Research on Improved Hybrid Particle Swarm Optimization Algorithm for Cloud Computing Task Scheduling
- 10.2991/meici-18.2018.234How to use a DOI?
- Cloud computing; Task scheduling; Ant colony algorithm; Hybrid PSO algorithm
In the cloud computing environment, one of the hot spot of researches in cloud computing is how to accomplish the service request in numerous running tasks. This paper puts forward an improved hybrid particle swarm optimization, firstly using particle swarm algorithm as the main level algorithm, the initial solution rapidly, followed by the max min ant colony algorithm, as the algorithm to find the optimal solution based on the initial solution. Finally, the availability and advantage of the proposed algorithm can be tested through the simulation experiment.
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Xiaoguang Yang AU - Qian Wang AU - Yimin Zhang PY - 2018/12 DA - 2018/12 TI - Research on Improved Hybrid Particle Swarm Optimization Algorithm for Cloud Computing Task Scheduling BT - Proceedings of the 2018 8th International Conference on Management, Education and Information (MEICI 2018) PB - Atlantis Press SP - 1162 EP - 1167 SN - 1951-6851 UR - https://doi.org/10.2991/meici-18.2018.234 DO - 10.2991/meici-18.2018.234 ID - Yang2018/12 ER -