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International Transactions on Evolutionary and Metaheuristic Algorithms
Vol. 6, No. 1, Apr. 2020 Task Scheduling in the Cloud Amended Through Genetic Algorithms | Miscellaneous
a University of Baghdad, Baghdad, Iraq
Corresponding Author Affiliation: University of Baghdad, Baghdad, Iraq Tel: 773 Phone: 2026138 E-mail: fadhilheba@gmail.com 2nd e-mail: heba@kecbu.uobaghdad.edu.iq
Highlights and Novelties
2- Furthermore, it builds on the concept of virtualization and the pay-as-you-go principle. The management of these resources has been the subject of considerable research. 3- A task scheduling algorithm is based on genetic algorithms (GA) to allocate and implement tasks specific to the application. 4- The use of a genetic algorithm for the distribution of tasks and schedules seeks more and more attention from the scholars. Manuscript Abstract
At present, cloud computing is used far and wide in companies and institutions. Yet, there are some challenges in using cloud computing. The central challenge is resource management, as cloud computing provides IT resources (for example, CPU, memory, network, storage, etc.). Furthermore, it builds on the concept of virtualization and the pay-as-you-go principle. The management of these resources has been the subject of considerable research. A task scheduling algorithm is based on genetic algorithms (GA) to allocate and implement tasks specific to the application. The use of a genetic algorithm for the distribution of tasks and schedules seeks more and more attention from scholars. To solve the difficulty of resource scheduling in large-scale, nonlinear cluster systems, and has achieved ideal effects GA has been widely applied. By what means to make reasonable use of computing resources that creates total and average time complete a shorter and smaller task costing an important issue. Research spectacles that artificial methods can achieve, further optimal load balancing than traditional approaches. Keywords
Task Scheduling Cloud Computing Genetic Algorithm Copyright
© Copyright was transferred to International Computer Science and Engineering Society (ICSES) by all the Authors. Cite this manuscript as
Heba Fadhil, "Task Scheduling in the Cloud Amended Through Genetic Algorithms," International Transactions on Evolutionary and Metaheuristic Algorithms (ITEMA), vol. 6, no. 1, pp. 1-2, Apr. 2020. For External Scientific Databeses
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