Multi-resource balance optimization for virtual machine placement in cloud data centers. (December 2020)

• Record Type: Journal Article
• Authors: Wei, Wenting; Wang, Kun; Wang, Kexin; Gu, Huaxi; Shen, Hong
• Is Part Of: Computers & electrical engineering. Volume 88(2020)
• Publication Date: 2020-12
• Subjects: Data centers -- Virtual machine placement -- Multi-resource balance -- NSGA-II -- Bin-packing; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2020.106866
• Languages: English
• ISSNs: 0045-7906

Abstract

Graphical abstract: Abstract: Network virtualization is widely regarded as a key enabler to improve the desired flexibility and scalability of cloud computing services. With the rapid expansion of data centers, it remains a challenge to provide efficient management of resources for virtual machine placement. Due to multi-dimensional physical resources in servers, there maybe resource fragmentation causing by an imbalanced usage of multi-dimensional resources, when multiple virtual machines carrying diverse requests are deployed on the same server simultaneously. In this paper, we devote to how to balance multiple resources usage to alleviate resource fragmentation while maximizing the service rate for virtual machine placement, so that it can prevent waste of physical resources and undesirable performance. In order to solve such a bi-objective optimization problem, we present a joint bin-packing heuristic and genetic algorithm which achieves an approximate optimal solution with much lower time complexity.