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Open AccessArticle
LSMOF-AD: Three-Stage Optimization Approach with Adaptive Differential for Large-Scale Container Scheduling
by
Mingshan Chen
Mingshan Chen 1,2,
Weichao Ding
Weichao Ding 1,2,*,
Mengyang Zhu
Mengyang Zhu 1,
Wen Shi
Wen Shi 1 and
Guoqing Jiang
Guoqing Jiang 2,*
1
School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China
2
Key Lab of Information Network Security, Ministry of Public Security, Shanghai 200031, China
*
Authors to whom correspondence should be addressed.
Processes 2024, 12(7), 1531; https://doi.org/10.3390/pr12071531 (registering DOI)
Submission received: 27 June 2024
/
Revised: 17 July 2024
/
Accepted: 18 July 2024
/
Published: 20 July 2024
Abstract
Container technology has gained a widespread application in cloud computing environments due to its low resource overhead and high flexibility. However, as the number of containers grows, it becomes increasingly challenging to achieve the rapid and coordinated optimization of multiple objectives for container scheduling, while maintaining system stability and security. This paper aims to overcome these challenges and provides the optimal allocation for a large number of containers. First, a large-scale multi-objective container scheduling optimization model is constructed, which involves the task completion time, resource cost, and load balancing. Second, a novel optimization algorithm called LSMOF-AD (large-scale multi-objective optimization framework with muti-stage and adaptive differential strategies) is proposed to effectively handle large-scale container scheduling problems. The experimental results show that the proposed algorithm has a better performance in multiple benchmark problems compared to other advanced algorithms and can effectively reduce the task processing delay, while achieving a high resource utilization and load balancing compared to other scheduling strategies.
Share and Cite
MDPI and ACS Style
Chen, M.; Ding, W.; Zhu, M.; Shi, W.; Jiang, G.
LSMOF-AD: Three-Stage Optimization Approach with Adaptive Differential for Large-Scale Container Scheduling. Processes 2024, 12, 1531.
https://doi.org/10.3390/pr12071531
AMA Style
Chen M, Ding W, Zhu M, Shi W, Jiang G.
LSMOF-AD: Three-Stage Optimization Approach with Adaptive Differential for Large-Scale Container Scheduling. Processes. 2024; 12(7):1531.
https://doi.org/10.3390/pr12071531
Chicago/Turabian Style
Chen, Mingshan, Weichao Ding, Mengyang Zhu, Wen Shi, and Guoqing Jiang.
2024. "LSMOF-AD: Three-Stage Optimization Approach with Adaptive Differential for Large-Scale Container Scheduling" Processes 12, no. 7: 1531.
https://doi.org/10.3390/pr12071531
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