In this paper, we measure and model the distribution of multicast group members. Multicast research has traditionally been plagued by a lack of real data and an absence of a systematic simulation methodology. Although temporal group properties have received some attention, the location of group members has not been measured and modelled. However, the placement of members can have significant impact on the design and evaluation of multicast schemes and protocols as shown in previous studies. In our work, we identify properties of members that reflect their spatial clustering and the correlation among them (such as participation probability, and pairwise correlation). Then, we obtain values for these properties by monitoring the membership of network games and large audio-video broadcasts from IETF and NASA. Finally, we provide a comprehensive model that can generate realistic groups. We evaluate our model against the measured data with excellent results. A realistic group membership model can help us improve the effectiveness of simulations and guide the design of group-communication protocols.

Measuring and modelling the group membership in the Internet / J.H. Cui, M. Faloutsos, D. Maggiorini, M. Gerla, K. Boussetta - In: Proceedings of the 2003 ACM SIGCOMM Internet Measurement Conference, IMC 2003 : Miami Beach, Florida, USA, October 27-29, 2003New York : Association for computing machinery, 2003. - ISBN 1581137737. - pp. 65-77 (( convegno Internet Measurement Conference (IMC) tenutosi a Miami nel 2003 [10.1145/948205.948215].

Measuring and modelling the group membership in the Internet

D. Maggiorini;
2003

Abstract

In this paper, we measure and model the distribution of multicast group members. Multicast research has traditionally been plagued by a lack of real data and an absence of a systematic simulation methodology. Although temporal group properties have received some attention, the location of group members has not been measured and modelled. However, the placement of members can have significant impact on the design and evaluation of multicast schemes and protocols as shown in previous studies. In our work, we identify properties of members that reflect their spatial clustering and the correlation among them (such as participation probability, and pairwise correlation). Then, we obtain values for these properties by monitoring the membership of network games and large audio-video broadcasts from IETF and NASA. Finally, we provide a comprehensive model that can generate realistic groups. We evaluate our model against the measured data with excellent results. A realistic group membership model can help us improve the effectiveness of simulations and guide the design of group-communication protocols.
Group Membership; Maximum Entropy; Member Clustering; Pairwise Correlation; Skewed Distribution
Settore INF/01 - Informatica
2003
ACM
Book Part (author)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/36036
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