Rule-based Stream Reasoning for Intelli...

Content-Centric Networking (CCN) research addresses the mismatchbetween the modern usage of the Internet and its outdated architecture. Importantly,CCN routers use various caching strategies to locally cache content frequentlyrequested by end users. However, it is unclear which content shall bestored and when it should be replaced. In this work, we employ novel techniquestowards intelligent administration of CCN routers. Our approach allows for autonomousswitching between existing strategies in response to changing contentrequest patterns using rule-based stream reasoning framework LARS which extendsAnswer Set Programming for streams. The obtained possibility for flexiblerouter configuration at runtime allows for faster experimentation and may resultin significant performance gains, as shown in our evaluation.