Coding Window Size Research Articles

Scheduling for Optimal File-Transfer Delay using Chunked Random Linear Network Coding Broadcast

We study the broadcast transmission of a single file to an arbitrary number of receivers using Random Linear Network Coding (RLNC) in a network with unreliable channels. Due to the increased computational complexity of the decoding process (especially for large files), we apply chunked RLNC (i.e., RLNC is applied within non-overlapping subsets of the file). In our work, we show the optimality of the Least Received (LR) batch scheduling policy with regards to the expected file transfer completion time. The LR policy strives to keep the receiver queues balanced . This is done by transmitting packets (corresponding to encoded batches) that are needed by the receivers with the shortest queues of successfully received packets. Furthermore, we provide formulas for the expected time for the file transmission to all receivers using the LR batch scheduling policy and the minimum achievable coding window size in the case of a pre-defined delay constraint. Moreover, we evaluate through simulations a modification of the LR policy in a more realistic system setting with reduced feedback from the receivers. Finally, we provide an initial analysis and further modifications to the LR policy for time-correlated channels and asymmetric channels.

Securing Network Coding Architectures Against Pollution Attacks With Band Codes

During a pollution attack, malicious nodes purposely transmit bogus data to the honest nodes to cripple the communication. Securing the communication requires identifying and isolating the malicious nodes. However, in network coding (NC) architectures, random recombinations at the nodes increase the probability that honest nodes relay polluted packets. Thus, discriminating between honest and malicious nodes to isolate the latter turns out to be challenging at best. Band codes (BCs) are a family of rateless codes whose coding window size can be adjusted to reduce the probability that honest nodes relay polluted packets. We leverage such a property to design a distributed scheme for identifying the malicious nodes in the network. Each node counts the number of times that each neighbor has been involved in cases of polluted data reception and exchanges such counts with its neighbor nodes. Then, each node computes for each neighbor a discriminative honest score estimating the probability that the neighbor relays clean packets. We model such probability as a function of the BC coding window size, showing its impact on the accuracy and effectiveness of our distributed blacklisting scheme. We experiment distributing a live video feed in a P2P NC system, verifying the accuracy of our model and showing that our scheme allows us to secure the network against pollution attacks recovering near pre-attack video quality.

Three-dimensional surface reconstruction via a robust binary shape-coded structured light method

A binary shape-coded structured light method for single-shot three-dimensional reconstruction is presented. The projected structured pattern is composed with eight geometrical shapes with a coding window size of 2×2. The pattern element is designed as rhombic with embedded geometrical shapes. The pattern feature point is defined as the intersection of two adjacent rhombic shapes, and a multitemplate-based feature detector is presented for its robust detection and precise localization. Based on the extracted grid-points, a topological structure is constructed to separate the pattern elements from the obtained image. In the decoding stage, a training dataset is first established from training samples that are collected from a variety of target surfaces. Then, the deep neural network technique is applied for the classification of pattern elements. Finally, an error correction algorithm is introduced based on the epipolar and neighboring constraints to refine the decoding results. The experimental results show that the proposed method not only owns high measurement precision but also has strong robustness to surface color and texture.

Adaptive Network Coding Scheme for TCP over Wireless Sensor Networks

The purpose of this paper is to develop a network coding scheme to enhance TCP performance in wireless sensor networks. It is well known that TCP performs poorly over wireless links which suffer from packet losses mainly due to the bad channel. To address this problem, it is useful to incorporate network coding into TCP, as network coding can offer significant benefits in terms of throughput, reliability, and robustness. However, the encoding and decoding operations of network coding techniques will bring an additional delay that has a negative effect on applications of wireless sensor networks. In this paper, we propose an adaptive network coding (ANC) scheme which contains two major aspects: the adjustment of the redundancy factor R and the adjustment of the coding window size CW. We dynamically adjust these two parameters depending on the measured packet loss rate, so that the proposed ANC can effectively mask packet losses and reduce the decoding delay of network coding. The performance of our scheme is evaluated by simulations using NS-2 simulator. Compared to other schemes, the ANC not only achieves a good throughput but also has the lowest average delay and the lowest maximum delay in all experimental environments.

