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 Pillai, Sanjaikanth E Vadakkethil Somanathan; Paramasivam, Santhosh; Polimetla, Kiran; Dhanasekaran, Selvaraj; Agrawal, Krishna Kant; Yadav, Satya Prakash; Logeshwaran, Jaganathan; Gatto, Gianluca Title A name given to the resource Optimizing resource management using hybrid metaheuristic algorithm for fog layer design in edge computing 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 Systems and Soft Computing;Volume;7;Issue;;Article No.;200323; Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1016/j.sasc.2025.200323" target="_blank" rel="noreferrer noopener">https://doi.org/10.1016/j.sasc.2025.200323</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105008508277?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105008508277?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 Pillai S.E.V.S., School of Electrical Engineering and Computer Science, University Of North Dakota, Grand Forks, United States; Paramasivam S., Department of Electrical and Electronic Engineering, University of Cagliari, Cagliari, 09123, Italy; Polimetla K., Department of Information Technology, Adobe Inc., Austin, TX, United States; Dhanasekaran S., Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, Tamil Nadu, Coimbatore, 641202, India; Agrawal K.K., School of Computer Science and Engineering, Galgotias University, Greater Noida, India; Yadav S.P., Department of Computer Science and Engineering, Madan Mohan Malaviya University of Technology, Uttar Pradesh, Gorakhpur, India; Logeshwaran J., Department of Computer Science, Christ University, Karnataka, Bengaluru, 560029, India; Gatto G., Department of Electrical and Electronic Engineering, University of Cagliari, Cagliari, 09123, Italy Description An account of the resource The growing complexity of management in fog computing environments necessitates more efficient algorithms capable of optimizing resource allocation, minimizing latency, and maximizing throughput and energy efficiency. Existing techniques, consisting of the Multi-Objective Crow Search Algorithm (MOCSA) and Fuzzy Meta-Heuristics Optimization (FMHO), regularly suffer from suboptimal performance due to constrained exploration abilities and slower convergence fees. To overcome with these demanding situations, this paper proposes a singular Hybrid Metaheuristic Algorithm (HMA) that mixes the strengths of more than one metaheuristic techniques, along with genetic algorithms, simulated annealing, and gray wolf optimization (GA-SA-GWO). The HMA is specifically designed to enhance useful resource control in fog computing by optimizing useful resource allocation, lowering latency, and enhancing usual gadget performance. Experimental results exhibit that the proposed HMA significantly outperforms existing solutions, with 26.98 % improved latency, 90.64 % resource utilization, 96.05 % throughput, 37.06 % reduced energy utilization, and 93.85 % energy utilization. These outcomes spotlight the HMA's potential to successfully manage sources in dynamic and unpredictable fog computing environments, providing a greater scalable and robust solution for actual-time applications. 2025 Subject The topic of the resource Cloud; Edge computing; Environmental monitoring; High performance; Low power sensor network; Low-latency; Metaheuristic; Optimal resource allocation; Optimization; Reduced power consumption Publisher An entity responsible for making the resource available Academic Press Relation A related resource ISSN: 27729419; 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; Gold Open Access; Green Open Access Format The file format, physical medium, or dimensions of the resource online