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Open AccessJournal ArticleDOI

Wireless Power Transfer and Data Collection in Wireless Sensor Networks

TLDR
This paper investigates a novel optimal scheduling strategy, called EHMDP, aiming to minimize data packet loss from a network of sensor nodes in terms of the nodes’ energy consumption and data queue state information and shows that the proposed algorithm significantly improves the network performance.
Abstract
In a rechargeable wireless sensor network, the data packets are generated by sensor nodes at a specific data rate, and transmitted to a base station. Moreover, the base station transfers power to the nodes by using wireless power transfer (WPT) to extend their battery life. However, inadequately scheduling WPT and data collection causes some of the nodes to drain their battery and have their data buffer overflow, whereas the other nodes waste their harvested energy, which is more than they need to transmit their packets. In this paper, we investigate a novel optimal scheduling strategy, called EHMDP, aiming to minimize data packet loss from a network of sensor nodes in terms of the nodes’ energy consumption and data queue state information. The scheduling problem is first formulated by a centralized MDP model, assuming that the complete states of each node are well known by the base station. This presents the upper bound of the data that can be collected in a rechargeable wireless sensor network. Next, we relax the assumption of the availability of full state information so that the data transmission and WPT can be semidecentralized. The simulation results show that, in terms of network throughput and packet loss rate, the proposed algorithm significantly improves the network performance.

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Citations
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Journal ArticleDOI

Holistic Network Virtualization and Pervasive Network Intelligence for 6G

TL;DR: This tutorial paper looks into the evolution and prospect of network architecture and proposes a novel conceptual architecture for the 6th generation (6G) networks, which can facilitate three types of interplay, i.e., the interplay between digital twin and network slicing paradigms, between model-driven and data-driven methods for network management, and between virtualization and AI.
Journal ArticleDOI

Multi-Step Data Prediction in Wireless Sensor Networks Based on One-Dimensional CNN and Bidirectional LSTM

TL;DR: A novel model for multi-step sensory data prediction in wireless sensor network based on 1-D CNN (One-Dimensional Convolutional Neural Network) and Bi-LSTM (Bidirectional Long and Short-Term Memory) is proposed and its performance is better compared with other related methods.
Journal ArticleDOI

On-Board Deep Q-Network for UAV-Assisted Online Power Transfer and Data Collection

TL;DR: An on-board deep Q-network is developed to minimize the overall data packet loss of the sensing devices, by optimally deciding the device to be charged and interrogated for data collection, and the instantaneous patrolling velocity of the UAV.
Journal ArticleDOI

On Buffer-Constrained Throughput of a Wireless-Powered Communication System

TL;DR: The analysis and results, explicitly relating the throughput to the buffer constraint in addition to WPC characteristics, shed new light on the design and performance analysis of WPC systems.
Journal ArticleDOI

Mobile data gathering and energy harvesting in rechargeable wireless sensor networks

TL;DR: A near optimal buffer-battery-aware adaptive scheduling scheme is further proposed, in which the run-time status of the data buffer and battery are utilized and the performance of NO-BBA is close to that of Opt-JoDGE, especially when a certain delay is tolerable.
References
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Book

Markov Decision Processes: Discrete Stochastic Dynamic Programming

TL;DR: Puterman as discussed by the authors provides a uniquely up-to-date, unified, and rigorous treatment of the theoretical, computational, and applied research on Markov decision process models, focusing primarily on infinite horizon discrete time models and models with discrete time spaces while also examining models with arbitrary state spaces, finite horizon models, and continuous time discrete state models.
Journal ArticleDOI

Wireless Networks With RF Energy Harvesting: A Contemporary Survey

TL;DR: This paper presents an overview of the RF-EHNs including system architecture, RF energy harvesting techniques, and existing applications, and explores various key design issues according to the network types, i.e., single-hop networks, multiantenna networks, relay networks, and cognitive radio networks.
Journal ArticleDOI

Energy Harvesting Sensor Nodes: Survey and Implications

TL;DR: Various aspects of energy harvesting sensor systems- architecture, energy sources and storage technologies and examples of harvesting-based nodes and applications are surveyed and the implications of recharge opportunities on sensor node operation and design of sensor network solutions are discussed.
Journal ArticleDOI

Multiuser MISO Beamforming for Simultaneous Wireless Information and Power Transfer

TL;DR: This paper studies a multiuser multiple-input single-output (MISO) broadcast system for simultaneous wireless information and power transfer (SWIPT), where a multi-antenna access point sends information and energy simultaneously via beamforming to multiple single-antennas receivers.
Journal ArticleDOI

Energy Provisioning in Wireless Rechargeable Sensor Networks

TL;DR: The analysis shows that the deployment methods, by exploiting the physical characteristics of wireless recharging, can greatly reduce the number of readers compared with those assuming traditional coverage models.
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