Lishan Yang
ABSTRACT
As an imperative role of Industrial Internet of Things, data acquisition system has been considered as a promising and useful technology to realize the interconnections among industrial devices and to promote interoperability. Since balanced energy utilization is benefit to extend the network lifetime, we propose an energy-balancing data acquisition strategy via employing graph signal sampling-set rotation method based on edge computing architecture. The IIoT network is partitioned into several clusters for satisfying the requirement of balanced energy consumption, and the lower bound of sampling ratio is introduced. Besides, a weighted probability model is introduced to rotate the sampling vertices within clusters. Simulation results demonstrate the effectiveness of the proposed sampling-set rotation strategy on the reconstruction performance and sensitivity with different graph cut-off frequencies. Finally, the temperature data collected by the weather stations across the United States is employed as the real-world data example to verify the performance of the proposed strategy.
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Index Terms
- Energy-Balancing Data Acquisition Strategy by Employing Graph Signal Sampling-set Rotation Method for Edge Computing Enabled Industrial Internet of Things
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