High-performance Migration Tool for Live Container in a Workflow (original) (raw)
Abstract
As a lightweight virtualization solution, container technology can provide resource-limiting capabilities and can run multiple isolated process sets under a single kernel instance. Multitenant preemption leads to competition in computing, storage, and network resources, resulting in degraded computing service performance. Virtualization service migration can provide a solution to the problem of resource shortage in supercomputing systems. However, the resource overhead and delay in the migration process also reduce the efficiency of high-performance computers. To solve this problem, this dissertation designs a migration tool. Firstly, this dissertation proposes a method of container migration. Secondly, this dissertation optimizes the startup of containers from checkpoints and proposes a multicontainer migration strategy, reducing the migration time by 30% compared to sequential migration. The migration method in this paper provides valuable experience for service migration in supercomputers and data centers.
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Funding
This work was supported by National Program on Key Research Project (No.2018YFB0204400), by NSFC (No.61702484 and No.61972380), by CASSPRP (XDB24050200), by CCF-Baidu Open Fund (CCF-BAIDU OF2020015), by Youth Innovation Promotion Association of Chinese Academy of Sciences (No.2021099), by State Grid Corporation of China Headquarters Project (5700-202158261A-0-0-00).
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Authors and Affiliations
- University of Chinese Academy of Sciences, Beijing, China
Zhanyuan Di, En Shao & Guangming Tan - State Key Laboratory of Computer Architecture, Institute of Computing Technology, CAS, Beijing, China
Zhanyuan Di, En Shao & Guangming Tan
Authors
- Zhanyuan Di
- En Shao
- Guangming Tan
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Correspondence toEn Shao.
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Di, Z., Shao, E. & Tan, G. High-performance Migration Tool for Live Container in a Workflow.Int J Parallel Prog 49, 658–670 (2021). https://doi.org/10.1007/s10766-021-00697-z
- Received: 07 November 2020
- Accepted: 27 February 2021
- Published: 23 March 2021
- Version of record: 23 March 2021
- Issue date: October 2021
- DOI: https://doi.org/10.1007/s10766-021-00697-z