LAPSE:2023.14883
Published Article

LAPSE:2023.14883
Zero-Energy Computation Offloading with Simultaneous Wireless Information and Power Transfer for Two-Hop 6G Fog Networks
March 2, 2023
Abstract
Currently, we are faced with an ever-increasing number of devices and objects connected to the Internet aimed at creating the so-called Internet of Things framework, fostering the creation of a connected world of objects. One of the main challenges we are actually facing is constituted by the constrained sizes of such objects: reduced memory, reduced computational capacity, and reduced battery sizes. Particular attention should be devoted to energy efficiency, since a potential energy shortage would negatively impact not only its operation but also network-wide operation, considering the tight connections among any object. According to the 6G system’s use-case related to self-sustainability and zero-energy networks, this paper focuses on an energy-efficient fog network architecture for IoT scenarios, jointly implementing computation offloading operations and simultaneous wireless information and power Transfer (SWIPT), hence, enabling the possibility of jointly transferring energy and computational tasks among the nodes. The system under consideration is composed of three nodes, where an access point (AP) is considered to be always connected to the power network, while a relay node and an end node can harvest energy from the AP. The proposed solution allows to jointly optimize the computation offloading and the energy harvesting phases while maximizing the network lifetime, so as to maximize the operational time of the network. Numerical results obtained on MATLAB demonstrate that the proposed algorithm performs better than the other benchmarks considered for comparison.
Currently, we are faced with an ever-increasing number of devices and objects connected to the Internet aimed at creating the so-called Internet of Things framework, fostering the creation of a connected world of objects. One of the main challenges we are actually facing is constituted by the constrained sizes of such objects: reduced memory, reduced computational capacity, and reduced battery sizes. Particular attention should be devoted to energy efficiency, since a potential energy shortage would negatively impact not only its operation but also network-wide operation, considering the tight connections among any object. According to the 6G system’s use-case related to self-sustainability and zero-energy networks, this paper focuses on an energy-efficient fog network architecture for IoT scenarios, jointly implementing computation offloading operations and simultaneous wireless information and power Transfer (SWIPT), hence, enabling the possibility of jointly transferring energy and computational tasks among the nodes. The system under consideration is composed of three nodes, where an access point (AP) is considered to be always connected to the power network, while a relay node and an end node can harvest energy from the AP. The proposed solution allows to jointly optimize the computation offloading and the energy harvesting phases while maximizing the network lifetime, so as to maximize the operational time of the network. Numerical results obtained on MATLAB demonstrate that the proposed algorithm performs better than the other benchmarks considered for comparison.
Record ID
Keywords
computation offloading, energy harvesting, fog computing, wireless power transfer, zero energy devices
Subject
Suggested Citation
Tarchi D, Bozorgchenani A, Gebremeskel MD. Zero-Energy Computation Offloading with Simultaneous Wireless Information and Power Transfer for Two-Hop 6G Fog Networks. (2023). LAPSE:2023.14883
Author Affiliations
Tarchi D: Department of Electrical, Electronic and Information Engineering “Guglielmo Marconi”, University of Bologna, 40136 Bologna, Italy [ORCID]
Bozorgchenani A: School of Computing and Communications, Lancaster University, Lancaster LA1 4WA, UK [ORCID]
Gebremeskel MD: Department of Electrical, Electronic and Information Engineering “Guglielmo Marconi”, University of Bologna, 40136 Bologna, Italy
Bozorgchenani A: School of Computing and Communications, Lancaster University, Lancaster LA1 4WA, UK [ORCID]
Gebremeskel MD: Department of Electrical, Electronic and Information Engineering “Guglielmo Marconi”, University of Bologna, 40136 Bologna, Italy
Journal Name
Energies
Volume
15
Issue
5
First Page
1632
Year
2022
Publication Date
2022-02-22
ISSN
1996-1073
Version Comments
Original Submission
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PII: en15051632, Publication Type: Journal Article
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LAPSE:2023.14883
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https://doi.org/10.3390/en15051632
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Mar 2, 2023
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