Task Scheduling with Multi-strategy Improved Sparrow Search Algorithm in Cloud Datacenters
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-8082-6_13
Reference17 articles.
1. Keshanchi, B., Souri, A., Navimipour, N.J.: 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)
2. Gupta, A., Garg, R.: Load balancing based task scheduling with ACO in cloud computing. In: 2017 International Conference on Computer and Applications (ICCA), pp. 174–179. IEEE (2017)
3. Prem Jacob, T., Pradeep, K.: A multi-objective optimal task scheduling in cloud environment using cuckoo particle swarm optimization. Wirel. Pers. Commun. 109, 315–331 (2019)
4. Xue, J., Shen, B.: A novel swarm intelligence optimization approach: sparrow search algorithm. Syst. Sci. Control Eng. 8(1), 22–34 (2020)
5. Abdulhammed, O.Y.: Load balancing of IoT tasks in the cloud computing by using sparrow search algorithm. J. Supercomput. 78(3), 3266–3287 (2022)
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