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      다국어 초록 (Multilingual Abstract)

      With the spread of smartphones containing multiple on-board sensors, the market for context aware applications have grown. However, due to the limited power capacity of a smartphone, users feel discontented QoS. Additionally, context aware application...

      With the spread of smartphones containing multiple on-board sensors, the market for context aware applications have grown. However, due to the limited power capacity of a smartphone, users feel discontented QoS. Additionally, context aware applications require the utilization of many forms of context and sensing information. If context transition has occurred, types of needed sensors must be changed and each sensor modules need to turn on/off. In addition, excessive sensing has been found when the context decision is ambiguous. In this paper, we focus on power consumption associated with the context transition that occurs during indoor/outdoor detection, modeling the activities of the sensor associated with these contexts. And we suggest a freezing algorithm that reduces power consumption in context transition. We experiment with a commercial application that service is indoor/outdoor location tracking, measure power consumption in context transition with and without the utilization of the proposed method. We find that proposed method reduces power consumption about 20% during context transition.

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      참고문헌 (Reference)

      1 최기용, "모바일 기기의 전력 측정을 위한 휴대용 시스템" 한국정보과학회 20 (20): 131-142, 2014

      2 O. Canovas, "WiFiBoost: a terminal-based method for detection of indoor/outdoor places" 2014

      3 Y. Liu, "Where has my battery gone? Finding sensor related energy black holes in smartphone applications" 2-10, 2013

      4 H. J. Kim, "Trends of Mobile App. Analytics Plaform" 29 (29): 50-60, 2014

      5 G. D. Abowd, "Towards a Better Understanding of Context and Context-Awareness" 304-307, 1999

      6 I. Manotas, "SEEDS: a software engineer's energy-optimization decision support framework" 503-514, 2014

      7 S. Park, "Reducing Energy Consumption of Alarm-induced Wake-ups on Android Smartphones" 33-38, 2015

      8 S. He, "Optimizing Smartphone Power Consumption through Dynamic Resolution Scaling" 27-39, 2015

      9 D. Li, "Making web applications more energy efficient for OLED smartphones" 527-538, 2014

      10 P. Zhou, "IODetector: a generic service for indoor outdoor detection" 113-126, 2012

      1 최기용, "모바일 기기의 전력 측정을 위한 휴대용 시스템" 한국정보과학회 20 (20): 131-142, 2014

      2 O. Canovas, "WiFiBoost: a terminal-based method for detection of indoor/outdoor places" 2014

      3 Y. Liu, "Where has my battery gone? Finding sensor related energy black holes in smartphone applications" 2-10, 2013

      4 H. J. Kim, "Trends of Mobile App. Analytics Plaform" 29 (29): 50-60, 2014

      5 G. D. Abowd, "Towards a Better Understanding of Context and Context-Awareness" 304-307, 1999

      6 I. Manotas, "SEEDS: a software engineer's energy-optimization decision support framework" 503-514, 2014

      7 S. Park, "Reducing Energy Consumption of Alarm-induced Wake-ups on Android Smartphones" 33-38, 2015

      8 S. He, "Optimizing Smartphone Power Consumption through Dynamic Resolution Scaling" 27-39, 2015

      9 D. Li, "Making web applications more energy efficient for OLED smartphones" 527-538, 2014

      10 P. Zhou, "IODetector: a generic service for indoor outdoor detection" 113-126, 2012

      11 "GeoLog"

      12 H. Shen, "Enhancing Mobile Apps To Use Sensor Hubs Without Programmer Effort" 227-238, 2015

      13 J. Cheon, "Development of Testing of BMT Model for Evaluating Power Consumption of Mobile Context-Aware Application" Ajou University 2015

      14 P. Georgiev, "DSP.ear: Leveraging Co-Processor Support for Continuous Audio Sensing on Smartphones" 295-309, 2014

      15 C. Perera, "Context Aware Computing for The Internet of Things: A Survey" 16 (16): 414-454, 2013

      16 "Android Open Source Project"

      17 L. Xhang, "AccelWord: Energy Efficient Hotword Detection through Accelerometer" 301-315, 2015

      18 R. Valentin, "A Semi-Supervised Learning Approach for Robust Indoor-Outdoor Detection with Smartphones" 280-294, 2014

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2021 평가예정 계속평가 신청대상 (등재유지)
      2016-01-01 평가 우수등재학술지 선정 (계속평가)
      2015-01-01 평가 등재학술지 유지 (등재유지) KCI등재
      2002-01-01 평가 학술지 통합 (등재유지) KCI등재
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      학술지 인용정보

      학술지 인용정보
      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0.19 0.19 0.19
      KCIF(4년) KCIF(5년) 중심성지수(3년) 즉시성지수
      0.2 0.18 0.373 0.07
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