期刊
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
卷 17, 期 10, 页码 7075-7084出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TII.2020.3025510
关键词
Transmitters; Sensors; Job shop scheduling; Optimization; Reliability; Internet of Things; Wireless sensor networks; Internet of Things (IoT); mobile edge computing (MEC); on-demand sensing; wireless power transfer (WPT)
类别
资金
- Natural Sciences, and Engineering Research Council of Canada (NSERC)
The paper proposes an energy-aware mode switching strategy for IoT nodes to perform either on-demand sensing or dedicated wireless power transfer. It includes a scheduling scheme to maximize the utility of IoT nodes by considering residual energy and energy required for sensing tasks, as well as a transmitter scheduling scheme to minimize charging costs while keeping IoT nodes sufficiently charged. Simulation results show significant energy reduction in the overall system with less than 50% of IoT nodes and less than 60% of energy transmitters activated in all scenarios.
On-demand data sensing and wireless power transfer (WPT) can provide sustainability and robust operations in large-scale industrial Internet of Things (IoT) networks. The efficiency of on-demand data collection and WPT can be increased by efficient scheduling of IoT nodes and dedicated energy transmitters respectively. In this article, we propose an energy-aware mode switching strategy to enable IoT nodes to perform either on-demand sensing or dedicated WPT. For on-demand sensing, we propose an IoT node scheduling scheme to maximize the utility of the IoT nodes comprising residual energy and energy required for sensing operation while considering the reliability of sensing tasks. For WPT, we propose an energy transmitter scheduling scheme for IoT nodes to minimize the cost of charging while keeping IoT nodes sufficiently charged. The simulation results for IoT node scheduling demonstrate that less than 50% IoT nodes need to be activated in all scenarios to complete the tasks. The proposed energy transmitter scheduling scheme shows that less than 60% energy transmitters should be scheduled in all the scenarios which results in significant energy reduction in the overall system.
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