Online Self-Organizing Network Control with Time Averaged Weighted Throughput Objective

We study an online multisource multisink queueing network control problem characterized with self-organizing network structure and self-organizing job routing. We decompose the self-organizing queueing network control problem into a series of interrelated Markov Decision Processes and construct a co...

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Main Authors: Zhicong Zhang, Shuai Li, Xiaohui Yan
Format: Article
Language:English
Published: Wiley 2018-01-01
Series:Discrete Dynamics in Nature and Society
Online Access:http://dx.doi.org/10.1155/2018/4184805
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author Zhicong Zhang
Shuai Li
Xiaohui Yan
author_facet Zhicong Zhang
Shuai Li
Xiaohui Yan
author_sort Zhicong Zhang
collection DOAJ
description We study an online multisource multisink queueing network control problem characterized with self-organizing network structure and self-organizing job routing. We decompose the self-organizing queueing network control problem into a series of interrelated Markov Decision Processes and construct a control decision model for them based on the coupled reinforcement learning (RL) architecture. To maximize the mean time averaged weighted throughput of the jobs through the network, we propose a reinforcement learning algorithm with time averaged reward to deal with the control decision model and obtain a control policy integrating the jobs routing selection strategy and the jobs sequencing strategy. Computational experiments verify the learning ability and the effectiveness of the proposed reinforcement learning algorithm applied in the investigated self-organizing network control problem.
format Article
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institution OA Journals
issn 1026-0226
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language English
publishDate 2018-01-01
publisher Wiley
record_format Article
series Discrete Dynamics in Nature and Society
spelling doaj-art-12483671febd4ffc951dca8edb4a90a92025-08-20T02:02:10ZengWileyDiscrete Dynamics in Nature and Society1026-02261607-887X2018-01-01201810.1155/2018/41848054184805Online Self-Organizing Network Control with Time Averaged Weighted Throughput ObjectiveZhicong Zhang0Shuai Li1Xiaohui Yan2Department of Industrial Engineering, Dongguan University of Technology, Dongguan, ChinaDepartment of Industrial Engineering, Dongguan University of Technology, Dongguan, ChinaDepartment of Industrial Engineering, Dongguan University of Technology, Dongguan, ChinaWe study an online multisource multisink queueing network control problem characterized with self-organizing network structure and self-organizing job routing. We decompose the self-organizing queueing network control problem into a series of interrelated Markov Decision Processes and construct a control decision model for them based on the coupled reinforcement learning (RL) architecture. To maximize the mean time averaged weighted throughput of the jobs through the network, we propose a reinforcement learning algorithm with time averaged reward to deal with the control decision model and obtain a control policy integrating the jobs routing selection strategy and the jobs sequencing strategy. Computational experiments verify the learning ability and the effectiveness of the proposed reinforcement learning algorithm applied in the investigated self-organizing network control problem.http://dx.doi.org/10.1155/2018/4184805
spellingShingle Zhicong Zhang
Shuai Li
Xiaohui Yan
Online Self-Organizing Network Control with Time Averaged Weighted Throughput Objective
Discrete Dynamics in Nature and Society
title Online Self-Organizing Network Control with Time Averaged Weighted Throughput Objective
title_full Online Self-Organizing Network Control with Time Averaged Weighted Throughput Objective
title_fullStr Online Self-Organizing Network Control with Time Averaged Weighted Throughput Objective
title_full_unstemmed Online Self-Organizing Network Control with Time Averaged Weighted Throughput Objective
title_short Online Self-Organizing Network Control with Time Averaged Weighted Throughput Objective
title_sort online self organizing network control with time averaged weighted throughput objective
url http://dx.doi.org/10.1155/2018/4184805
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AT shuaili onlineselforganizingnetworkcontrolwithtimeaveragedweightedthroughputobjective
AT xiaohuiyan onlineselforganizingnetworkcontrolwithtimeaveragedweightedthroughputobjective