CCN routers that autonomously switch between existing strategies in response to changing content request patterns. In particular, we present a router architecture for CCN networks that is controlled by rule-based stream reasoning, following the recent formal framework LARS which extends Answer Set Programming for streams. The obtained possibility for flexible router configuration at runtime allows for faster experimentation and may thus help to advance the further development of CCN. Moreover, the empirical evaluation of our feasibility study shows that the resulting caching agent may give significant performance gains.