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Content Provider | IEEE Xplore Digital Library |
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Author | Xiaonong Lu Baoqun Yin Haipeng Zhang Qiang Ling |
Copyright Year | 2012 |
Description | Author affiliation: Department of Automation, University of Science and Technology of China, Hefei, 230027, PRC (Xiaonong Lu; Baoqun Yin; Haipeng Zhang; Qiang Ling) |
Abstract | In this paper, we propose an admission control method based on model and prediction for distributed service systems. First, we use partly observable Markov decision process (POMDP) to model the service system. Next, we put the service allocation policy into the model parameters and use randomized policy as admission control policies to optimize system performance. The target of optimization is to maximize the system benefits. Based on the POMDP model, we propose an observation-based policy gradient algorithm to solve the optimal policy. We use HMM-based method to detect and predict change of the system, then updating the system model and admission policy with dynamic adaptive method. Experiment result shows compare with the best effort service policy our optimal policy has a better system performance. |
Starting Page | 5518 |
Ending Page | 5523 |
File Size | 220317 |
Page Count | 6 |
File Format | |
ISBN | 9781467325813 |
ISSN | 21612927 |
e-ISBN | 9789881563811 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2012-07-25 |
Publisher Place | China |
Access Restriction | Subscribed |
Rights Holder | Chinese Assoc of Automati |
Subject Keyword | Adaptation models Admission control Hidden Markov models POMDP Randomized Policy Aerospace electronics Predictive models Resource management Mathematical model Admission Control HMM-based method Distributed Service Systems |
Content Type | Text |
Resource Type | Article |
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