دانلود رایگان مقاله انگلیسی زمانبندی کار انرژی موثر در محیط ابر - الزویر 2017

Abstract

Cloud computing is a style of computing in which dynamically scalable and other virtualized resources are provided as a service over the Internet. The energy consumption and makespan associated with the resources allocated should be taken into account. This paper focuses on task scheduling using Clonal Selection Algorithm (TSCSA) to optimize energy and processing time. The result obtained by TSCSA was simulated by an open source cloud platform (CloudSim). Finally, the results were compared to existing scheduling algorithms and found that the proposed algorithm (TSCSA) provide an optimal balance results for multiple objectives.

7. Conclusion

This paper presented multi-objective CSA based optimization algorithm which can solve the task scheduling problem under the computing environment, where of the number of data center and user job changes dynamically. But, in changing environment, cloud computing resources needs to be operated in optimally manner. Therefore, multi-objective CSA based algorithm is suitable for cloud computing environment because the algorithm is able to effectively utilize the system resources to reduce energy and makespan. The experimental results illustrated that the proposed methods (TSCSA) out-performed the maximum applications scheduling algorithm and random scheduling For further studies, the optimization model should add more essential objectives ( bandwidth, load balancing, cost etc) and should focus more robust algorithm.