Title: Resource scheduling optimisation algorithm for containerised microservice architecture in cloud computing

Authors: Peng Li; Jinquan Song; He Xu; Lu Dong; Yang Zhou

Addresses: School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Jiangsu, Nanjing, 210003, China ' School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Jiangsu, Nanjing, 210003, China ' School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Jiangsu, Nanjing, 210003, China ' School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Jiangsu, Nanjing, 210003, China ' School of Computer Science and Technology, Nanjing University of Posts and Telecommunications, Jiangsu, Nanjing, 210003, China

Abstract: Currently, the containerised microservice architecture has aroused great concern. The single application is developed as a suite of small services to facilitate the application deployment, expansion and management. The traditional scheduling of microservice tends to focus on the load balancing of cluster, ignoring the quality of service (QoS). Therefore, this paper proposes a prediction model of component relevance, by adopting the optimised artificial bee colony algorithm (OABC) on the containerised microservice scheduling. Different assessment strategies are adopted according to the differences in the correlation among components. Two-point crossover operator is introduced to improve the exploration ability of the algorithm. The mutation operator is added to enhance the local search ability, and the mutation probability is set to the dynamic value which varies with the number of iterations to speed up the convergence of the algorithm. The experimental results show that the OABC is preferable to the artificial bee colony algorithm (ABC) and the greedy algorithm as to the cluster load balancing and service response time aspects.

Keywords: cloud computing; microservice; container; load balancing; artificial bee colony; ABC; quality of service; QoS.

DOI: 10.1504/IJHPSA.2018.094144

International Journal of High Performance Systems Architecture, 2018 Vol.8 No.1/2, pp.51 - 58

Received: 19 Nov 2017
Accepted: 10 Feb 2018

Published online: 01 Aug 2018 *

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