OptiMoS: Optimal Sensing for Mobile Sensors
作者： Zhixian Yan , Julien Eberle , Karl Aberer
DOI: 10.1109/MDM.2012.43
关键词:
摘要: Both sensor coverage maximization and energy cost minimization are the fundamental requirements in design of real-life mobile sensing applications, e.g., (1) deploying environmental sensors (like CO2, fine particle measurement) on public transports to monitor air pollution, (2) analyzing smart phone embedded GPS, accelerometer) recognize people daily activities. However contradict each other: higher frequency takes, more is used, vise versa. In this paper, we a novel two-step process ("OptiMoS") achieve optimal that can effectively balance cost. first step, OptiMoS divides continuous readings into several segments, where one segment highly-correlated rather than amongst different segments. second identifies sampling for segment, selected guarantee reasonably high with limited rate. Various greedy near-optimal segmentation methods designed OptiMoS, evaluated using data from sensors.
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