doi: 10.7763/IJCTE.2019.V11.1248
Mobile Access Control Based on Trajectory Analysis and Prediction for Uploading Data
Li Chen
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- College of Mathematics Physics and Information Engineering, Jiaxing University, Jiaxing 314001, China.
Abstract
For large-scale mobile data collection, e.g environmental monitoring, mobile sensing nodes upload sensory data which they have collected via WiFi. Within Internet access point’s (AP) communication range that they can access Internet by AP to do it. However, unfortunately communication resources of APs are quite scarce to the huge amount of sensory data that have to be uploaded. To address these problems in existing research on access request scheduling, this paper builds a dynamic model for quantifying uncertain space-time features of network and mobile access requests, then predict the future revenues of them. Based on it, reverse affects the optimization of the current strategy. This paper proposes an approximation algorithm to solve the optimization of the current strategy based on dynamic models of mobile access requests. Simulation results verify that SOA consistently outperforms the existing algorithm.
Keywords
- Mobile sensing nodes (MSN)
- data collection
- mobile crowd sensing
- time to live (TTL)
How to Cite
Li Chen, Kun Deng, Jun Yang, Panpan Li, Tao Jiang, and Tao He, "Mobile Access Control Based on Trajectory Analysis and Prediction for Uploading Data," International Journal of Computer Theory and Engineering, vol. 11, no. 5, pp. 84-88, 2019. https://doi.org/10.7763/IJCTE.2019.V11.1248
Copyright & License
Copyright © 2019 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).