Intelligent Service Provisioning in Fog Computing

Abstract

Fog computing is a distributed paradigm that extends cloud computing closer to the edge of the network, and even beyond that. By employing local resources, it enables quicker and more effective data processing and analysis. The optimization and automation of resource allocation, data processing, and job scheduling in the fog environment are made possible by the application of machine learning to Fog Computing Orchestration. It is also important, when working with the network computing models, to consider the XaaS paradigm, as it promotes the flexibility and scalability of fog services, bringing the concept of “service” into the foreground. Therefore, the need for a fog orchestrator enabling such characteristics arises, leveraging AI and the “service-centric” approach to enhance users’ service fruition. The design and development of such an orchestrator will be the objective of the early-stage PhD project presented in this paper.