An Efficient Approach to Genetic Algorithm for Task Scheduling in Cloud Computing Environment
Автор: Shaminder Kaur, Amandeep Verma
Журнал: International Journal of Information Technology and Computer Science(IJITCS) @ijitcs
Статья в выпуске: 10 Vol. 4, 2012 года.
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Cloud computing is recently a booming area and has been emerging as a commercial reality in the information technology domain. Cloud computing represents supplement, consumption and delivery model for IT services that are based on internet on pay as per usage basis. The scheduling of the cloud services to the consumers by service providers influences the cost benefit of this computing paradigm. In such a scenario, Tasks should be scheduled efficiently such that the execution cost and time can be reduced. In this paper, we proposed a meta-heuristic based scheduling, which minimizes execution time and execution cost as well. An improved genetic algorithm is developed by merging two existing scheduling algorithms for scheduling tasks taking into consideration their computational complexity and computing capacity of processing elements. Experimental results show that, under the heavy loads, the proposed algorithm exhibits a good performance.
Cloudlets, Cloud Computing, Genetic Algorithm, Makespan, Task-Scheduling
Короткий адрес: https://sciup.org/15011773
IDR: 15011773
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