Performance and complexity of tunable sparse network coding with gradual growing tuning functions over wireless networks
| Autor: | Chres W. Sorensen, Pablo Garrido, Ramón Agüero, Daniel E. Lucani |
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| Přispěvatelé: | Universidad de Cantabria |
| Rok vydání: | 2016 |
| Předmět: |
Wireless Networks
Wireless mesh network Network packet Wireless network Computer science TSNC Goodput Distributed computing 020206 networking & telecommunications 02 engineering and technology Sparse Matrices Robustness (computer science) Linear network coding 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Network performance Random Linear Coding Simulation |
| Zdroj: | IEEE 27th Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), 2016, Valencia, 2145-2150 UCrea Repositorio Abierto de la Universidad de Cantabria Universidad de Cantabria (UC) PIMRC Garrido, P, Sørensen, C W, Roetter, D E L & Aguero, R 2016, Performance and Complexity of Tunable Sparse Network Coding with Gradual Growing Tuning Functions over Wireless Networks . in Personal, Indoor, and Mobile Radio Communications (PIMRC), 2016 IEEE 27th Annual International Symposium on . IEEE, I E E E International Symposium Personal, Indoor and Mobile Radio Communications, IEEE 27th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio Communications-(PIMRC), Valencia, Spain, 04/09/2016 . https://doi.org/10.1109/PIMRC.2016.7794915 |
| DOI: | 10.1109/PIMRC.2016.7794915 |
| Popis: | Random Linear Network Coding (RLNC) has been shown to be a technique with several benefits, in particular when applied over wireless mesh networks, since it provides robustness against packet losses. On the other hand, Tunable Sparse Network Coding (TSNC) is a promising concept, which leverages a trade-off between computational complexity and goodput. An optimal density tuning function has not been found yet, due to the lack of a closed-form expression that links density, performance and computational cost. In addition, it would be difficult to implement, due to the feedback delay. In this work we propose two novel tuning functions with a lower computational cost, which do not highly increase the overhead in terms of the transmission of linear dependent packets compared with RLNC and previous proposals. Furthermore, we also broaden previous studies of TSNC techniques, by means of an extensive simulation campaign carried out using the ns-3 simulator. This brings the possibility of assessing their performance over more realistic scenarios, e.g considering MAC effects and delays. We exploit this implementation to analyze the impact of the feedback sent by the decoder. The results, compared to RLNC, show a reduction of 3.5 times in the number of operations without jeopardizing the network performance, in terms of goodput, even when we consider the delay effect on the feedback sent by the decoder This work has been supported by the Spanish Government (Ministerio de Economía y Competitividad, Fondo Europeo de Desarrollo Regional, FEDER) by means of the projects COSAIF, “Connectivity as a Service: Access for the Internet of the Future” (TEC2012-38754-C02-01), and ADVICE (TEC2015-71329-C2-1-R). This work was also financed in part by the TuneSCode project (No. DFF 1335-00125) granted by the Danish Council for Independent Research. |
| Databáze: | OpenAIRE |
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