An Improved Dingo Optimization for Resource Aware Scheduling in Cloud Fog Computing Environment
Task scheduling in Cloud-Fog computing environments is a critical aspect of optimizing resource allocation and enhancing performance. This study presents an improved version of the Dingo Optimization Algorithm (IDOA) specifically designed for task scheduling in Cloud-Fog computing. The enhanced IDOA...
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| Format: | Article |
| Language: | English |
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OICC Press
2024-02-01
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| Series: | Majlesi Journal of Electrical Engineering |
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| Online Access: | https://oiccpress.com/mjee/article/view/5013 |
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| author | Santhosh Kumar Medishetti Ganesh Reddy Karri |
| author_facet | Santhosh Kumar Medishetti Ganesh Reddy Karri |
| author_sort | Santhosh Kumar Medishetti |
| collection | DOAJ |
| description | Task scheduling in Cloud-Fog computing environments is a critical aspect of optimizing resource allocation and enhancing performance. This study presents an improved version of the Dingo Optimization Algorithm (IDOA) specifically designed for task scheduling in Cloud-Fog computing. The enhanced IDOA incorporates novel modifications to address the limitations of the original algorithm and improve the efficiency and effectiveness of task allocation. The algorithm incorporates modifications to the fitness evaluation function, a dynamic update mechanism, and a neighborhood search technique to enhance task allocation efficiency. Extensive simulations and comparisons with existing algorithms are conducted to evaluate the performance of the IDOA. The results demonstrate its superiority in terms of task makespan time, VM failure rate, and degree of imbalance. Overall, the improved Dingo Optimization Algorithm offers a promising solution for efficient task scheduling in Cloud-Fog computing environments. The algorithm effectively balances exploration and exploitation, facilitating efficient task scheduling in Cloud-Fog computing environments and optimizing cloud-based applications and services. |
| format | Article |
| id | doaj-art-4d9952ad17384ddbb8e680381d01d2bf |
| institution | OA Journals |
| issn | 2345-377X 2345-3796 |
| language | English |
| publishDate | 2024-02-01 |
| publisher | OICC Press |
| record_format | Article |
| series | Majlesi Journal of Electrical Engineering |
| spelling | doaj-art-4d9952ad17384ddbb8e680381d01d2bf2025-08-20T02:15:54ZengOICC PressMajlesi Journal of Electrical Engineering2345-377X2345-37962024-02-0117310.30486/mjee.2023.1989335.1165An Improved Dingo Optimization for Resource Aware Scheduling in Cloud Fog Computing EnvironmentSanthosh Kumar Medishetti0Ganesh Reddy Karri1VIT-AP University, Amaravathi, A.P., India, 522 237.AP, IndiaTask scheduling in Cloud-Fog computing environments is a critical aspect of optimizing resource allocation and enhancing performance. This study presents an improved version of the Dingo Optimization Algorithm (IDOA) specifically designed for task scheduling in Cloud-Fog computing. The enhanced IDOA incorporates novel modifications to address the limitations of the original algorithm and improve the efficiency and effectiveness of task allocation. The algorithm incorporates modifications to the fitness evaluation function, a dynamic update mechanism, and a neighborhood search technique to enhance task allocation efficiency. Extensive simulations and comparisons with existing algorithms are conducted to evaluate the performance of the IDOA. The results demonstrate its superiority in terms of task makespan time, VM failure rate, and degree of imbalance. Overall, the improved Dingo Optimization Algorithm offers a promising solution for efficient task scheduling in Cloud-Fog computing environments. The algorithm effectively balances exploration and exploitation, facilitating efficient task scheduling in Cloud-Fog computing environments and optimizing cloud-based applications and services.https://oiccpress.com/mjee/article/view/5013Cloud-Fog computingdegree of imbalanceDingo Optimization Algorithm.makespanTask scheduling |
| spellingShingle | Santhosh Kumar Medishetti Ganesh Reddy Karri An Improved Dingo Optimization for Resource Aware Scheduling in Cloud Fog Computing Environment Majlesi Journal of Electrical Engineering Cloud-Fog computing degree of imbalance Dingo Optimization Algorithm. makespan Task scheduling |
| title | An Improved Dingo Optimization for Resource Aware Scheduling in Cloud Fog Computing Environment |
| title_full | An Improved Dingo Optimization for Resource Aware Scheduling in Cloud Fog Computing Environment |
| title_fullStr | An Improved Dingo Optimization for Resource Aware Scheduling in Cloud Fog Computing Environment |
| title_full_unstemmed | An Improved Dingo Optimization for Resource Aware Scheduling in Cloud Fog Computing Environment |
| title_short | An Improved Dingo Optimization for Resource Aware Scheduling in Cloud Fog Computing Environment |
| title_sort | improved dingo optimization for resource aware scheduling in cloud fog computing environment |
| topic | Cloud-Fog computing degree of imbalance Dingo Optimization Algorithm. makespan Task scheduling |
| url | https://oiccpress.com/mjee/article/view/5013 |
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