Numerical evaluation of a group-oriented multicast protocol using stochastic activity networks

Luai M. Malhis, William H. Sanders, Richard D. Schlichting

Research output: Contribution to conferencePaper

Abstract

Group-oriented multicast protocols that provide message ordering and delivery guarantees are becoming increasingly important in distributed system design. However, despite the large number of such protocols, little analytical work has been done concerning their performance, especially in the presence of message loss. This paper illustrates a method for determining the performability of group-oriented multicast protocols using stochastic activity networks, a stochastic extension to Petri nets, and reduced base model construction. In particular, we study the performability of one such protocol, called Psync, under a wide variety of workload and message loss probabilities. The specific focus is on measuring two quantities, the stabilization time - that is, the time required for messages to arrive at all hosts - and channel utilization. The analysis shows that Psync works well when message transmissions are frequent, but exhibits extremely long message stabilization times when transmissions are infrequent and message losses occur. The results provide useful insight on the behavior of Psync, as well as serve as a guide for evaluating the performability of other group-oriented multicast protocols.

Original languageEnglish (US)
Pages63-72
Number of pages10
StatePublished - Dec 1 1995
EventProceedings of the 6th International Workshop on Petri Nets and Performance Models - Durham, NC, USA
Duration: Oct 3 1995Oct 6 1995

Other

OtherProceedings of the 6th International Workshop on Petri Nets and Performance Models
CityDurham, NC, USA
Period10/3/9510/6/95

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ASJC Scopus subject areas

  • Applied Mathematics
  • Modeling and Simulation

Cite this

Malhis, L. M., Sanders, W. H., & Schlichting, R. D. (1995). Numerical evaluation of a group-oriented multicast protocol using stochastic activity networks. 63-72. Paper presented at Proceedings of the 6th International Workshop on Petri Nets and Performance Models, Durham, NC, USA, .