Research Article
Bidding Strategy Based on Adaptive Differential Evolution Algorithm for Dynamic Pricing IaaS Instances
@INPROCEEDINGS{10.1007/978-3-030-67537-0_28, author={Dawei Kong and Guangze Liu and Li Pan and Shijun Liu}, title={Bidding Strategy Based on Adaptive Differential Evolution Algorithm for Dynamic Pricing IaaS Instances}, proceedings={Collaborative Computing: Networking, Applications and Worksharing. 16th EAI International Conference, CollaborateCom 2020, Shanghai, China, October 16--18, 2020, Proceedings, Part I}, proceedings_a={COLLABORATECOM}, year={2021}, month={1}, keywords={Dynamic pricing model Iterative algorithm Amazon cloud Spot instance}, doi={10.1007/978-3-030-67537-0_28} }- Dawei Kong
Guangze Liu
Li Pan
Shijun Liu
Year: 2021
Bidding Strategy Based on Adaptive Differential Evolution Algorithm for Dynamic Pricing IaaS Instances
COLLABORATECOM
Springer
DOI: 10.1007/978-3-030-67537-0_28
Abstract
In recent years, with the development of cloud computing technology and the improvement of infrastructure performance, cloud computing has developed rapidly. In order to meet the diverse needs of users and to maximize the revenue of cloud computing service providers, cloud providers have launched auction-type instances like Amazon Spot instances in the AWS cloud. For dynamic pricing cloud instances, how to select appropriate instance or instance group among multiple instances and make reasonable bids to optimize its own costs is a great challenge. This paper models the dynamic pricing instance pricing and multi-instance combination problem as a constrained optimization problem. Then we introduce the basic differential algorithm and proposes an adaptive differential evolution algorithm to optimize the combination of price bidding based on the optimal cost and the use of instances. Finally, we use real dynamic pricing instance price data released by the Amazon cloud to verify the optimization strategy. The experimental results show that the adaptive differential evolution algorithm has a better optimization effect on short-term task requirements and long-term task requirements.
