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The expansion of 802.11 AP deployment provides opportunistic Wi-Fi access in underground mass rapid transit (MRT) system. However, such vehicular network faces the challenge of limited time for the MS on the train to connect the base station at the station. Therefore, to maximize the throughput within these several tens of seconds becomes crucial to the network. To achieve this goal, we propose accelerometer-assisted rate adaptation (AARA), a mechanism utilizes the out-of-band information of a train’s acceleration to improve the conventional rate adaptation scheme. AARA consists of two parts: First, AARA divides a train’s movement into four phases and performs real-time estimation on the train’s current movement phase. Second, AARA employs the estimation results to enhance the bit-rate selection during each phase. We conduct experiments on two different Taipei MRT systems: high-capacity MRT and medium-capacity MRT. The experimental results show that the average throughput of AARA outperforms that of the conventional scheme in different scenarios. In addition, we also design a mechanism of power saving with the aid of the movement estimation. |
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