基于流推理的CCN路由器缓存策略控制
Stream Reasoning-Based Control of Caching Strategies in CCN Routers
摘要：
以内容为中心的网络（CCN）研究解决了互联网的现代使用和过时的架构之间的不匹配。重要的是，CCN路由器可以在本地缓存频繁请求的内容，以加快向最终用户的交付。因此，出现了缓存策略的问题，即，应存储哪些内容以及应在何时替换。在这项工作中，我们采用了新的技术对智能管理的CCN路由器，自主切换现有的策略，以响应不断变化的内容请求模式。特别是，我们提出了一个路由器架构的CCN网络，控制基于规则的流推理，最近的正式框架LARS扩展回答集编程流。在运行时灵活配置路由器的可能性允许更快的实验，因此可能有助于推动CCN的进一步发展。此外，我们的可行性研究的实证评估表明，由此产生的缓存代理可能会带来显着的性能收益。
英文摘要：
Content-Centric Networking (CCN) research addresses the mismatch between the modern usage of the Internet and its outdated architecture.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.
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