Proceedings Article10.1109/IUCC/DSCI/SMARTCNS.2019.00133
Resource Scheduling in Cloud Computing Based on Firefly Algorithm
Chang’an Ren,Yinzhen Huang,Luo Qingyun,Xiaocui Li +3 more
- 01 Oct 2019
- Vol. 2019, pp 638-643
2
TL;DR: Experimental results show that the proposed approach can obtain good scheduling scheme to ensure load balance of virtual machine resource, which can meet the user's preferences.
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Abstract: In order to improve the utilization ratio of virtual machine resource, and then realize reasonable scheduling of it. In this paper, we propose a novel cloud computing resource scheduling optimization approach based on firefly algorithm. Firstly, mathematical model is built according to virtual machine resource scheduling problem. Then, considering the optimal time span and load function, we propose improved firefly algorithm, named selective elimination and decision domain strategy of firefly algorithm (SDFA) and use the SDFA to search the optimal scheme. Finally, we use the CloudSim platform to evaluate the effectiveness of our proposed approach. Experimental results show that our proposed approach can obtain good scheduling scheme to ensure load balance of virtual machine resource, which can meet the user's preferences.
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Citations
ECFA: An Efficient Convergent Firefly Algorithm for Solving Task Scheduling Problems in Cloud-Edge Computing
TL;DR: An efficient convergent firefly algorithm for scheduling security-critical tasks onto edge servers and the cloud datacenter is proposed, using a probability-based mapping operator to convert an individual firefly into a scheduling solution, in order to associate the firefly space with the solution space.
15
•Journal Article
Cloud resource scheduling based on improved particle swarm optimization algorithm by membrane computing
TL;DR: The results show that the proposed algorithm can reduce the average completion time of tasks to improve the efficiency of task processing and can get more reasonable cloud computing resource scheduling result.
2
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