Dynamic Sampling Procedure for Decomposable Random Networks

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

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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)
Subtitle of host publication[Proceedings]
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3752-3763
Number of pages12
ISBN (Electronic)9781728132839
ISBN (Print)9781728120522
DOIs
Publication statusPublished - 2020
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
Country/TerritoryUnited States
CityNational Harbor
Period8/12/1911/12/19

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