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Design and Implementation of Parking Guidance System Based on Internet of Things(IoT) Using Q-learning Model
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 Title & Authors
Design and Implementation of Parking Guidance System Based on Internet of Things(IoT) Using Q-learning Model
Ji, Yong-Joo; Choi, Hak-Hui; Kim, Dong-Seong;
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 Abstract
This paper proposes an optimal dynamic resource allocation method in IoT (Internet of Things) parking guidance system using Q-learning resource allocation model. In the proposed method, a resource allocation using a forecasting model based on Q-learning is employed for optimal utilization of parking guidance system. To demonstrate efficiency and availability of the proposed method, it is verified by computer simulation and practical testbed. Through simulation results, this paper proves that the proposed method can enhance total throughput, decrease penalty fee issued by SLA (Service Level Agreement) and reduce response time with the dynamic number of users.
 Keywords
Internet of things (IoT);Q-learning;Cloud computing;Virtual machine provisioning (VM provisioning);
 Language
Korean
 Cited by
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