Improving application support in 6G networks with CAPOM: Confluence-aided process organization method

Jamil Alsayaydeh, Jamil Abedalrahim and Al Gburi, Ahmed Jamal Abdullah and Irianto and Herawan, Safarudin Gazali (2023) Improving application support in 6G networks with CAPOM: Confluence-aided process organization method. IEEE Access, 11. pp. 99426-99437. ISSN 2169-3536

[img] Text
0270213092023353.PDF

Download (917kB)

Abstract

Systems requiring terahertz transmission and high sampling capabilities can be supported by sixth-generation (6G) technology with minimal latency and excellent service throughput. Regardless of the distributions of data and services, High-Performance Computing (HPC) enhances speed and provides diversified applications and functionality. The Confluence-Aided Process Organization Method (CAPOM) is suggested in this article to take advantage of process allocations while using an HPC paradigm. The process allocations and completions are scheduled based on prior and current system conditions to minimize waiting time based on the 6G qualities. This implies that state requirements for process allocation, distribution, and completion are carried out with the assistance of federated learning. The initial state allocations are based on the user/application request; in other allocations, the application's request for completion time and capacity for processing are considered. Offloading and shared processing are therefore combined to maximize resource deliveries. The federated learning states are checked post-completion times to mitigate the waiting duration of dense service demands. Indicators such as distribution ratios, latency, wait time, and processing rate are considered for the effectiveness of the proofs. The suggested CAPOM achieves an 8.67% higher processing rate, 9.09% reduced latency, 8.76% less wait time, and a 6.73% higher distribution ratio for the various capacities.

Item Type: Article
Uncontrolled Keywords: 6G, Federated learning, HPC, Process allocation, Service distribution
Divisions: Faculty of Electronics and Computer Engineering
Depositing User: Norfaradilla Idayu Ab. Ghafar
Date Deposited: 19 Jun 2024 14:58
Last Modified: 19 Jun 2024 14:58
URI: http://eprints.utem.edu.my/id/eprint/27112
Statistic Details: View Download Statistic

Actions (login required)

View Item View Item