Throughput-Delay Analysis of Random Linear Network Coding for Wireless Broadcasting

In an unreliable single-hop broadcast network setting, we investigate the throughput and decoding-delay performance of random linear network coding as a function of the coding window size and the network size. Our model consists of a source transmitting packets of a single flow to a set of $n$ users over independent erasure channels. The source performs random linear network coding (RLNC) over $k$ (coding window size) packets and broadcasts them to the users. We note that the broadcast throughput of RLNC must vanish with increasing $n$, for any fixed $k.$ Hence, in contrast to other works in the literature, we investigate how the coding window size $k$ must scale for increasing $n$. Our analysis reveals that the coding window size of $\Theta(\ln(n))$ represents a phase transition rate, below which the throughput converges to zero, and above which it converges to the broadcast capacity. Further, we characterize the asymptotic distribution of decoding delay and provide approximate expressions for the mean and variance of decoding delay for the scaling regime of $k=\omega(\ln(n)).$ These asymptotic expressions reveal the impact of channel correlations on the throughput and delay performance of RLNC. We also show how our analysis can be extended to other rateless block coding schemes such as the LT codes. Finally, we comment on the extension of our results to the cases of dependent channels across users and asymmetric channel model.

Throughput-delay analysis of one-to-many wireless multi-hop flows based on random linear network coding

This paper addresses the issue of throughput-delay of one-to-many wireless multi-hop flows based on random linear network coding (RLNC). Existing research results have been focusing on the single-hop model which is not suitable for wireless multi-hop networks. In addition, the conditions of related system model are too idealistic. To address these limitations, we herein investigate the performance of a wireless multi-hop network, focusing on the one-to-many flows. Firstly, a system model with multi-hop delay was constructed; secondly, the transmission schemes of system model were gradually improved in terms of practical conditions such as limited queue length and asynchronous forwarding way; thirdly, the mean delay and the mean throughput were quantified in terms of coding window size if and number of destination nodes N for the wireless multi-hop transmission. Our findings show a clear relationship between the multi-hop transmission performance and the network coding parameters. This study results will contribute significantly to the evaluation and the optimization of network coding method.

TCP Performance Improvement in Network Coding over Multipath Environments

Abstract In one of the most impacting schemes proposed to address the TCP throughput problem over network coding, the network coding layer sends an acknowledgement if an innovative linear combination is received, even when a new packet is not decoded. Although this scheme is very effective, its implementation requires a limit on the coding window size. This limitation causes low TCP throughput in the presence of packet reordering. We argue that a TCP variant detecting a packet loss relying only on timers is effective in dealing with the packet reordering problem in network coding environments as well. Also we propose a new network coding layer to support such a TCP variant. Simulation results for a 2-path environment show that our proposed scheme improves TCP throughput by 19%. Key Words : Network Coding, TCP, ARQ, Packet Reordering * 정회원, 홍익대학교 컴퓨터정보통신공학과접수일자 2011.10.12, 수정완료 2011.11.28게재확정일자 2011.12.16 Ⅰ. 서 론 네트워크 코딩방식의 실용화를 가로막는 중요한 문제 중 하나는 TCP와 함께 사용될 때 종종 좋은 성능을 얻지 못하는 문제이다. 이를 해결하기 위한 연구 결과들

Efficient search and scheduling in P2P-based media-on-demand streaming service

We are interested in providing a media-on-demand streaming service to a large population of clients using a peer-to-peer approach. Since the demands of different clients are asynchronous and the contents of clients' buffers are continuously changing, finding partners with expected data and collaborating with them for future content delivery are very important and challenging problems. In this paper, we propose a generic buffer-assisted search (BAS) scheme to improve partner search efficiency by reducing the size of index overlay. We have also developed a novel scheduling algorithm based on deadline-aware network coding (DNC) to fully exploit network resources by dynamically adjusting the coding window size. Extensive simulation results demonstrate that BAS can provide a faster response time with less control cost than the existing search methods, and DNC improves the network capacity utilization and provides high streaming quality under different network conditions.