Affiliation:
1. Department of Computer Engineering, Sungkyul University, Anyang 14097, Republic of Korea
2. Department of Convergence Security Engineering, Sungshin Women’s University, Seoul 02844, Republic of Korea
Abstract
Efficient energy management is a significant task in Internet-of-Things (IoT) devices because typical IoT devices have the constraint of a limited power supply. In particular, energy harvesting IoT devices must be tolerant of complex and varying temporal/spatial environments for energy availability. Several schemes have been proposed to manage energy usage in IoT devices, such as duty-cycle control, transmission power control, and task scheduling. However, these approaches need to deal with the operating conditions particular to energy harvesting devices, e.g., power depletion according to energy harvesting conditions. In this paper, regarding a wireless sensor network (WSN) as a representative IoT device, we propose an Energy Intelligence Platform Module (EIPM) for energy harvesting WSNs. The EIPM provides harvested energy status prediction, checkpointing, and task execution control to ensure continuous operation according to energy harvesting conditions while minimizing required hardware/software overheads such as additional measurement components and computations. Our experiment results demonstrate that the EIPM successfully enables a device to cope with energy insufficiency under various harvesting conditions.
Funder
Sungshin Women’s University Research