Cloud service resource allocation with particle swarm optimization algorithm

Cheng, Shi1; Guo, Lantian2; Yang, Tao3; Feng, Jiqiang4; Sun, Yifei5; Shao, Chang6; Duan, Qiqi6

10.1007/978-981-10-7179-9_41

2017

1865-0929

12th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2017

791

523-532

Harbin, China

Springer Verlag

Cloud service resource allocation is an essential task in cloud computing. The cloud service resource allocation problem is modeled as an optimization problem, and is solved via different particle swarm optimization (PSO) variants in this paper. The aim of our method is to minimize the delay and the price at the same time. Based on the experimental results, it could be conducted that the good performance could be achieved via PSO algorithms. The future research is to utilize PSO algorithms on solving more real-world problems, especially with other quality of service problems.
© Springer Nature Singapore Pte Ltd 2017.

其他

EI

Shenzhen Science and Technology Innovation Commission[201703063000511] ; [GK201703062] ; [GK201603014] ; Shenzhen Science and Technology Innovation Commission[ZDSYS201703031748284] ; Natural Science Foundation of Shaanxi Province[2017JQ6070] ; National Natural Science Foundation of China[61672334] ; National Natural Science Foundation of China[61672433] ; National Natural Science Foundation of China[61401283] ; National Natural Science Foundation of China[61402373]

20174704440181

Computation theory ; Distributed database systems ; Quality of service ; Resource allocation ; Swarm intelligence

Computer Theory, Includes Formal Logic, Automata Theory, Switching Theory, Programming Theory:721.1 ; Computer Software, Data Handling and Applications:723 ; Database Systems:723.3 ; Management:912.2

EV Compendex

1.School of Computer Science, Shaanxi Normal University, Xi’an, China
2.Shenzhen Research Institute, Northwestern Polytechnical University, Shenzhen, China
3.School of Automation, Northwestern Polytechnical University, Xi’an, China
4.Institute of Intelligent Computing Science, Shenzhen University, Shenzhen, China
5.School of Physics and Information Technology, Shaanxi Normal University, Xi’an, China
6.Shenzhen Key Lab of Computational Intelligence, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China

Cheng, Shi,Guo, Lantian,Yang, Tao,et al. Cloud service resource allocation with particle swarm optimization algorithm[C]:Springer Verlag,2017:523-532.