An Optimization Method for Resource Allocation in Industrial Internet of Things
View Article

Keywords

Resource Allocation
Industrial Internet of Things (IIoT)
Optimization Method
IoT Resource Management
Industrial Automation

How to Cite

An Optimization Method for Resource Allocation in Industrial Internet of Things. (2024). Innovative: International Multidisciplinary Journal of Applied Technology (2995-486X), 2(6), 38-51. https://multijournals.org/index.php/innovative/article/view/1738

Abstract

An approach to improving the overall performance of edge-integrated edge IoT networks is presented in this paper: linked deep learning-based resource scheduling. An IoT network needs to use the greatest resources available from the edge layer in order to do a task efficiently and within the allotted time. Careful resource scheduling is necessary for the selection and distribution of the best resources. Deep learning algorithms were previously developed to reduce information transmission idleness and integrate edge networks with Internet of Things applications. To enhance the overall effectiveness and caliber of management of an IoT application, it is important to examine a few distinct metrics, such as reaction time, hold up time, and data transmission requirements. To achieve this higher performance, a convolutional brain network and gated recurrent unit are used in a connected system. The suggested resource scheduling model takes into account the characteristics and needs of the resources in order to select the best resources from the resource pool and distribute them to the IoT networks. An extensive analysis of the related approach and trial perceptions is included in this paper. 

View Article