text: We propose a novel causal coding scheme with forward error correction (FEC) for a point-to-point communication link with delayed feedback. The proposed model can learn the erasure pattern in the channel, and adaptively adjust its transmission and FEC rate based on the burstiness of the channel and the feedback. We investigate the throughput, and the in-order delivery delay of the adaptive causal coding algorithm, and contrast its performance with the one of the selective repeat (SR) ARQ. We demonstrate via an experimental study of the protocol that our model can double the throughput gains, and triple the gain in terms of mean in-order delivery delay when the channel is bursty, while keeping the difference between the maximum and mean in-order delivery delay is much smaller than SR ARQ. Closing the delay gap along with boosting the throughput is very promising for enabling ultra-reliable low-latency communications applications. We validate the performance of data delivery under the traces of Intel.
  @cite_26: 
  @cite_3: We consider an Adaptive Random Convolutional Network Coding (ARCNC) algorithm to address the issue of field size in random network coding for multicast, and study its memory and decoding delay performances through both analysis and numerical simulations. ARCNC operates as a convolutional code, with the coefficients of local encoding kernels chosen randomly over a small finite field. The cardinality of local encoding kernels increases with time until the global encoding kernel matrices at the related sink nodes have full rank. ARCNC adapts to unknown network topologies without prior knowledge, by locally incrementing the dimensionality of the convolutional code. Because convolutional codes of different constraint lengths can coexist in different portions of the network, reductions in decoding delay and memory overheads can be achieved. We show that this method performs no worse than block linear network codes in terms of decodability, and can provide significant gains in terms of average decoding delay or memory in combination, shuttle and random geometric networks.
  @cite_6: Reducing the in-order delivery, or playback, delay of reliable transport layer protocols over error prone networks can significantly improve application layer performance. This is especially true for applications that have time sensitive constraints such as streaming services. We explore the benefits of a coded generalization of selective repeat ARQ for minimizing the in-order delivery delay. An analysis of the delay's first two moments is provided so that we can determine when and how much redundancy should be added to meet a user's requirements. Numerical results help show the gains over selective repeat ARQ, as well as the trade-offs between meeting the user's delay constraints and the costs inflicted on the achievable rate. Finally, the analysis is compared with experimental results to help illustrate how our work can be used to help inform system decisions.
  @cite_0: Video surveillance and similar real-time applications on wireless networks require increased reliability and high performance of the underlying transmission layer. Classical solutions, such as Reed-Solomon codes, increase the reliability, but typically have the negative side-effect of additional overall delays due to processing overheads. This paper describes the delay reduction achieved through online network coding approaches with a limit on the number of packets to be mixed before decoding and a systematic encoding structure. We use the inorder per packet delay as our key performance metric. This metric captures the elapsed time between (network) encoding RTP packets and completely decoding the packets in-order on the receiver side. Our solutions are implemented and evaluated on a point-to-point link between a Raspberry Pi device and a network (de)coding enabled software running on a regular PC. We find that our sliding window approach (more feedback) outperforms all other tested mechanisms in terms of per-+packet delay including the Reed-Solomon encoding employing the systematic approach, a random linear network coding approach, and our proposed on-the-fly network coding approach (which relies on less feedback).We show gains in order of magnitudes between our sliding window and the other approaches when we manage the redundancy transmission adaptively. This low per-packet delay and the inherent reliability of our schemes make these solutions particularly suitable for real-time multimedia delivery in contrast to other classical and network coding strategies.
  @cite_19: We introduce CTCP, a reliable transport protocol using network coding. CTCP is designed to incorporate TCP features such as congestion control, reliability, and fairness while significantly improving on TCP's performance in lossy, interference-limited and or dynamic networks. A key advantage of adopting a transport layer over a link layer approach is that it provides backward compatibility with wireless equipment installed throughout existing networks. We present a portable userspace implementation of CTCP and extensively evaluate its performance in both testbed and production wireless networks.
  @cite_23: We consider use of FEC to reduce in-order delivery delay over packet erasure channels. We propose a class of streaming codes that is capacity achieving and provides a superior throughput-delay trade-off compared to block codes by introducing flexibility in where and when redundancy is placed. This flexibility results in significantly lower in-order delay for a given throughput for a wide range of network scenarios. Furthermore, a major contribution of this paper is the combination of queuing and coding theory to analyze the code's performance. Finally, we present simulation and experimental results illustrating the code's benefits.
  @cite_15: 
  @cite_16: 
  @cite_12: We investigate the performance of delay constrained data transmission over wireless networks without end-to-end feedback. Forward error-correction coding (FEC) is performed at the bit level to combat channel distortions and random linear network coding (RLNC) is performed at the packet level to recover from packet erasures. We focus on the scenario where RLNC re-encoding is performed at intermediate nodes and we assume that any packet that contains bit errors after FEC decoding can be detected and erased. To facilitate explicit characterization of data transmission over network-coded wireless systems, we propose a generic two-layer abstraction of a network that models both bit symbol-level operations at the lower layer (termed PHY-layer) over several heterogeneous links and packet-level operations at the upper layer (termed NET-layer). Based on this model, we propose a network reduction method to characterize the throughput-reliability function of the end-to-end transmission. Our approach not only reveals an explicit tradeoff between data delivery rate and reliability, but also provides an intuitive visualization of the bottlenecks within the underlying network. We illustrate our approach via a point-to-point link and a relay network and highlight the advantages of this method over capacity-based approaches.
  @cite_11: Unlike traditional file transfer where only total delay matters, streaming applications impose delay constraints on each packet and require them to be in order. To achieve fast in-order packet decoding, we have to compromise on the throughput. We study this trade-off between throughput and in-order decoding delay, and in particular how it is affected by the frequency of block-wise feedback, whereby the source receives full channel state feedback at periodic intervals. Our analysis shows that for the same throughput, having more frequent feedback significantly reduces the in-order decoding delay. For any given block-wise feedback delay, we present a spectrum of coding schemes that span different throughput-delay tradeoffs. One can choose an appropriate coding scheme from these, depending upon the delaysensitivity and bandwidth limitations of the application.
summary: Using FEC, in order delivery delay over packet erasure channels can be reduced @cite_23 , and the performance of SR ARQ protocols @cite_6 can be boosted. Delay bounds for convolutional codes have been provided in @cite_3 , @cite_0 . Packet dropping to reduce playback delay of streaming over an erasure channel is investigated in @cite_16 , @cite_11 , @cite_26 . Delay-optimal codes without feedback for burst erasure channels, and the decoding delay of codes for more general erasure models have been analyzed in @cite_15 . Transmission with delay constraints have been considered in @cite_12 by combining the PHY and NET layer aspects, where bit level FEC is performed at the PHY layer, and Random Linear Network Coding (RLNC) is performed at the NET layer. To prevent packet loss in the presence of interference and large RTT, a network coded TCP solution has been proposed in @cite_19 . In Fig. , we refer to two of the coding approaches that are the closest to ours.