Technological Innovations in Human Resource Management: Using Cloud-Edge Computing

Utilizing cloud-edge technological advances offers substantial opportunities for resource administration, effectiveness, and financial savings. These characteristics have promoted consumer and enterprise usage of the smart integrated cloud-edge model in the Internet of Things (IoT). In integrated cloud-edge computation, among the major difficulties is human resource management (HRM). Choosing the best capabilities depending on Quality of Service (QoS) considerations is a crucial and significant problem in IoT settings as software and hardware assets in the edge context are allotted for reacting to human demands. In the sense that system effectiveness rises and reaction duration falls with appropriate resource choosing, allotment, and surveillance, HRM may be viewed as an NP issue. This work uses the Whale Optimized Technique in cloud-edge computation to offer an optimal framework for the HRM issue. According to empirical outcomes, the suggested framework outperformed the additional meta-heuristic techniques in two distinct situations: shortest response duration, allocation expenses, and growing proportion of HRs allotted.