Dynamic Sampling Procedure for Decomposable Random Networks

Haidong Li, Yijie Peng, Xiaoyun Xu, Chun Hung Chen, Bernd F. Heidergott

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

This research studies the problem of node ranking in a random network. Specifically, we consider a Markov chain with several ergodic classes and unknown transition probabilities which can be estimated by sampling. The objective is to select all of the best nodes in each ergodic class. A sampling procedure is proposed to decompose the Markov chain and maximize a weighted probability of correct selection of the best nodes in each ergodic class. Numerical results demonstrate the efficiency of the proposed sampling procedure.

Original languageEnglish
Title of host publication2019 Winter Simulation Conference (WSC 2019)
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3752-3763
Number of pages12
ISBN (Electronic)9781728132839
DOIs
Publication statusPublished - Dec 2019
Event2019 Winter Simulation Conference, WSC 2019 - National Harbor, United States
Duration: 8 Dec 201911 Dec 2019

Publication series

NameProceedings - Winter Simulation Conference
Volume2019-December
ISSN (Print)0891-7736

Conference

Conference2019 Winter Simulation Conference, WSC 2019
CountryUnited States
CityNational Harbor
Period8/12/1911/12/19

    Fingerprint

Cite this

Li, H., Peng, Y., Xu, X., Chen, C. H., & Heidergott, B. F. (2019). Dynamic Sampling Procedure for Decomposable Random Networks. In 2019 Winter Simulation Conference (WSC 2019) (pp. 3752-3763). [9004795] (Proceedings - Winter Simulation Conference; Vol. 2019-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WSC40007.2019.9004795