TY - GEN
T1 - Achieving Ultra Energy-efficient and Collision-free Data Collection in Wake-up Radio Enabled mIoT
AU - Hsu, Chia An
AU - Li, Frank Y.
AU - Chen, Chiuyuan
AU - Tseng, Yu Chee
PY - 2020/6/7
Y1 - 2020/6/7
N2 - To achieve ultra-low energy consumption and decade-long battery lifetime for Internet of things (IoT) networks, wake-up radio (WuR) appears as an eminent solution. While keeping devices in deep sleep for most of the time, a WuR enabled IoT device can be woken up for data transmission at any time by a wake-up call (WuC). However, collisions happen among WuCs for transmitter-initiated data reporting and among data packets for receiver-initiated data collection. In this paper, we propose two novel hashing-based schemes in order to achieve collisionfree data transmissions for receiver-initiated data collection. We consider first a simple scenario in which all devices in a region of interest are covered by a data collector and propose a scheme which facilitates a scheduled time for data uploading of each device. Then we extend our scheme to cover a more realistic scenario where IoT devices are distributed across a larger region that cannot be covered by a single data collector. In this case, we propose a partitioning algorithm for data collection across multiple partitions. Both analysis and simulations are performed to demonstrate the effectiveness of the proposed schemes.
AB - To achieve ultra-low energy consumption and decade-long battery lifetime for Internet of things (IoT) networks, wake-up radio (WuR) appears as an eminent solution. While keeping devices in deep sleep for most of the time, a WuR enabled IoT device can be woken up for data transmission at any time by a wake-up call (WuC). However, collisions happen among WuCs for transmitter-initiated data reporting and among data packets for receiver-initiated data collection. In this paper, we propose two novel hashing-based schemes in order to achieve collisionfree data transmissions for receiver-initiated data collection. We consider first a simple scenario in which all devices in a region of interest are covered by a data collector and propose a scheme which facilitates a scheduled time for data uploading of each device. Then we extend our scheme to cover a more realistic scenario where IoT devices are distributed across a larger region that cannot be covered by a single data collector. In this case, we propose a partitioning algorithm for data collection across multiple partitions. Both analysis and simulations are performed to demonstrate the effectiveness of the proposed schemes.
UR - http://www.scopus.com/inward/record.url?scp=85089413261&partnerID=8YFLogxK
U2 - 10.1109/ICC40277.2020.9149361
DO - 10.1109/ICC40277.2020.9149361
M3 - Conference contribution
AN - SCOPUS:85089413261
T3 - IEEE International Conference on Communications
BT - 2020 IEEE International Conference on Communications, ICC 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE International Conference on Communications, ICC 2020
Y2 - 7 June 2020 through 11 June 2020
ER -