Distributed DDPG-Based Resource Allocation for Age of Information Minimization in Mobile Wireless-Powered Internet of Things
As a vital metric of information timeliness, Age of Information (AoI) is important for real-time applications in Internet of Things (IoT), such as health monitoring. To satisfy these requirements, we study a wireless-powered IoT (WPIoT), where a static hybrid access point (HAP) coordinates wireless...
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Published in | IEEE internet of things journal Vol. 11; no. 17; pp. 29102 - 29115 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English Japanese |
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IEEE
01.09.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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Abstract | As a vital metric of information timeliness, Age of Information (AoI) is important for real-time applications in Internet of Things (IoT), such as health monitoring. To satisfy these requirements, we study a wireless-powered IoT (WPIoT), where a static hybrid access point (HAP) coordinates wireless energy transfer to mobile IoT nodes, and mobile IoT nodes transmit data to the HAP or static IoT nodes. We minimize the AoI of mobile IoT nodes by optimizing the selection of the HAP or static IoT node for transmission, the channel selection, the duration of data transmission, and the transmit power, and prove the AoI minimization problem as nondeterministic polynomial hard. To tackle it, we propose a deep deterministic policy gradient (DDPG)-based distributed multinode resource allocation (DDMRA) algorithm, which combines the advantages of the distributed algorithms and centralized algorithms, and combines the selection of discrete actions in the deep Q-network algorithm into the DDPG algorithm. In the DDMRA algorithm, mobile IoT nodes save the energy consumption of transmitting state information to the HAP. Numerical results validate the superior performance of the DDMRA algorithm compared with the baseline algorithms. |
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AbstractList | As a vital metric of information timeliness, Age of Information (AoI) is important for real-time applications in Internet of Things (IoT), such as health monitoring. To satisfy these requirements, we study a wireless-powered IoT (WPIoT), where a static hybrid access point (HAP) coordinates wireless energy transfer to mobile IoT nodes, and mobile IoT nodes transmit data to the HAP or static IoT nodes. We minimize the AoI of mobile IoT nodes by optimizing the selection of the HAP or static IoT node for transmission, the channel selection, the duration of data transmission, and the transmit power, and prove the AoI minimization problem as nondeterministic polynomial hard. To tackle it, we propose a deep deterministic policy gradient (DDPG)-based distributed multinode resource allocation (DDMRA) algorithm, which combines the advantages of the distributed algorithms and centralized algorithms, and combines the selection of discrete actions in the deep Q-network algorithm into the DDPG algorithm. In the DDMRA algorithm, mobile IoT nodes save the energy consumption of transmitting state information to the HAP. Numerical results validate the superior performance of the DDMRA algorithm compared with the baseline algorithms. |
Author | Luo, Rongwei Liu, Xiaoying Liu, Jia Qiu, Jiefan Zheng, Kechen |
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SubjectTerms | Age of Information (AoI) Algorithms Data transmission deep deterministic policy gradient (DDPG) Energy consumption Heuristic algorithms Internet of Things Minimization mobility Mobility models Nodes Optimization Polynomials Real time Remote monitoring Resource allocation Resource management Wireless sensor networks wireless-powered Internet of Things (WPIoT) |
Title | Distributed DDPG-Based Resource Allocation for Age of Information Minimization in Mobile Wireless-Powered Internet of Things |
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