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Title |
An Efficient Scheduling Technique for Cloud Computing Systems Based on Particle Swarm Optimization and Genetic Algorithm |
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Author |
Ebrahim Behrouzian Nejad |
| Citation |
Vol. 26 No. 8 pp. 115-123 |
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Abstract |
Cloud computing is a new processing method for delivering information technology services based on computer networks. One of the main challenges in cloud based system is task scheduling algorithm. Performance of cloud computing systems largely depend upon underlying scheduling algorithms which can affect other performance parameters such as makespan, load balancing, cost and energy consumption. So, in this paper a scheduling algorithm is presented called HGPA which is based on Particle Swarm Optimization (PSO) and Genetic Algorithm (GA). This algorithm attempts to improve load balancing and make span parameters in cloud computing systems. Evaluation and simulation results show that this proposed scheduling algorithm is able to reduce makespan and improve load balancing in cloud computing systems in comparison with other evaluated techniques. |
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Keywords |
Cloud computing systems, Scheduling Algorithm, Particle Swarm Optimization and Genetic Algorithm (GA). |
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