Distributed AI in Zero-touch Provisioning for Edge Networks: Challenges and Research Directions
This addresses scalability and sustainability issues for network administrators and service providers in edge networks, but it is incremental as it builds on existing concepts without presenting new experimental results.
The paper tackles the challenge of managing network devices in edge networks by combining Distributed Artificial Intelligence (DAI) with Zero-touch Provisioning (ZTP) to enable seamless and intelligent resource provisioning with minimal human intervention.
Zero-touch network is anticipated to inaugurate the generation of intelligent and highly flexible resource provisioning strategies where multiple service providers collaboratively offer computation and storage resources. This transformation presents substantial challenges to network administration and service providers regarding sustainability and scalability. This article combines Distributed Artificial Intelligence (DAI) with Zero-touch Provisioning (ZTP) for edge networks. This combination helps to manage network devices seamlessly and intelligently by minimizing human intervention. In addition, several advantages are also highlighted that come with incorporating Distributed AI into ZTP in the context of edge networks. Further, we draw potential research directions to foster novel studies in this field and overcome the current limitations.