Details

Autor(en) / Beteiligte

• Xie, Xiaolan
• Xu, Ke
• Wang, Xiangwei

Titel

Cloud computing resource scheduling based on improved differential evolution ant colony algorithm

Ist Teil von

• Proceedings of the 2019 International Conference on Data Mining and Machine Learning, 2019, p.171-177

Ort / Verlag

New York, NY, USA: ACM

Erscheinungsjahr

2019

Quelle

ACM Digital Library

Beschreibungen/Notizen

• Due to the uneven distribution of cloud computing resources and the long processing time of resource scheduling, a cloud computing resource scheduling strategy based on improved differential evolution ant colony algorithm is proposed. By changing the size of the mutation operator F in the differential evolution algorithm, the differential evolution algorithm is controlled not to fall into the local search state and the convergence premature phenomenon. Then the improved differential evolution algorithm is combined with the ant colony algorithm to preserve the ant colony. The algorithm local search optimal characteristics, and has the characteristics of improved global evolution of differential evolution algorithm. The combination of the two can well optimize the problem of unbalanced load and long processing time in the cloud computing resource scheduling process.