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Research Article | Open Access |

Genetic-Based Task Scheduling Algorithm in Cloud Computing Environment

Author 1: Safwat A. Hamad Author 2: Fatma A. Omara
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 7, No. 4 · Published 2016 · Cited by 96

DOI: https://doi.org/10.14569/IJACSA.2016.070471

Abstract

Nowadays, Cloud computing is widely used in companies and enterprises. However, there are some challenges in using Cloud computing. The main challenge is resource management, where Cloud computing provides IT resources (e.g., CPU, Memory, Network, Storage, etc.) based on virtualization concept and pay-as-you-go principle. The management of these resources has been a topic of much research. In this paper, a task scheduling algorithm based on Genetic Algorithm (GA) has been introduced for allocating and executing an application’s tasks. The aim of this proposed algorithm is to minimize the completion time and cost of tasks, and maximize resource utilization. The performance of this proposed algorithm has been evaluated using CloudSim toolkit.

Keywords

How to Cite this Article

Hamad, S. A., & Omara, F. A. (2016). Genetic-Based Task Scheduling Algorithm in Cloud Computing Environment. International Journal of Advanced Computer Science and Applications, 7(4). https://doi.org/10.14569/IJACSA.2016.070471

Hamad, Safwat A., and Fatma A. Omara. "Genetic-Based Task Scheduling Algorithm in Cloud Computing Environment." International Journal of Advanced Computer Science and Applications, vol. 7, no. 4, 2016, https://doi.org/10.14569/IJACSA.2016.070471.

@article{Hamad2016,
  title     = {Genetic-Based Task Scheduling Algorithm in Cloud Computing Environment},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {4},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Safwat A. Hamad and Fatma A. Omara},
  doi       = {10.14569/IJACSA.2016.070471},
  url       = {https://doi.org/10.14569/IJACSA.2016.070471}
}

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