Real-Time Monitoring of Multicast Group Information

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. key words: membership estimation, adaptive sampling, probabilistic polling, binomial probability, multicast