Evaluation of receiver-feedback techniques for fragmentation over LPWANs

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThe Internet Engineering Task Force (IETF) has standardized a new framework for IPv6 support over Low Power Wide Area Networks (LPWANs), called Static Context Header Compression and Fragmentation (SCHC). SCHC includes acknowledgment (ACK)-based mechanisms for reliable fragmented packet transmission. For the latter, SCHC defines a Receiver-Feedback Technique (RFT), called Compressed Bitmap (CB), by which a receiver reports to the sender whether the fragments carrying a packet have been received or not. Such information is carried as ACK payload. Considering the extraordinary frame size and message rate constraints of LPWANs, ACK payload size becomes crucial. In this paper, we compare the performance of CB with that of several alternative RFTs, namely List of Lost Fragments (LLF), List of Deltas (LoD), and Uncompressed Bitmap (UB), where the latter is used as a benchmark. We evaluate the considered RFTs in terms of ACK size, number of Layer 2 (L2) frames needed to carry an ACK, and ACK Time on Air. Our analysis shows that the use of RFTs different from CB offers significant performance improvement in many scenarios. Furthermore, we provide guidance on which RFT should be used for different packet sizes, error rates and error patterns.This research is funded in part by the ERDF and the Spanish Government through project TEC2016-79988-P and project PID2019-106808RA-I00, AEI/FEDER, EU.Peer ReviewedPostprint (author's final draft

Informe mensual d'articles publicats. Campus Baix Llobregat. Base de dades Scopus. Desembre 2019.

Informe bibliomètric mensual Campus Baix Llobregat. Base de dades Scopus. Desembre 2019. EETAC i DEAB, ESAB.Postprint (published version

LoRaWAN SCHC Fragmentation Demystified

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