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Erschienen in:
2011 | OriginalPaper | Buchkapitel
An Adaptive WiFi Rate Selection Algorithm for Moving Vehicles with Motion Prediction
verfasst von : Jianwei Niu, Yuhang Gao, Shaohui Guo, Chao Tong, Guoping Du
Erschienen in: Future Information Technology
Verlag: Springer Berlin Heidelberg
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With the proliferation of Wi-Fi devices, many cities have been covered by Wi-Fi network; it is increasingly important for people in moving vehicles to be able to access the Internet using Wi-Fi devices. Since the signal strength varies dramatically for WiFi devices in moving Vehicles, it is necessary for the data-rate of Wi-Fi devices to be adjusted dynamically. In this paper, we propose an Adaptive Wi-Fi Data-rate Selection (AWDS) algorithm based on motion predication. By detecting the signal strength of APs, Wi-Fi devices on the move are able to predicate the motion model of vehicles, and to select data rate of Wi-Fi devices accordingly. In this way, Wi-Fi rate selection will be more consistent with its wireless surroundings in the future period of time. Experiment results demonstrate that the AWDS algorithm outperforms the rate selection algorithm built in Android G1.