Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Vetriveeran, Divya; Sri, Leena R. Title A name given to the resource Resource Provisioning in Fog Computing - A Survey Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived ACM Computing Surveys;Volume;57;Issue;12;Article No.;305; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1145/3744662" target="_blank" rel="noreferrer noopener">https://doi.org/10.1145/3744662</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105011388077?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105011388077?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Vetriveeran D., AIML &amp; Data Science, Christ University, Bangalore, India; Sri L.R., Computer Science and Engineering, Thiagarajar College of Engineering, Madurai, India Description An account of the resource The internet world has created an era where any device can interconnect with each other. Gathering intelligence from streaming data is challenging and can create wonders and valuable innovations for humanity. The shortcomings of connectivity due to the remote location of the cloud induce latency and performance issues in real-time. Thus, a traditional cloud may not be suitable for all applications. A secure, low latent bandwidth infrastructure under research led to Fog Computing. The fog nodes have limited resources, and effective utilization can boost the applications performance. Ensuring effective routing of the tasks and load balancing among the nodes is essential and tedious in any network. Resource management becomes challenging due to heterogeneity, dynamic workload, unpredictability of the computing environment, and so on. In such cases, using Artificial Intelligence (AI) can be promising, provided the complexity and the computing are handled. Proactive load handling based on the changes in network traffic has a huge scope for research. This article gives a detailed survey of the various fog network architectures and the intelligent methodologies in resource allocation in a fog network using machine learning algorithms. Furthermore, the article shows the directions of research in intelligent resource allocation and handling. 2025 Copyright held by the owner/author(s) Subject The topic of the resource artificial intelligence algorithms; Fog computing; mi-croservices; research challenges; resource provisioning; software defined networking Publisher An entity responsible for making the resource available Association for Computing Machinery Relation A related resource ISSN: 3600300; CODEN: ACSUE Language A language of the resource English Type The nature or genre of the resource Article Rights Information about rights held in and over the resource All Open Access; Hybrid Gold Open Access Format The file format, physical medium, or dimensions of the resource online