CBVMI: A container-based virtualization method for instruments. (December 2018)

• Record Type: Journal Article
• Authors: Huang, Min; Liu, Zhaoqing
• Is Part Of: Measurement. Volume 130(2018)
• Page Start: 151
• Page End: 160
• Publication Date: 2018-12
• Subjects: Intelligent instruments -- Network test system -- Virtualization -- LXC; Weights and measures -- Periodicals; Measurement -- Periodicals; Measurement; Weights and measures; Periodicals; 530.8
• DOI: 10.1016/j.measurement.2018.08.003
• Languages: English
• ISSNs: 0263-2241

Abstract

Highlights: Local resources of instruments can be virtualized and isolated. Local resources can be available to the system to accomplish complex test tasks. The proposed method can be implemented in instruments with limited resources. A real physical platform was built to evaluate the proposed method. Abstract: Intelligent instruments, which dominate the network test system, typically have certain redundant resources even when the test task has ongoing operations. Thus, if these surplus resources can be utilized by the centralized manager and the test task scheduler to conduct test data pre-processing or system-level test data processing, the performance and efficiency of the test system could be greatly improved. This paper proposed a novel method called CBVMI, a Container-Based Virtualization Method for Instruments, which can make full use of these surplus resources of intelligent instruments. Meanwhile, it can achieve effective isolation between virtual resources to avoid interference of test tasks while maintaining necessary network interconnection among virtual resources. Furthermore, CBVMI provides one method for the network bandwidth allocation, and ultimately utilizes the network bandwidth to achieve efficient information transmission among virtual resources. To the best of our knowledge, this is the first work to introduce virtualization techniques into the research of intelligent instruments. The proposed method was evaluated on a real physical platform. The experimental results show that CBVMI can efficiently improve the utilization of system resources.