Journal
IEEE INTERNET OF THINGS JOURNAL
Volume 6, Issue 5, Pages 9165-9174Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2019.2928557
Keywords
Collaborative charge; Industrial Internet of Things (IIoT); optimization; wireless rechargeable sensor networks (WRSNs)
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Funding
- National Key Research and Development Program [2017YFE0125300]
- National Natural Science Foundation of China-Guangdong Joint Fund [U1801264]
- Jiangsu Key Research and Development Program [BE2019648]
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Wireless sensor networks (WSNs) are an important core of the Industrial Internet of Things (IIoT). Wireless rechargeable sensor networks (WRSNs) are sensor networks that are charged by mobile chargers (MCs), and can achieve self-sufficiency. Therefore, the development of WRSNs has begun to attract widespread attention in recent years. Most of the existing energy replenishment algorithms for MCs use one or more MCs to serve the whole network in WRSNs. However, a single MC is not suitable for large-scale network environments, and multiple MCs make the network cost too high. Thus, this paper proposes a collaborative charging algorithm based on network density clustering (CCA-NDC) in WRSNs. This algorithm uses the mean-shift algorithm based on density to cluster, and then the mother wireless charger vehicle (MWCV) carries multiple sub wireless charger vehicles (SWCVs) to charge the nodes in each cluster by using a gradient descent optimization algorithm. The experimental results confirm that the proposed algorithm can effectively replenish the energy of the network and make the network more stable.
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