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
Este artigo apresenta um método para monitorar informações de um grupo multicast de grande porte que pode acompanhar a dinâmica do grupo em tempo real, evitando a implosão de feedback usando polling probabilístico. Em particular, este artigo melhora a abordagem baseada em pesquisas probabilísticas, derivando um valor médio de referência como o valor de controle de referência para o número de feedback esperado das propriedades de um modelo de estimativa binomial. Como resultado, nosso método altera adaptativamente seus parâmetros de estimativa dependendo do feedback dos receptores, a fim de obter um tempo de estimativa rápido e com alta precisão, evitando a possível ocorrência de implosão de feedback. Nossa implementação experimental e avaliação no PlanetLab mostraram que o método proposto controla efetivamente o número de feedback e estima com precisão o tamanho de um grupo multicast dinâmico.
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Achmad BASUKI, Achmad Husni THAMRIN, Hitoshi ASAEDA, Jun MURAI, "Real-Time Monitoring of Multicast Group Information" in IEICE TRANSACTIONS on Information,
vol. E93-D, no. 8, pp. 2213-2222, August 2010, doi: 10.1587/transinf.E93.D.2213.
Abstract: This paper presents a method to monitor information of a large-sized multicast group that can follow the group's dynamics in real-time while avoiding feedback implosion by using probabilistic polling. In particular, this paper improves the probabilistic-polling-based approach by deriving a reference mean value as the reference control value for the number of expected feedback from the properties of a binomial estimation model. As a result, our method adaptively changes its estimation parameters depending on the feedback from receivers in order to achieve a fast estimate time with high accuracy, while preventing the possible occurrence of feedback implosion. Our experimental implementation and evaluation on PlanetLab showed that the proposed method effectively controls the number of feedback and accurately estimates the size of a dynamic multicast group.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.E93.D.2213/_p
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@ARTICLE{e93-d_8_2213,
author={Achmad BASUKI, Achmad Husni THAMRIN, Hitoshi ASAEDA, Jun MURAI, },
journal={IEICE TRANSACTIONS on Information},
title={Real-Time Monitoring of Multicast Group Information},
year={2010},
volume={E93-D},
number={8},
pages={2213-2222},
abstract={This paper presents a method to monitor information of a large-sized multicast group that can follow the group's dynamics in real-time while avoiding feedback implosion by using probabilistic polling. In particular, this paper improves the probabilistic-polling-based approach by deriving a reference mean value as the reference control value for the number of expected feedback from the properties of a binomial estimation model. As a result, our method adaptively changes its estimation parameters depending on the feedback from receivers in order to achieve a fast estimate time with high accuracy, while preventing the possible occurrence of feedback implosion. Our experimental implementation and evaluation on PlanetLab showed that the proposed method effectively controls the number of feedback and accurately estimates the size of a dynamic multicast group.},
keywords={},
doi={10.1587/transinf.E93.D.2213},
ISSN={1745-1361},
month={August},}
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TY - JOUR
TI - Real-Time Monitoring of Multicast Group Information
T2 - IEICE TRANSACTIONS on Information
SP - 2213
EP - 2222
AU - Achmad BASUKI
AU - Achmad Husni THAMRIN
AU - Hitoshi ASAEDA
AU - Jun MURAI
PY - 2010
DO - 10.1587/transinf.E93.D.2213
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E93-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2010
AB - This paper presents a method to monitor information of a large-sized multicast group that can follow the group's dynamics in real-time while avoiding feedback implosion by using probabilistic polling. In particular, this paper improves the probabilistic-polling-based approach by deriving a reference mean value as the reference control value for the number of expected feedback from the properties of a binomial estimation model. As a result, our method adaptively changes its estimation parameters depending on the feedback from receivers in order to achieve a fast estimate time with high accuracy, while preventing the possible occurrence of feedback implosion. Our experimental implementation and evaluation on PlanetLab showed that the proposed method effectively controls the number of feedback and accurately estimates the size of a dynamic multicast group.
ER -