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Cache Freshness in Named Data Networking for the Internet of Things

Abstract : The Information-Centric Networking (ICN) paradigm is shaping the foreseen future Internet architecture by focusing on the data itself rather than its hosting location. It is a shift from a host-centric communication model to a content-centric model supporting among others unique and location-independent content names, in-network caching and name-based routing. By leveraging the easy data access, and reducing both the retrieval delay and the load on the data producer, the ICN can be a viable framework to support the Internet of Things (IoT), interconnecting billions of heterogeneous constrained objects. Among several ICN architectures, the Named Data Networking (NDN) is considered as a suitable ICN architecture for IoT systems. However, its default caching approach lacks a data freshness mechanism, while IoT data are transient and frequently updated by the producer which imposes stringent requirements in terms of information freshness. Furthermore, IoT devices are usually resource-constrained with harsh limitations on energy, memory and processing power. We propose in this paper a caching strategy and a novel cache freshness mechanism to monitor the validity of cached contents in an IoT environment while minimizing the caching process cost. We compared our solution to several relevant schemes using the ccnSim simulator. Our solution exhibits the best system performances in terms of hop reduction ratio, server hit reduction ratio and response latency, yet it provides the lowest cache cost and significantly improves the content validity.
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https://hal.laas.fr/hal-01676509
Contributor : Maroua Meddeb <>
Submitted on : Friday, January 5, 2018 - 4:43:26 PM
Last modification on : Thursday, June 10, 2021 - 3:02:22 AM
Long-term archiving on: : Wednesday, May 23, 2018 - 2:48:30 PM

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Maroua Meddeb, Amine Dhraief, Abdelfettah Belghith, Thierry Monteil, Khalil Drira, et al.. Cache Freshness in Named Data Networking for the Internet of Things. The Computer Journal, Oxford University Press (UK), 2018, 61 (10), pp.1496-1511. ⟨10.1093/comjnl/bxy005⟩. ⟨hal-01676509⟩

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