Abstract
This paper proposes a data management platform using a fog computing model. It enables to construct of dynamic user data plane adapted to diverse range and several kinds of functions for these users. In particular, this paper implements a sample recommendation application of movie information being able to control the data on fog nodes. However, this paper does not include the quantitative evaluation applying to application services.
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References
Reuters: Facebook says data leak hits 87 million users, widening privacy scandal. https://www.reuters.com/article/us-facebook-privacy/facebook-says-data-leak-hits-87-million-users-widening-privacy-scandal-idUSKCN1HB2CM
New York Times: How Trump Consultants Exploited the Facebook Data of Millions. https://www.nytimes.com/2018/03/17/us/politics/cambridge-analytica-trump-campaign.html
Hashida, K.: Decentralized PDS and information bank total optimization of life and industry by ecentralized big data. Inf. Manag. 60(4), 251–260 (2017)
Alrawais, A., Alhothaily, A., Hu, C., Cheng, X.: Fog computing for the Internet of Things: security and privacy issues. IEEE Internet Comput. 21(2), 34–42 (2017)
Dubey, H., et al.: Fog computing in medical Internet-of-Things: architecture, implementation, and applications. In: Khan, Samee U., Zomaya, Albert Y., Abbas, Assad (eds.) Handbook of Large-Scale Distributed Computing in Smart Healthcare. SCC, pp. 281–321. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-58280-1_11
Tsuchiya, T., Miyosawa, T., Hirose, H., Koyanagi, K.: Virtualization model of a large logical database for diffused data by peer-to-peer cloud computing technology. In: Proceeding of the Thirteenth International Conference on Networks, February 2014
Yoshinaga, H., Tsuchiya, T., Koyanagi, K.: Scalable and persistent multimedia data management system using the distributed interval trees, In: Proceedings of Euro IMSA, pp. 86–92, July 2009
Node.js. https://nodejs.org/
Docker. https://www.docker.com/
MyAnimeListDataset. https://www.kaggle.com/azathoth42/myanimelist
Barkan, O., Koenigstein, N.: Item2Vec: neural item embedding for collaborative filtering. In: IEEE 26th International Workshop on Machine Learning for Signal Processing (2016)
Acknowledgement
This work was partly supported by MEXT KAKENHI Grant Number 17K01149.
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Tsuchiya, T. et al. (2019). Dynamic Data Management Strategy on Cloud Network by Fog Computing Model. In: Dang, T., Küng, J., Takizawa, M., Bui, S. (eds) Future Data and Security Engineering. FDSE 2019. Lecture Notes in Computer Science(), vol 11814. Springer, Cham. https://doi.org/10.1007/978-3-030-35653-8_22
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DOI: https://doi.org/10.1007/978-3-030-35653-8_22
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