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CAINE: A Context-Aware Information-Centric Network Ecosystem

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  • George Kamel
  • Ning Wang
  • Vasileios Vasilakis
  • Zhili Sun
  • Pirabakaran Navaratnam
  • Chonggang Wang
  • Lijun Dong
  • Rahim Tafazolli


Publication details

JournalIEEE Communications Magazine
DatePublished - 5 Aug 2015
Issue number8
Number of pages8
Pages (from-to)176-183
Original languageEnglish


Information-centric networking (ICN) is an emerging networking paradigm that places content identifiers rather than host identifiers at the core of the mechanisms and protocols used to deliver content to end users. Such a paradigm allows routers enhanced with content-awareness to play a direct role in the routing and resolution of content requests from users, without any knowledge of the specific locations of hosted content. However, to facilitate good network traffic engineering and satisfactory user QoS, content routers need to exchange advanced network knowledge to assist them with their resolution decisions. In order to maintain the location-independency tenet of ICNs, such knowledge (known as context information) needs to be independent of the locations of servers. To this end, we propose CAINE - Context-Aware Information-centric Network Ecosystem - which enables context-based operations to be intrinsically supported by the underlying ICN routing and resolution functions. Our approach has been designed to maintain the location-independence philosophy of ICNs by associating context information directly to content rather than to the physical entities such as servers and network elements in the content ecosystem, while ensuring scalability. Through simulation, we show that based on such location-independent context information, CAINE is able to facilitate traffic engineering in the network, while not posing a significant control signalling burden on the network.

    Research areas

  • servers, context modelling, routing, information filters, signal resolution, information technology, telecommunication network management

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