TY - GEN
T1 - ATHOME
T2 - 2nd IEEE/ACM International Conference on Internet-of-Things Design and Implementation, IoTDI 2017
AU - Dong, Zheng
AU - Gu, Yu
AU - Fu, Lingkun
AU - Chen, Jiming
AU - He, Tian
AU - Liu, Cong
N1 - Publisher Copyright:
© 2017 ACM.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2017/4/18
Y1 - 2017/4/18
N2 - We present ATHOME, an Automatic Tunable wireless charging framework for smart low-power devices in current and future HOME. ATHOME automatically tunes the charging power of multiple stationary wireless chargers to provide enough energy that can continuously power up smart devices with varying working power profiles, while minimizing the total charging power to reduce energy cost. To reach this goal, ATHOME first solves a hard open problem of calculating the minimum required charging power for powering up a device with limited energy storage size and varying power profile. Based on the minimum charging power obtained for each device, ATHOME then provides an optimal solution with polynomial-time complexity that automatically tunes the charging power of all chargers in a real-time fashion, which enables all devices to work continuously while minimizing total charging power. We implement ATHOME on a WISP platform with 8 rechargeable nodes. Experiments demonstrate that ATHOME provides sufficient and tight charging power that enables devices to work continuously.
AB - We present ATHOME, an Automatic Tunable wireless charging framework for smart low-power devices in current and future HOME. ATHOME automatically tunes the charging power of multiple stationary wireless chargers to provide enough energy that can continuously power up smart devices with varying working power profiles, while minimizing the total charging power to reduce energy cost. To reach this goal, ATHOME first solves a hard open problem of calculating the minimum required charging power for powering up a device with limited energy storage size and varying power profile. Based on the minimum charging power obtained for each device, ATHOME then provides an optimal solution with polynomial-time complexity that automatically tunes the charging power of all chargers in a real-time fashion, which enables all devices to work continuously while minimizing total charging power. We implement ATHOME on a WISP platform with 8 rechargeable nodes. Experiments demonstrate that ATHOME provides sufficient and tight charging power that enables devices to work continuously.
KW - Internet-of-things
KW - Wireless rechargeable sensor network
UR - http://www.scopus.com/inward/record.url?scp=85019019033&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85019019033&partnerID=8YFLogxK
U2 - 10.1145/3054977.3054990
DO - 10.1145/3054977.3054990
M3 - Conference contribution
AN - SCOPUS:85019019033
T3 - Proceedings - 2017 IEEE/ACM 2nd International Conference on Internet-of-Things Design and Implementation, IoTDI 2017 (part of CPS Week)
SP - 133
EP - 143
BT - Proceedings - 2017 IEEE/ACM 2nd International Conference on Internet-of-Things Design and Implementation, IoTDI 2017 (part of CPS Week)
PB - Association for Computing Machinery, Inc
Y2 - 18 April 2017 through 20 April 2017
ER -