Task Scheduling Optimization in cloud computing by Cuckoo Search Algorithm | ||||
| Sohag Journal of Sciences | ||||
| Article 3, Volume 7, Issue 3, September 2022, Page 29-37 PDF (990.75 K) | ||||
| Document Type: Regular Articles | ||||
| DOI: 10.21608/sjsci.2022.249079 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
M. Kh. Elnahary  ; Ahmed Y. Hamed; H. El-Sayed1
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| Faculty of Computers and Artificial Intelligence, Department of Computer Science, Sohag University, Sohag, 82524, Egypt. | ||||
| Abstract | ||||
| : In cloud computing systems, task scheduling is crucial. Task scheduling cannot be done based on a single criterion but rather on rules and regulations which can be referred to as an agreement between cloud customers and providers. This agreement is nothing more than the user's desire for the providers to offer the kind of service that they expect. Providing high-quality services to consumers under the deal is a critical duty for providers, who must also manage many responsibilities. The task scheduling problem may be considered the search for an ideal assignment or mapping of a collection of subtasks of distinct tasks across the available set of resources to meet the intended goals for tasks. This paper proposes an efficient scheduling task algorithm based on the cuckoo search algorithm in cloud computing systems. By applying it to three cases, we evaluate the performance of our algorithm. The findings suggest that the proposed strategy successfully achieved the best solution in makespan, speedup, efficiency, and throughput. | ||||
| Keywords | ||||
| Heterogeneous resources; Cuckoo search algorithm; Task scheduling; Cloud Computing | ||||
| References | ||||
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