Service Priority-Driven Resource Management in Multiuser, Multiservice, and Multidevice 6G Wireless Networks

Effective resource management is critical in the dynamic environment of multiuser, multiservice, and multidevice 6G networks. This necessitates careful consideration of service priorities in the context of conflicting demands and limited resources. To address this challenge, this research introduces intelligent priority-driven resource allocation using the penalty function (IPRAPF) approach, which transforms resource allocation into an integer programming problem, balancing user expectations with available resources. IPRAPF significantly improves service accommodation per priority level over conventional optimization methods, such as simple relax and optimum branch and bound in different 6G networks. Notably, IPRAPF demonstrates robust performance with 20 users, five services, and four computing devices, supporting service allocation improvements ranging from 15% to 18% per priority level. In contrast, the simple relax method yields lower allocations, with improvements ranging from 11% to 13%, highlighting the superior effectiveness of the proposed IPRAPF. Moreover, an analysis of services per priority level highlights the capability of IPRAPF to optimize resource utilization and ensure seamless service delivery, especially with increased service diversity. This emphasizes the adaptability and importance of IPRAPF in navigating the constantly changing environment of 6G wireless networks.