Low-Latency Network-Adaptive Error Control for Interactive Streaming

Fong, Silas L.; Emara, Salma; Li, Baochun; Khisti, Ashish; Tan, Wai-Tian; Zhu, Xiaoqing; Apostolopoulos, John

doi:10.1145/3343031.3350942

Cited by 12 publications

(4 citation statements)

References 22 publications

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“…Recently, in single path communication using TCP and multipath communication using MPTCP, a priori forward error correction (FEC) according to the feedback acknowledgments was considered to reduce the in-order delay [18]- [21]. Coding techniques, e.g., MDS codes [22], [23] and systematic block codes [24], were considered as well. In particular, to compensate the average erasures in the lossy channels, RLNC is employed by periodically sending a priori FEC re-transmissions, i.e., the RLNC-coded packets generated from raw information in a sliding window block that has been used before for generating coded packets [25]- [27].…”

Section: Parammentioning

confidence: 99%

Bringing Network Coding into SDN: Architectural Study for Meshed Heterogeneous Communications

et al. 2021

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Modern communications have moved away from point-to-point models to increasingly heterogeneous network models. In this article, we propose a novel controller-based protocol to deploy adaptive causal network coding in heterogeneous and highly-meshed communication networks. Specifically, we consider using Software-Defined-Network (SDN) as the main controller. We first present an architecture for the highly-meshed heterogeneous multi-source multi-destination networks that represents the practical communication networks encountered in the fifth generation of wireless networks (5G) and beyond. Next, we present a promising solution to deploy network coding over the new architecture. In fact, we investigate how to generalize adaptive and causal random linear network coding (AC-RLNC), proposed for multipath multi-hop (MP-MH) communication channels, to a protocol for the new multi-source multi-destination network architecture using controller. To this end, we present a modularized implementation of AC-RLNC solution where the modules work together in a distributed fashion and perform the AC-RLNC technology. We also present a new controller-based setting through which the network coding modules can communicate and can attain their required information. Finally, we briefly discuss how the proposed architecture and network coding solution provide a good opportunity for future technologies, e.g., distributed coded computation and storage, mmWave communication environments, and innovative and efficient security features.

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Section: Parammentioning

confidence: 99%

Bringing Network Coding into SDN: Architectural Study for Meshed Heterogeneous Communications

et al. 2021

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“…Coding over small blocks of information is investigated in [5] under the assumption of perfect feedback. In [6], a coding scheme over a large finite field (GF(256)) for delaysensitive multimedia applications is proposed. In contrast, we seek computationally simpler strategies that operate on GF (2).…”

Section: Related Workmentioning

confidence: 99%

“…In contrast, we seek computationally simpler strategies that operate on GF (2). Unlike in [5] and [6], where each coded symbol is sent in a separate packet, we consider the transmission of coded symbols and information symbols in the same packet. By avoiding the extra packet overhead in this manner, lower energy consumption and smaller duty cycles are achieved.…”

Section: Related Workmentioning

confidence: 99%

Application-Layer Coding with Intermittent Feedback under Delay and Duty-Cycle Constraints

Borkotoky¹,

Schilcher²,

Raffelsberger³

2019

Preprint

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We propose two application-layer coding schemes for delay-constrained point-to-point packet communications over frequency bands with restrictions on the transmitter's maximum duty-cycle. The schemes operate over GF(2) and utilize intermittently available receiver feedback for erasure correction. Simulation results for independent Bernoulli erasure channels, Gilbert-Elliott channels, and Long Range (LoRa) communications demonstrate orders-ofmagnitude reductions in the delivery failure rate as compared to feedback-assisted repetition redundancy and a blind coding scheme that does not utilize feedback.

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“…Atiya et.al came up with a nonlinear prediction approach to realize automatic feature selection [10], and Fong et.al. combined an ingenious coding scheme along with a network adaptive algorithm for parameter update [11]. Nevertheless, all of them simply take the historical network pattern as the prediction of future pattern, ignoring the possible complicated relationship between history and future.…”

Section: Introductionmentioning

confidence: 99%

DeepRS: Deep-learning Based Network-Adaptive FEC for Real-Time Video Communications

Cheng

Zhang

et al. 2020

Preprint

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As real-time multimedia streaming thriving, Forward Error Correction (FEC) methods have been studied and applied extensively these years. Most of researchers paid their attention to the coding algorithms, attempted to balance the trade off between recovery ratio and delay with fewer redundance. However, when packet loss pattern changes dynamically, the redundance waste is too serious to be ignored. In this work, we propose a novel algorithm which adjusts the redundance ratio of FEC encoder according to the prediction of packet loss. Receivers are additionally required to feedback observed packet loss pattern. Streaming sender collects the feedbacked packet loss pattern and predicts the number of packet loss in the incoming short period. As for implementation, we adopt long short-term memory (LSTM) network as our deep learning algorithm, and exquisitely embed it in our adaptive FEC system. With the extensive experiments, our proposed scheme outperforms other FEC methods greatly both in the simulations and evaluations on traces observed from the real world.

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Low-Latency Network-Adaptive Error Control for Interactive Streaming

Cited by 12 publications

References 22 publications

Bringing Network Coding into SDN: Architectural Study for Meshed Heterogeneous Communications

Bringing Network Coding into SDN: Architectural Study for Meshed Heterogeneous Communications

Application-Layer Coding with Intermittent Feedback under Delay and Duty-Cycle Constraints

DeepRS: Deep-learning Based Network-Adaptive FEC for Real-Time Video Communications

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