Less is more: Choosing fair network coding parameters

Autor(en): Thieme, S.
Schutz, B.
Aschenbruck, N. 
Herausgeber: Khoukhi, L.
Oteafy, S.
Bulut, E.
Stichwörter: Network coding; Redundancy, Coding parameters; Congestion loss; Deployability; Fair networks; Less is mores; Linear combinations; Performance issues; TCP networks; Transport protocols; User spaces, Transmission control protocol
Erscheinungsdatum: 2021
Herausgeber: IEEE Computer Society
Enthalten in: Proceedings - Conference on Local Computer Networks, LCN
Band: 2021-October
Startseite: 123
Seitenende: 131
Zusammenfassung: 
TCP still is the prevailing transport protocol on the Internet. It does, however, suffer from severe performance issues on links with non-congestion losses. Instead of relying on the RTT-sensitive ARQ mechanism of TCP, network coding (NC) uses linear combinations of packets to correct forward erasures. Several approaches were developed to incorporate NC into TCP. While they are able to improve the offered service, their lack of deployability and fairness in modern environments is not desirable. To mitigate this, we propose TCPyNC, a Python-based intra-session NC user space shim layer for TCP. Not only are its gains equally high, but it is also more flexible regarding the use of TCP options and parameters. We use a numerical analysis and a testbed evaluation to determine parameters that enable a fair use of TCP in conjunction with Forward Erasure Correction (FEC). In order to reach this goal, we found the maxim less is more to be a sensible orientation. For scenarios with 10% random loss, instead of choosing a high redundancy rate and a large generation size in order to gain the best loss reduction, choosing redundancy rates that leave between 1% and 6% loss for TCP's ARQ to correct and generation sizes below 32 when using default TCP parameters, yields fair results. © 2021 IEEE.
Beschreibung: 
Conference of 46th IEEE Conference on Local Computer Networks, LCN 2021 ; Conference Date: 4 October 2021 Through 7 October 2021; Conference Code:173111
ISBN: 9780738124766
DOI: 10.1109/LCN52139.2021.9525026
Externe URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85118446317&doi=10.1109%2fLCN52139.2021.9525026&partnerID=40&md5=16b8f5b4a9f407a0cad534def6beb479

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