Research Article
Cloud Resource Combinatorial Double Auction Algorithm Based on Genetic Algorithm and Simulated Annealing
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@INPROCEEDINGS{10.1007/978-3-319-60717-7_43, author={Bing Hu and Lin Yao and Yong Chen and Zinxin Sun}, title={Cloud Resource Combinatorial Double Auction Algorithm Based on Genetic Algorithm and Simulated Annealing}, proceedings={Quality, Reliability, Security and Robustness in Heterogeneous Networks. 12th International Conference, QShine 2016, Seoul, Korea, July 7--8, 2016, Proceedings}, proceedings_a={QSHINE}, year={2017}, month={8}, keywords={Cloud computing resource Combinatorial double auction Genetic algorithm (GA) Simulated annealing (SA)}, doi={10.1007/978-3-319-60717-7_43} }- Bing Hu
Lin Yao
Yong Chen
Zinxin Sun
Year: 2017
Cloud Resource Combinatorial Double Auction Algorithm Based on Genetic Algorithm and Simulated Annealing
QSHINE
Springer
DOI: 10.1007/978-3-319-60717-7_43
Abstract
In this paper, on the basis of the analysis of common market model and some economic theories in the cloud computing resource management process, we propose a cloud resource management model based on combinatorial double auction. In order to solve the winner determination problem (WDP) in the combinatorial double auction, a cloud resource combinatorial double auction algorithm based on genetic algorithm and simulated annealing algorithm is proposed. Simulation results reveal that the algorithm combines genetic algorithm with simulated annealing algorithm (SAGA) outperforms genetic algorithm on fitness value and stability, and as the number of bidders increase, the solution have higher fitness value can be obtained.
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