Iot Enabled Fog Based Computing with Deep Learning Models to Increase The Allocation of Resource

Abstract

The existing resource allocation mechanism in fog computing environment fails to allocate optimal resources in the network environment. Since, these mechanism fails to allocate increasing user data from the internet of things devices. It is hence necessary to model a system that enables processing of task based on the resource available. The paper explains an internet of things based fog computing for allocation of resources using deep learning computations. The deep learning model is trained, tested and validated in an efficient manner to allocate the task in fog environment when user IoT data is sent for storage and processing. The experimental validation shows increased network throughput and reduced losses while a task is allocated in the user computing environment.