Green Communication for Sixth-Generation Intent-Based Networks: An Architecture Based on Hybrid Computational Intelligence Algorithm
| Autor: | Mohamed Abdel-Basset, Mohamed Elhoseny, Laila Abdel-Fatah, Khalid A. Eldrandaly, Nabil M. AbdelAziz |
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| Rok vydání: | 2021 |
| Předmět: |
Technology
Data collection Article Subject Computer Networks and Communications Computer science Node (networking) Interoperability 020206 networking & telecommunications Computational intelligence TK5101-6720 02 engineering and technology Transmission (telecommunications) Telecommunication 0202 electrical engineering electronic engineering information engineering Key (cryptography) 020201 artificial intelligence & image processing Electrical and Electronic Engineering Architecture Algorithm Generalized normal distribution Information Systems |
| Zdroj: | Wireless Communications and Mobile Computing, Vol 2021 (2021) |
| ISSN: | 1530-8677 1530-8669 |
| Popis: | The sixth-generation (6G) is envisioned as a pivotal technology that will support the ubiquitous seamless connectivity of substantial networks. The main advantage of 6G technology is leveraging Artificial Intelligence (AI) techniques for handling its interoperable functions. The pairing of 6G networks and AI creates new needs for infrastructure, data preparation, and governance. Thus, Intent-Based Network (IBN) architecture is a key infrastructure for 6G technology. Usually, these networks are formed of several clusters for data gathering from various heterogeneities in devices. Therefore, an important problem is to find the minimum transmission power for each node in the network clusters. This paper presents hybridization between two Computational Intelligence (CI) algorithms called the Marine Predator Algorithm and the Generalized Normal Distribution Optimization (MPGND). The proposed algorithm is applied to save power consumption which is an important problem in sustainable green 6G-IBN. MPGND is compared with several recently proposed algorithms, including Augmented Grey Wolf Optimizer (AGWO), Sine Tree-Seed Algorithm (STSA), Archimedes Optimization Algorithm (AOA), and Student Psychology-Based Optimization (SPBO). The experimental results with the statistical analysis demonstrate the merits and highly competitive performance of the proposed algorithm. |
| Databáze: | OpenAIRE |
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