{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,17]],"date-time":"2024-09-17T10:57:03Z","timestamp":1726570623121},"reference-count":19,"publisher":"IGI Global","issue":"1","license":[{"start":{"date-parts":[[2023,6,13]],"date-time":"2023-06-13T00:00:00Z","timestamp":1686614400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/deed.en_US"},{"start":{"date-parts":[[2023,6,13]],"date-time":"2023-06-13T00:00:00Z","timestamp":1686614400000},"content-version":"am","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/deed.en_US"},{"start":{"date-parts":[[2023,6,13]],"date-time":"2023-06-13T00:00:00Z","timestamp":1686614400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/deed.en_US"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,6,13]]},"abstract":"

Task scheduling in fog computing is one of the areas where researchers are having challenges as the demand grows for the use of internet of things (IoT) to access cloud computing resources. Many resource scheduling and optimization algorithms were used by many researchers in fog computing; some used single techniques while others used combined schemes to achieve dynamic scheduling in fog computing, many optimization techniques were assessed based on deterministic and meta-heuristic to find out solution to task scheduling problem in fog computing but could not achieve excellent results as required. This article proposes hybrid meta-heuristic optimization algorithm (HMOA) for energy efficient task scheduling in fog computing, the study combined modified particle swarm optimization (MPSO) meta-heuristic and deterministic spanning tree (SPT) to achieve task scheduling with the intention of eliminating the drawbacks of the two algorithms when used separately, the MPSO was used to schedule user task requests among fog devices, while hybrid MPSO-SPT was used to perform resource allocation and resource management in the fog computing environment. The study implemented the proposed algorithm using iFogSim; the performance of the algorithm was evaluated, assessed, and compared with other state-of-the-art task scheduling and resource management algorithms, the proposed method performs better in terms of energy consumption, resource utilization and response time, and the study proposed future research on evaluating the execution time using the hybrid algorithm.<\/p>","DOI":"10.4018\/ijcac.324758","type":"journal-article","created":{"date-parts":[[2023,6,13]],"date-time":"2023-06-13T19:40:35Z","timestamp":1686685235000},"page":"1-16","source":"Crossref","is-referenced-by-count":2,"title":["Performance Evaluation of Hybrid Meta-Heuristics-Based Task Scheduling Algorithm for Energy Efficiency in Fog Computing"],"prefix":"10.4018","volume":"13","author":[{"ORCID":"http:\/\/orcid.org\/0000-0003-1044-2550","authenticated-orcid":true,"given":"Ali Garba","family":"Jakwa","sequence":"first","affiliation":[{"name":"Abubakar Tafawa Balewa University, Nigeria"}]},{"given":"Abdulsalam Yau","family":"Gital","sequence":"additional","affiliation":[{"name":"Abubakar Tafawa Balewa University, Nigeria"}]},{"given":"Souley","family":"Boukari","sequence":"additional","affiliation":[{"name":"Abubakar Tafawa Balewa University, Nigeria"}]},{"given":"Fatima Umar","family":"Zambuk","sequence":"additional","affiliation":[{"name":"Abubakar Tafawa Balewa University, Nigeria"}]}],"member":"2432","reference":[{"key":"IJCAC.324758-0","doi-asserted-by":"publisher","DOI":"10.1109\/ICOEI.2019.8862777"},{"key":"IJCAC.324758-1","doi-asserted-by":"crossref","unstructured":"Ahmed, A. M., Rashid, T. A., & Soran, S. A. (2020). Cat Swarm Optimization Algorithm: A Survey and Performance Evaluation. Hindawi Computational Intelligence and Neuroscience, 20.","DOI":"10.1155\/2020\/4854895"},{"key":"IJCAC.324758-2","first-page":"17","article-title":"A Multi-Tier Architecture for the Management of Supply Chain of Cloud Resources in a Vitualized Cloud Environment: A Novel SCM Techniques for Cloud Resources Using Ant Colony Optimization and Spanning Tree.","author":"M.Aliyu","year":"2021","journal-title":"International Journal of Information Systems and Supply Chain Management"},{"key":"IJCAC.324758-3","doi-asserted-by":"publisher","DOI":"10.4018\/IJCAC.2020040101"},{"key":"IJCAC.324758-4","doi-asserted-by":"crossref","unstructured":"Amancio da Silva, D. M., Asamooning, G., Orrillo, H., Sofia, R. C., & Mendes, P. M. (2020). An Analysis of Fog Computing Data Placement Algorithms. arXiv, 1-8.","DOI":"10.1145\/3360774.3368201"},{"key":"IJCAC.324758-5","doi-asserted-by":"publisher","DOI":"10.31979\/etd.shqa-fdp6"},{"key":"IJCAC.324758-6","doi-asserted-by":"crossref","unstructured":"Hong, K., Lillethun, D., Ramachandran, U., Ottenw\u00e4lder, B., & Koldehofe, B. (2013). Mobile Fog: A Programming Model for Large\u2013Scale Applications on the Internet of Things. ACM, 15-20.","DOI":"10.1145\/2491266.2491270"},{"key":"IJCAC.324758-7","unstructured":"Kumari, K. A., Sastry, J. K., & Rao, K. R. (2019). Energy Efficient Load Balanced Optimal Resource Allocation Scheme for Cloud Environment. International Journal of Recent Technology and Engineering (IJRTE), 146-153."},{"key":"IJCAC.324758-8","doi-asserted-by":"crossref","unstructured":"Li, G., Liu, Y., Wu, J., & Li, D. (2019). Methods of Resource Scheduling Based on Optimized Fuzzy Clustering in Fog Computing. 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