Improved Harris Hawks Optimizer with chaotic maps and opposition-based learning for task scheduling in cloud environment
Author:
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Software
Link
https://link.springer.com/content/pdf/10.1007/s10586-023-04021-x.pdf
Reference73 articles.
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2. Zhang, Z., Zhao, M., Wang, H., Cui, Z., Zhang, W.: An efficient interval many-objective evolutionary algorithm for cloud task scheduling problem under uncertainty. Inf. Sci. (Ny) 583, 56–72 (2022)
3. Ghafari, R., Kabutarkhani, F.H., Mansouri, N.: Task scheduling algorithms for energy optimization in cloud environment: a comprehensive review. Cluster Comput. (2022). https://doi.org/10.1007/s10586-021-03512-z
4. Zade, B.M.H., Mansouri, N., Javidi, M.M.: A two-stage scheduler based on New Caledonian Crow Learning Algorithm and reinforcement learning strategy for cloud environment. J. Netw. Comput. Appl. 202, 103385 (2022)
5. Manikandan, N., Gobalakrishnan, N., Pradeep, K.: Bee optimization based random double adaptive whale optimization model for task scheduling in cloud computing environment. Comput. Commun. 187, 35–44 (2022)
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