(2025). An optimization framework for joint wireless data-power transmission in distributed energy harvesting networks. Computer Networks, 270, 111506. https://doi.org/10.1016/j.comnet.2025.111506
Περίληψη
In this paper, we address the challenge of performing effective joint wireless data-energy transfers in distributed mobile energy-harvesting networks. In principle, wireless power transfer resembles energy harvesting, however, it exhibits its own special features. We develop a holistic, backpressure-inspired technique, describing the evolution of each node’s queue-battery state, and we define an optimization problem with the objective of improving the balance of energy. We implement a dual Lagrange multipliers solution and determine the key variables influencing the system’s behavior. We investigate the overall energy transfer from the periphery to the core network in cases of traffic-stressed core nodes, and through analysis and simulation, we demonstrate the theoretical and practical potentials of this framework and its potential use for greener and self-sustainable networks.
- DOI
- 10.1016/j.comnet.2025.111506
- Τύπος
- Άρθρο σε Περιοδικό
- Έτος
- 2025
Σύνδεσμοι
BibTeX
@article{kallitsis2025optimization,
title = {An optimization framework for joint wireless data-power transmission in distributed energy harvesting networks},
author = {Georgios Kallitsis and Vasileios Karyotis and Symeon Papavassiliou},
url = {https://doi.org/10.1016/j.comnet.2025.111506},
doi = {10.1016/j.comnet.2025.111506},
year = {2025},
date = {2025-01-01},
journal = {Computer Networks},
volume = {270},
pages = {111506},
publisher = {Elsevier BV},
abstract = {In this paper, we address the challenge of performing effective joint wireless data-energy transfers in distributed mobile energy-harvesting networks. In principle, wireless power transfer resembles energy harvesting, however, it exhibits its own special features. We develop a holistic, backpressure-inspired technique, describing the evolution of each node’s queue-battery state, and we define an optimization problem with the objective of improving the balance of energy. We implement a dual Lagrange multipliers solution and determine the key variables influencing the system’s behavior. We investigate the overall energy transfer from the periphery to the core network in cases of traffic-stressed core nodes, and through analysis and simulation, we demonstrate the theoretical and practical potentials of this framework and its potential use for greener and self-sustainable networks.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}