TY - GEN
T1 - Dynamic Sampling Procedure for Decomposable Random Networks
AU - Li, Haidong
AU - Peng, Yijie
AU - Xu, Xiaoyun
AU - Chen, Chun Hung
AU - Heidergott, Bernd F.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85081122799&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85081122799&partnerID=8YFLogxK
U2 - 10.1109/WSC40007.2019.9004795
DO - 10.1109/WSC40007.2019.9004795
M3 - Conference contribution
AN - SCOPUS:85081122799
SN - 9781728120522
T3 - Proceedings - Winter Simulation Conference
SP - 3752
EP - 3763
BT - 2019 Winter Simulation Conference (WSC)
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 Winter Simulation Conference, WSC 2019
Y2 - 8 December 2019 through 11 December 2019
ER -