Implementation of Network Coding with Recoding for Unequal-sized and Header Compressed Traffic

Taghouti, Maroua; Tömösközi, Máté; Höweler, Malte; Lucani, Daniel E.; Fitzek, Frank H. P.; Bouallègue, Ammar; Ekler, Péter

doi:10.1109/wcnc.2019.8885446

Cited by 9 publications

(3 citation statements)

References 8 publications

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“…Our ongoing research focuses on decreasing the coding overhead even further by applying progressive shortening [13] to header compressed packets and evaluating it in a real mesh environment, as well as, generalising the header compression scheme itself for the application to arbitrary protocol headers.…”

Section: Discussionmentioning

confidence: 99%

Unidirectional Robust Header Compression for Reliable Low Latency Mesh Networks

Tömösközi

Lucani

Fitzek

et al. 2019

ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

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Next generation use-cases of mesh networks, such as connected vehicles and industrial devices, require low latency transmissions while fulfilling high reliability constraints. However, they also suffer from an increased protocol encapsulation overhead when handling a large number of messages with small payloads. A solution to this problem is to employ header compression algorithms in order to reduce the size of the individual protocol headers. Unfortunately, the current state-ofthe-art header compression schemes cannot be readily applied to network topologies that contain a combination of multiplehops and paths, as the compression only works favourably on a peer-to-peer, single-hop basis. With the unique combination of network coding and header compression one can always utilise unidirectional compression with maximum gain. In this paper we introduce and evaluate, for the first time, an integrated network coded header compression solution, which we call unidirectional Robust Header Compression (uRoHC). We show that one can-proportionally to the logical payload size-double the payload delivery efficiency compared to standard IPv4 and that we achieve results 10-15 % better than that of RoHCv2 for streams containing 33 bytes of payload.

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Section: Discussionmentioning

confidence: 99%

Unidirectional Robust Header Compression for Reliable Low Latency Mesh Networks

Tömösközi

Lucani

Fitzek

et al. 2019

ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

Self Cite

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“…This approach, however, cannot achieve an optimal theoretical rate. Practical concerns and solutions have been further investigated to improve this type of RLNC, such as decoding delay and complexity [12][13][14][15][16][17][18][19][20], packet size [21][22][23][24][25], and coefficient overhead [26][27][28].…”

Section: Network Coding-based Approachesmentioning

confidence: 99%

BAR: Blockwise Adaptive Recoding for Batched Network Coding

Yin

Yang

Zhou

et al. 2023

Entropy

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Multi-hop networks have become popular network topologies in various emerging Internet of Things (IoT) applications. Batched network coding (BNC) is a solution to reliable communications in such networks with packet loss. By grouping packets into small batches and restricting recoding to the packets belonging to the same batch; BNC has much smaller computational and storage requirements at intermediate nodes compared with direct application of random linear network coding. In this paper, we discuss a practical recoding scheme called blockwise adaptive recoding (BAR) which learns the latest channel knowledge from short observations so that BAR can adapt to fluctuations in channel conditions. Due to the low computational power of remote IoT devices, we focus on investigating practical concerns such as how to implement efficient BAR algorithms. We also design and investigate feedback schemes for BAR under imperfect feedback systems. Our numerical evaluations show that BAR has significant throughput gain for small batch sizes compared with existing baseline recoding schemes. More importantly, this gain is insensitive to inaccurate channel knowledge. This encouraging result suggests that BAR is suitable to be used in practice as the exact channel model and its parameters could be unknown and subject to changes from time to time.

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“…This prototype is for SNC and half-duplex packet switching, also based on USRP with RFX2400 daughterboards. Some other recent implementations of network coding can be found in, for example, [10,11].…”

Section: Introductionmentioning

confidence: 99%

Network Coding with Multimedia Transmission and Cognitive Networking: An Implementation based on Software-Defined Radio

Tran

Nguyen

Ngo

et al. 2021

REV J. Electron. Commun.

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Network coding (NC) is considered a breakthrough to improve throughput, robustness, and security of wireless networks. Although the theoretical aspects of NC have been extensively investigated, there have been only few experiments with pure NC schematics. This paper presents an implementation of NC in a two-way relay model and extend it to two nonstraightforward scenarios: i) multimedia transmission with layered coding and multiple-description coding; ii) cognitive radio with Vandermode Frequency Division Multiplexing (VFDM). The implementation is in real time and based on Software-Define Radio (SDR). The experimental results show that, by combining NC and source coding, we can control the quality of received multimedia content in an on-demand manner. Whereas in the VFDM-based cognitive radio, the received content in the primary receive is low quality (due to imperfect channel estimation) yet retrievable. Our implementation results serve as a proof for the practical feasibility of network coding in relevant applications.

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Implementation of Network Coding with Recoding for Unequal-sized and Header Compressed Traffic

Cited by 9 publications

References 8 publications

Unidirectional Robust Header Compression for Reliable Low Latency Mesh Networks

Unidirectional Robust Header Compression for Reliable Low Latency Mesh Networks

BAR: Blockwise Adaptive Recoding for Batched Network Coding

Network Coding with Multimedia Transmission and Cognitive Networking: An Implementation based on Software-Defined Radio

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