A discrete dwarf mongoose optimization algorithm to solve task assignment problems on smart farms
محفوظ في:
| الحاوية / القاعدة: | Cluster Computing vol. 27, no. 5 (Aug 2024), p. 6185 |
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| المؤلف الرئيسي: | |
| مؤلفون آخرون: | , , |
| منشور في: |
Springer Nature B.V.
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| الموضوعات: | |
| الوصول للمادة أونلاين: | Citation/Abstract Full Text Full Text - PDF |
| الوسوم: |
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| مستخلص: | In this study, we propose a novel cloud-edge collaborative task assignment model for smart farms that consists of a cloud server, m edge servers, and n sensors. The edge servers rely solely on solar-generated energy, which is limited, whereas the cloud server has access to a limitless amount of energy supplied by the smart grid. Each entire task from a sensor is processed by either an edge server or the cloud server. We consider the task to be unsplittable. Building on the algorithm for the multimachine job scheduling problem, we develop a corresponding approximation algorithm. In addition, we propose a new discrete heuristic based on the dwarf mongoose optimization algorithmm, named the discrete dwarf mongoose optimization algorithm, and we utilize the proposed approximation algorithm to improve the convergence speed of this heuristic while yielding better solutions. In this study, we consider task sets with heavy tasks independently, where a heavy task is a task that requires many computing resources to process. If such tasks are assigned as ordinary tasks, the assignment results may be poor. Therefore, we propose a new method to solve this kind of problem. |
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| تدمد: | 1386-7857 1573-7543 |
| DOI: | 10.1007/s10586-024-04271-3 |
| المصدر: | Advanced Technologies & Aerospace Database |