Abstract
According to the dynamic, distribution and complexity of cloud computing, resource scheduling effectively with users’ QoS demand and achieving maximum benefit is the unprecedented challenge. To solve the above problem, we propose to use genetic algorithm: design for the crossover operator and build a cloud resource optimization scheduling model that promised to address user needs while optimizing resource allocation. With the experiments, this paper verifies the superiority of models made in this paper. The results show that the use of genetic algorithm to optimize cloud resource scheduling has the rationality and feasibility. Meanwhile, using the genetic algorithm is useful for effectively scheduling of cloud resource meeting the users’ QoS.
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Wang, Y., Wang, J., Wang, C., Song, X. (2013). Resource Scheduling of Cloud with QoS Constraints. In: Guo, C., Hou, ZG., Zeng, Z. (eds) Advances in Neural Networks – ISNN 2013. ISNN 2013. Lecture Notes in Computer Science, vol 7952. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39068-5_43
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DOI: https://doi.org/10.1007/978-3-642-39068-5_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39067-8
Online ISBN: 978-3-642-39068-5
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