The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
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The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
A codificação de rede (NC) pode melhorar a eficiência da transmissão de informações e o rendimento das redes de dados. A codificação de rede linear aleatória (RLNC) é uma forma especial de esquema NC fácil de ser implementada. No entanto, quantificar o ganho de desempenho do RLNC em relação ao sistema de roteamento convencional baseado em Store and Forward (S/F), especialmente para redes sem fio, permanece uma importante questão em aberto. Para resolver este problema, neste artigo, com base na arquitetura de rede em camadas abstratas, construímos um modelo de rede aleatório dinâmico com distribuição de Poisson descrevendo os nós que se juntam aleatoriamente à rede para multicast de fonte única baseado em árvore na MANET. Em seguida, examinamos seu desempenho aplicando os métodos convencionais Store e Forward com FEC (S/F-FEC) e RLNC, respectivamente, e derivamos as expressões da função analítica da taxa média de perda de pacotes, taxa de decodificação bem-sucedida e taxa de transferência em relação à probabilidade de falha do link. Um experimento mostra que essas expressões têm precisão relativamente alta na descrição do desempenho do RLNC. Ele pode ser usado para projetar o algoritmo prático de codificação de rede para multicast multi-hop com topologia baseada em árvore em MANET e fornecer uma ferramenta de pesquisa para a análise de desempenho de RLNC.
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Song XIAO, Ji LU, Ning CAI, "MANET Multicast Model with Poisson Distribution and Its Performance for Network Coding" in IEICE TRANSACTIONS on Communications,
vol. E94-B, no. 3, pp. 823-826, March 2011, doi: 10.1587/transcom.E94.B.823.
Abstract: Network Coding (NC) can improve the information transmission efficiency and throughput of data networks. Random Linear Network Coding (RLNC) is a special form of NC scheme that is easy to be implemented. However, quantifying the performance gain of RLNC over conventional Store and Forward (S/F)-based routing system, especially for wireless network, remains an important open issue. To solve this problem, in this paper, based on abstract layer network architecture, we build a dynamic random network model with Poisson distribution describing the nodes joining the network randomly for tree-based single-source multicast in MANET. We then examine its performance by applying conventional Store and Forward with FEC (S/F-FEC) and RLNC methods respectively, and derive the analytical function expressions of average packet loss rate, successful decoding ratio and throughput with respect to the link failure probability. An experiment shows that these expressions have relatively high precision in describing the performance of RLNC. It can be used to design the practical network coding algorithm for multi-hop multicast with tree-based topology in MANET and provide a research tool for the performance analysis of RLNC.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.E94.B.823/_p
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@ARTICLE{e94-b_3_823,
author={Song XIAO, Ji LU, Ning CAI, },
journal={IEICE TRANSACTIONS on Communications},
title={MANET Multicast Model with Poisson Distribution and Its Performance for Network Coding},
year={2011},
volume={E94-B},
number={3},
pages={823-826},
abstract={Network Coding (NC) can improve the information transmission efficiency and throughput of data networks. Random Linear Network Coding (RLNC) is a special form of NC scheme that is easy to be implemented. However, quantifying the performance gain of RLNC over conventional Store and Forward (S/F)-based routing system, especially for wireless network, remains an important open issue. To solve this problem, in this paper, based on abstract layer network architecture, we build a dynamic random network model with Poisson distribution describing the nodes joining the network randomly for tree-based single-source multicast in MANET. We then examine its performance by applying conventional Store and Forward with FEC (S/F-FEC) and RLNC methods respectively, and derive the analytical function expressions of average packet loss rate, successful decoding ratio and throughput with respect to the link failure probability. An experiment shows that these expressions have relatively high precision in describing the performance of RLNC. It can be used to design the practical network coding algorithm for multi-hop multicast with tree-based topology in MANET and provide a research tool for the performance analysis of RLNC.},
keywords={},
doi={10.1587/transcom.E94.B.823},
ISSN={1745-1345},
month={March},}
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TY - JOUR
TI - MANET Multicast Model with Poisson Distribution and Its Performance for Network Coding
T2 - IEICE TRANSACTIONS on Communications
SP - 823
EP - 826
AU - Song XIAO
AU - Ji LU
AU - Ning CAI
PY - 2011
DO - 10.1587/transcom.E94.B.823
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E94-B
IS - 3
JA - IEICE TRANSACTIONS on Communications
Y1 - March 2011
AB - Network Coding (NC) can improve the information transmission efficiency and throughput of data networks. Random Linear Network Coding (RLNC) is a special form of NC scheme that is easy to be implemented. However, quantifying the performance gain of RLNC over conventional Store and Forward (S/F)-based routing system, especially for wireless network, remains an important open issue. To solve this problem, in this paper, based on abstract layer network architecture, we build a dynamic random network model with Poisson distribution describing the nodes joining the network randomly for tree-based single-source multicast in MANET. We then examine its performance by applying conventional Store and Forward with FEC (S/F-FEC) and RLNC methods respectively, and derive the analytical function expressions of average packet loss rate, successful decoding ratio and throughput with respect to the link failure probability. An experiment shows that these expressions have relatively high precision in describing the performance of RLNC. It can be used to design the practical network coding algorithm for multi-hop multicast with tree-based topology in MANET and provide a research tool for the performance analysis of RLNC.
ER -