Selective Content Retrieval in Information-Centric Networking

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Abstract

Recently, novel networking architectures have emerged to cope with the fast-evolving and new Internet utilisation patterns. Information-Centric Networking (ICN) is a prominent example of this architecture. By perceiving content as the core element of the networking functionalities, ICN opens up a whole new avenue of information exchange optimisation possibilities. This paper presents an approach that progresses the base operation of ICN and leverages content identification right at the network layer, allowing to selectively retrieve partial pieces of information from content already present in ICN in-network caches. Additionally, this proposal enables information producers to seamlessly offload some content processing tasks into the network. The concept is discussed and demonstrated through a proof-of-concept prototype targeting an Internet of Things (IoT) scenario, where consumers retrieve specific pieces of the whole information generated by sensors. The obtained results showcase reduced traffic and storage consumption at the core of the network.

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APA

Quevedo, J., & Corujo, D. (2022). Selective Content Retrieval in Information-Centric Networking. Sensors, 22(22). https://doi.org/10.3390/s22228742

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