Real-time monitoring of multicast group information

Achmad Basuki, Achmad Husni Thamrin, Hitoshi Asaeda, Jun Murai

Research output: Contribution to journalArticlepeer-review


This paper presents a method to monitor information of a large-sized multicast group that can follow the group's dynamics in realtime 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.

Original languageEnglish
Pages (from-to)2213-2222
Number of pages10
JournalIEICE Transactions on Information and Systems
Issue number8
Publication statusPublished - 2010 Aug


  • Adaptive sampling
  • Binomial probability
  • Membership estimation
  • Multicast
  • Probabilistic polling

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence


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