Significant Motion-Based Adaptive Sampling Module for Mobile Sensing Framework
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초록
Many mobile sensing frameworks have been developed to help researcher doing their mobile sensingresearch. However, energy consumption is still an issue in the mobile sensing research, and the existingframeworks do not provide enough solution for solving the issue. We have surveyed several mobile sensingframeworks and carefully chose one framework to improve. We have designed an adaptive sampling modulefor a mobile sensing framework to help solve the energy consumption issue. However, in this study, we limitour design to an adaptive sampling module for the location and motion sensors. In our adaptive samplingmodule, we utilize the significant motion sensor to help the adaptive sampling. We experimented with twosampling strategies that utilized the significant motion sensor to achieve low-power consumption during thecontinuous sampling. The first strategy is to utilize the sensor naively only while the second one is to add theduty cycle to the naive approach. We show that both strategies achieve low energy consumption, but the onethat is combined with the duty cycle achieves better result.
Abstract
Many mobile sensing frameworks have been developed to help researcher doing their mobile sensingresearch. However, energy consumption is still an issue in the mobile sensing research, and the existingframeworks do not provide enough solution for solving the issue. We have surveyed several mobile sensingframeworks and carefully chose one framework to improve. We have designed an adaptive sampling modulefor a mobile sensing framework to help solve the energy consumption issue. However, in this study, we limitour design to an adaptive sampling module for the location and motion sensors. In our adaptive samplingmodule, we utilize the significant motion sensor to help the adaptive sampling. We experimented with twosampling strategies that utilized the significant motion sensor to achieve low-power consumption during thecontinuous sampling. The first strategy is to utilize the sensor naively only while the second one is to add theduty cycle to the naive approach. We show that both strategies achieve low energy consumption, but the onethat is combined with the duty cycle achieves better result.
참고문헌 (28)
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