Mobile crowd sensing enables large-scale sensing of the physical world at low cost by leveraging the available sensors on the mobile phones. One of the key factors for the success of mobile crowd sensing is uploading the sensing data to the cloud promptly. Traditional data uploading strategies leveraging whenever available networks may incur extra data cost, impact phone performance,, drain battery power significantly. In this paper, we propose an energy-efficient large data uploading framework using only WiFi network. Specifically, we propose to upload data at WiFi Ready Conditions (WRCs), when the WiFi network is connected, no front-end applications are using it. By forecasting the WRCs that will be encountered in a data uploading task, our framework intelligently selects optimal WRCs to minimize the overall energy consumption. Our evaluation results with the Device Analyzer Dataset show that the proposed method can effectively upload large data while consuming 30% less energy than the greedy-based baseline method.
['Longbiao Chen', 'Leye Wang', 'Daqing Zhang', 'Shijian Li', 'Gang Pan']
EnUp: Energy-Efficient Data Uploading for Mobile Crowd Sensing Applications