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Systematic Network Coding with Overlap for IoT Scenarios

Authors: Mihail Zverev; Pablo Garrido 0002; Ramón Agüero; Josu Bilbao;

Systematic Network Coding with Overlap for IoT Scenarios

Abstract

The presence of IoT in current networking scenarios is more relevant every day. IoT covers a wide range of applications, ranging from wearable devices to vehicular communications. With the consolidation of Industry 4.0, IIoT (Industrial IoT) environments are becoming more common. Communications in these scenarios are mostly wireless, and due to the lossy nature of wireless communications, the loss of information becomes an intrinsic problem. However, loss recovery schemes increase the delay that characterizes any communication. On the other hand, both reliability (robustness) and low delay are crucial requirements for some applications in IIoT. An interesting strategy to improve both of them is the use of Network Coding techniques, which have shown promising results, in terms of increasing reliability and performance. This work focuses on a possible new coding approach, based on systematic network coding scheme with overlapping generations. We perform a thorough analysis of its behavior. Based on the results, we draw out a number of conclusions for practical implementations in wireless networks, focusing our interest in IIoT environments.

The authors are grateful for the funding of the Industrial Doctorates Program from the University of Cantabria (Call 2018). This work has been partially supported by the Basque Government through the Elkartek program under the DIGITAL project (Grant agreement no. KK-2019/00095), as well as by the Spanish Government (MINECO, MCIU, AEI, FEDER) by means of the projects ADVICE: Dynamic provisioning of connectivity in high density 5G wireless scenarios (TEC2015-71329-C2-1-R) and FIERCE: Future Internet Enabled Resilient Cities (RTI2018-093475-A-100).

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Keywords

Network coding, Systematic coding, IIoT

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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