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Selective Content Retrieval in Information-Centric Networking.

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Information-Centric Networking (ICN) enables selective retrieval of partial content from caches. This approach reduces network traffic and storage needs, particularly in Internet of Things (IoT) applications.

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Area of Science:

  • Computer Science
  • Networking
  • Information Systems

Background:

  • Evolving internet usage necessitates novel networking architectures.
  • Information-Centric Networking (ICN) shifts focus from location to content.
  • ICN offers potential for optimizing information exchange.

Purpose of the Study:

  • To enhance Information-Centric Networking (ICN) capabilities.
  • To enable selective retrieval of partial content from network caches.
  • To allow content processing offloading to the network infrastructure.

Main Methods:

  • Developed an approach for content identification at the network layer.
  • Implemented a proof-of-concept prototype.
  • Tested the prototype in an Internet of Things (IoT) scenario.

Main Results:

  • Demonstrated selective retrieval of specific information pieces.
  • Showcased reduced traffic consumption in the network core.
  • Indicated reduced storage consumption within ICN caches.

Conclusions:

  • The proposed ICN enhancement facilitates efficient partial content retrieval.
  • Offloading content processing to the network is feasible.
  • The approach significantly benefits data-intensive scenarios like IoT.