Abstract
With the development and spread of Internet of Things (IoT) technology, various kinds of data are now being generated from IoT devices, and the number of such data is expected to increase significantly in the future. Data that depends on geographical location and time is commonly referred to as spatio-temporal data (STD). Since the “locally produced and consumed” paradigm of STD use is effective for location-dependent applications, the authors have previously proposed using a STD retention system for high mobility vehicles equipped with high-capacity storage modules, high-performance computing resources, and short-range wireless communication equipment. In this system, each vehicle controls its data transmission probability based on the neighboring vehicle density in order to achieve not only high coverage but also reduction of the number of data transmissions. In this paper, we propose a data transmission control method for STD retention in low vehicle density environments. The results of simulations conducted in this study show that our proposed scheme can improve data retention performance while limiting the number of data transmissions to the lowest level possible.
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Acknowledgements
This work supported in part by JSPS KAKENHI Grant Number 18H03234, NICT Grant Number 19304, and USA Grant number NSF 17-586.
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Goto, I., Nobayashi, D., Tsukamoto, K., Ikenaga, T., Lee, M. (2020). Transmission Control Method to Realize Efficient Data Retention in Low Vehicle Density Environments. In: Barolli, L., Nishino, H., Miwa, H. (eds) Advances in Intelligent Networking and Collaborative Systems. INCoS 2019. Advances in Intelligent Systems and Computing, vol 1035. Springer, Cham. https://doi.org/10.1007/978-3-030-29035-1_38
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DOI: https://doi.org/10.1007/978-3-030-29035-1_38
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