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A Dynamic Pricing Mechanism in IoT for DaaS: A Reinforcement Learning Approach

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1075))

Abstract

With the rapid development of the Internet of things, a large amount of data has been accumulated. However, how to make full use of these data has become a new problem. In this article, we will focus on how to develop data resources using the intelligent data pricing (SDP) approach. Establish a B2B data marketplace for integrating, storing, and analyzing business data. Simulate interactions between service providers and enterprises in the marketplace. Since the service provider has markov consciousness, q-learning algorithm is adopted to solve the model. Experimental results show that q-learning algorithm can make every participant in the market obtain the optimal profit.

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Acknowledgment

This work is supported by the National Key Research and Development Program of China (2016YFB1001100).

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Correspondence to Jian Ye .

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Song, B., Song, J., Ye, J. (2020). A Dynamic Pricing Mechanism in IoT for DaaS: A Reinforcement Learning Approach. In: Liu, Y., Wang, L., Zhao, L., Yu, Z. (eds) Advances in Natural Computation, Fuzzy Systems and Knowledge Discovery. ICNC-FSKD 2019. Advances in Intelligent Systems and Computing, vol 1075. Springer, Cham. https://doi.org/10.1007/978-3-030-32591-6_65

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