Metaheuristic Optimization-Based Resource Allocation Technique for Cybertwin-Driven 6G on IoE Environment

• Published in: IEEE transactions on industrial informatics Vol. 18; no. 7; pp. 4884 - 4892
• Main Authors: Jain, Deepak Kumar, Tyagi, Sumarga Kumar Sah, Neelakandan, Subramani, Prakash, Mohan, Natrayan, Lakshmaiya
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.07.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 6G mobile communication; Algorithms; Blockchain; Blockchains; Cloud computing; Costs; Cryptography; cybertwin; Heuristic methods; Internet; Internet of Everything (IoE); Logic gates; Machine learning; Metaheuristics; Network design; Optimization; Resource allocation; Resource management; sixth-generation (6G) networks
• ISSN: 1551-3203; 1941-0050
• DOI: 10.1109/TII.2021.3138915

Rapid advancements of sixth-generation (6G) network and Internet of Everything (IoE) supports numerous emerging services and application. Increasing mobile internet traffic and services, on the other hand, presented a number of challenges that could not be addressed with the current network design. The cybertwin is equipped with a variety of capabilities, including communication assistants, network data loggers, and digital asset owners, to address these difficulties. While spectrum resources are limited, effective resource management and sharing are essential in achieving these requirements. With this motivation, this article presents a new metaheuristic with blockchain based resource allocation technique (MWBA-RAT) for cybertwin driven 6G on IoE environment. The incorporation of the blockchain in 6G enables the network to monitor, manage, and share resources effectively. The proposed MWBA-RAT technique designs a new quasi-oppositional search and rescue optimization (QO-SRO) algorithm for the optimal resource allocation process and this shows the novelty of the work. The QO-SRO algorithm involves the integration of the quasi oppositional based learning concept with the traditional SRO algorithm to improve its convergence rate. A wide range of experiments are performed to highlight the enhanced outcomes of the MWBA-RAT technique.