An Adaptive Transmission Power Control Algorithm for Wearable Healthcare Systems Based on Variations in the Body Conditions
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초록
In wearable healthcare systems, sensor devices can be deployed in places around the human body such as thestomach, back, arms, and legs. The sensors use tiny batteries, which have limited resources, and old sensorbatteries must be replaced with new batteries. It is difficult to deploy sensor devices directly into the humanbody. Therefore, instead of replacing sensor batteries, increasing the lifetime of sensor devices is more efficient. A transmission power control (TPC) algorithm is a representative technique to increase the lifetime of sensordevices. Sensor devices using a TPC algorithm control their transmission power level (TPL) to reduce batteryenergy consumption. The TPC algorithm operates on a closed-loop mechanism that consists of two parts, suchas sensor and sink devices. Most previous research considered only the sink part of devices in the closed-loop. If we consider both the sensor and sink parts of a closed-loop mechanism, sensor devices reduce energyconsumption more than previous systems that only consider the sensor part. In this paper, we propose a newapproach to consider both the sensor and sink as part of a closed-loop mechanism for efficient energymanagement of sensor devices. Our proposed approach judges the current channel condition based on thevalues of various body sensors. If the current channel is not optimal, sensor devices maintain their current TPLwithout communication to save the sensor’s batteries. Otherwise, they find an optimal TPL. To compareperformance with other TPC algorithms, we implemented a TPC algorithm and embedded it into sensordevices. Our experimental results show that our new algorithm is better than other TPC algorithms, such aslinear, binary, hybrid, and ATPC.
Abstract
In wearable healthcare systems, sensor devices can be deployed in places around the human body such as thestomach, back, arms, and legs. The sensors use tiny batteries, which have limited resources, and old sensorbatteries must be replaced with new batteries. It is difficult to deploy sensor devices directly into the humanbody. Therefore, instead of replacing sensor batteries, increasing the lifetime of sensor devices is more efficient. A transmission power control (TPC) algorithm is a representative technique to increase the lifetime of sensordevices. Sensor devices using a TPC algorithm control their transmission power level (TPL) to reduce batteryenergy consumption. The TPC algorithm operates on a closed-loop mechanism that consists of two parts, suchas sensor and sink devices. Most previous research considered only the sink part of devices in the closed-loop. If we consider both the sensor and sink parts of a closed-loop mechanism, sensor devices reduce energyconsumption more than previous systems that only consider the sensor part. In this paper, we propose a newapproach to consider both the sensor and sink as part of a closed-loop mechanism for efficient energymanagement of sensor devices. Our proposed approach judges the current channel condition based on thevalues of various body sensors. If the current channel is not optimal, sensor devices maintain their current TPLwithout communication to save the sensor’s batteries. Otherwise, they find an optimal TPL. To compareperformance with other TPC algorithms, we implemented a TPC algorithm and embedded it into sensordevices. Our experimental results show that our new algorithm is better than other TPC algorithms, such aslinear, binary, hybrid, and ATPC.
참고문헌 (19)
- D. E. Knuth, "The Art of Computer Programming (Volume 3. Sorting and Searching)" (1998), Addison-Wesley
- T. H. Cormen, "Introduction to Algorithms" (2009), MIT Press
- M. Quwaider, "Body-posture-based dynamic link power control in wearable sensor networks", IEEE Communications Magazine, 48(7), pp.134~142 (2010)
- W. S. Lee, "Experimental link channel characteristics in wireless body sensor systems", Proceedings of the International Conference on Information Network 2012, pp.374~378 (2012)
- W. Lee, "Network and Parallel Computing", pp.308~314 (2012), Springer
- 이우식, "An Accelerometer-Assisted Power Management for Wearable Sensor Systems", KSII Transactions on Internet and Information Systems, 9(1), pp.318~330 (2015), 한국인터넷정보학회[DOI]
- W. Lee, "Hybrid transmission power control for wireless body sensor systems", International Journal of Distributed Sensor Networks (2014)[DOI]
- W. Lee, "Comparisons of transmission power control algorithms in wireless body sensor systems", International Journal of Multimedia and Ubiquitous Engineering, 8(4), pp.303~311 (2013)
- W. Lee, "Extended dynamic transmission power control algorithm in wireless body sensor network systems", International Journal of Control and Automation, 6(6), pp.339~350 (2013)
- N. Kim, "Equation-based transmission power control for wearable sensor systems", IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, 98(7), pp.1558~1561 (2015)
- W. Zang, "Motion aware transmission power control scheme in wireless body area network", Proceedings of 2015 IEEE Workshop on Signal Processing Systems (SiPS), pp.1~5 (2015)
- G. Newell, "Human-motion based transmission power control in wireless body area networks", Proceedings of 2016 IEEE 3rd World Forum on Internet of Things (WF-IoT), pp.277~282 (2016)
- A. H. Sodhro, "Energy-efficient adaptive transmission power control for wireless body area networks", IET Communications, 10(1), pp.81~90 (2016)
- W. Zang, "An accelerometer-assisted transmission power control solution for energy-efficient communications in WBAN", IEEE Journal on Selected Areas in Communications, 34(12), pp.3427~3437 (2016)
- Y. Zhang, "A relay-aided transmission power control method in wireless body area networks", IEEE Access, 5, pp.8408~8418 (2017)
- W. Zang, "Gait-cycle-driven transmission power control scheme for a wireless body area network", IEEE Journal of Biomedical and Health Informatics, 22(3), pp.697~706 (2017)
- Y. Li, "MAPM: movement-based adaptive prediction mechanism for energy conservation in body sensor networks", Proceedings of 2016 IEEE Global Communications Conference (GLOBECOM), pp.1~6 (2016)
- B. Moulton, "Body-area-network transmission power control using variable adaptive feedback periodicity", Proceedings of 2010 Australian Communications Theory Workshop (AusCTW), pp.139~144 (2010)
- S. Kim, "RSSI", LQI-based transmission power control for body area networks in healthcare environment, 2013, pp.17(3), 561~571