Defragmenting the 6LoWPAN Fragmentation Landscape: A Performance Evaluation
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IMT Atlantique, IRISA, 35000 Rennes, France
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IMT Atlantique, STACK (Inria/LS2N), 44000 Nantes, France
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Authors to whom correspondence should be addressed.
Academic Editor: Joaquin Ordieres Meré
Sensors 2021, 21(5), 1711; https://doi.org/10.3390/s21051711
Received: 31 December 2020
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Revised: 5 February 2021
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Accepted: 18 February 2021
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Published: 2 March 2021
(This article belongs to the Special Issue Dependable IoT Networking)
The emergence of the Internet of Things (IoT) has made wireless connectivity ubiquitous and necessary. Extending the IoT to the Industrial Internet of Things (IIoT) places significant demands in terms of reliability on wireless connectivity. The Institute of Electrical and Electronics Engineers (IEEE) Std 802.15.4-2015 standard was designed in response to these demands, and the IPv6 over Low power Wireless Personal Area Networks (6LoWPAN) adaptation layer was introduced to address (among other issues) its payload size limitations by performing packet compression and fragmentation. However, the standardised method does not cope well with low link-quality situations and, thus, we present the state-of-the-art Forward Error Correction (FEC) methods and introduce our own contribution, Network Coding FEC (NCFEC), to improve performance in these situations. We present and analyse the existing methods as well as our own theoretically, and we then implement them and perform an experimental evaluation using the 6TiSCH simulator. The simulation results demonstrate that when high reliability is required and only low quality links are available, NCFEC performs best, with a trade-off between additional network and computational overhead. In situations where the link quality can be guaranteed to be higher, simpler solutions also start to be feasible, but with reduced adaptation flexibility.
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Keywords:
Internet of Things (IoT); industrial IoT; 6LoWPAN; RFC 4944; fragmentation; fragment forwarding; Forward Error Correction (FEC); network coding
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MDPI and ACS Style
Bruniaux, A.; Koutsiamanis, R.-A.; Papadopoulos, G.Z.; Montavont, N. Defragmenting the 6LoWPAN Fragmentation Landscape: A Performance Evaluation. Sensors 2021, 21, 1711. https://doi.org/10.3390/s21051711
AMA Style
Bruniaux A, Koutsiamanis R-A, Papadopoulos GZ, Montavont N. Defragmenting the 6LoWPAN Fragmentation Landscape: A Performance Evaluation. Sensors. 2021; 21(5):1711. https://doi.org/10.3390/s21051711
Chicago/Turabian StyleBruniaux, Amaury, Remous-Aris Koutsiamanis, Georgios Z. Papadopoulos, and Nicolas Montavont. 2021. "Defragmenting the 6LoWPAN Fragmentation Landscape: A Performance Evaluation" Sensors 21, no. 5: 1711. https://doi.org/10.3390/s21051711
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