Ant Colony Algorithm for Container-based Microservice Scheduling in Hybrid Cloud. Issue 1 (August 2021)

• Record Type: Journal Article
• Authors: Lin, Miao; Xi, Jianqing; Bai, Weihua; Wu, Jiayin
• Is Part Of: Journal of physics. Volume 1994:Issue 1(2021)
• Publication Date: 2021-08
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1994/1/012028
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: The microservice model divides the application into a group of loosely coupled and collaborative fine-grained services, which results in the workflow scheduling problem, especially in the complex environment of resource diversity such as hybrid cloud. To solve this problem, this paper establishes a workflow scheduling model of microservice based on multiple container instances and proposes an ant colony optimization (ACO) algorithm to optimize finish time and resource cost. The algorithm proposed optimizes update strategies of multi-objective heuristic information to improve the selection probability of the dominant path. The comparative experiments show that the proposed optimization algorithm achieves better results in scheduling objectives in the hybrid cloud.