A Survey on Nature-Inspired Optimization Methods for Effective Task Scheduling in Cloud Computing Environment
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-68639-9_29
Reference25 articles.
1. Kaiyue, W.P., et al.: Distributed online scheduling and routing of multicast-oriented tasks for fitness function-driven cloud computing. IEEE Commun. Lett. 20(4), 684–687 (2016)
2. Zhu, X.C., et al.: ANGEL: agent-based scheduling for realtime tasks in virtualized clouds. IEEE Trans. Comput. 64(12), 3389–3403 (2015)
3. Chen, C., et al.: An energy-saving task scheduling strategy based on vacation queuing theory in cloud computing. Tsinghua Sci. Technol. 20(1), 28–39 (2015)
4. Keshanchi, B.A., et al.: An improved genetic algorithm for task scheduling in the cloud environments using the priority queues: formal verification, simulation, and statistical testing. J. Syst. Softw. 124, 1–21 (2017)
5. Lovász, G., Niedermeier, F., De Meer, H.: Performance tradeoffs of energy-aware virtual machine consolidation. Clust. Comput. 16, 481–496 (2013)
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