Rethinking Virtual Machines Live Migration for Memory Disaggregation

Resource underutilization has troubled data centers for several decades. On the CPU front, live migration plays a crucial role in reallocating CPU resources. Nevertheless, contemporary Virtual Machine (VM) live migration methods are burdened by substantial resource consumption. In terms of memory management, disaggregated memory offers an effective solution to enhance memory utilization, but leaves a gap in addressing CPU underutilization. Our findings highlight a considerable opportunity to optimize live migration in the context of disaggregated memory systems. We introduce Anemoi, a resource management system that seamlessly integrates VM live migration with memory disaggregation to address the aforementioned gap. In the context of disaggregated memory, remote memory becomes accessible from destination nodes, effectively eliminating the need for extensive network transmission of memory pages, and thereby significantly reducing migration time. In addition, we propose using memory replicas as an optimization to the live migration system. To mitigate the overhead of potential excessive memory consumption, we develop a dedicated compression algorithm. Our evaluations demonstrate that Anemoi leads to a notable 69% reduction in network bandwidth utilization and an impressive 83% reduction in migration time compared to traditional VM live migration. Additionally, our compression algorithm achieves an outstanding space-saving rate of 83.6%.

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Publication Details

Journal
IEEE Transactions on Parallel and Distributed Systems
Published
2025-08-18
DOI
https://doi.org/10.1109/tpds.2025.3597149
Primary Topic
Advanced Data Storage Technologies
Type
article
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article

Rethinking Virtual Machines Live Migration for Memory Disaggregation

Zhengwei Qi, Xingguo Jia, Xingzi Yu, Yun Wang et al.
IEEE Transactions on Parallel and Distributed Systems
Advanced Data Storage Technologies
article

Rethinking Virtual Machines Live Migration for Memory Disaggregation

Zhengwei Qi, Xingguo Jia, Xingzi Yu, Yun Wang, Senhao Yu, Jin Zhang
article en

Abstract

Resource underutilization has troubled data centers for several decades. On the CPU front, live migration plays a crucial role in reallocating CPU resources. Nevertheless, contemporary Virtual Machine (VM) live migration methods are burdened by substantial resource consumption. In terms of memory management, disaggregated memory offers an effective solution to enhance memory utilization, but leaves a gap in addressing CPU underutilization. Our findings highlight a considerable opportunity to optimize live migration in the context of disaggregated memory systems. We introduce Anemoi, a resource management system that seamlessly integrates VM live migration with memory disaggregation to address the aforementioned gap. In the context of disaggregated memory, remote memory becomes accessible from destination nodes, effectively eliminating the need for extensive network transmission of memory pages, and thereby significantly reducing migration time. In addition, we propose using memory replicas as an optimization to the live migration system. To mitigate the overhead of potential excessive memory consumption, we develop a dedicated compression algorithm. Our evaluations demonstrate that Anemoi leads to a notable 69% reduction in network bandwidth utilization and an impressive 83% reduction in migration time compared to traditional VM live migration. Additionally, our compression algorithm achieves an outstanding space-saving rate of 83.6%.

IEEE Transactions on Parallel and Distributed SystemsVol. 36(11)
Shanghai Jiao Tong University (CN)
Reduced inequalities
Openalex Percentile: Top 77%
Advanced Data Storage Technologies
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Rethinking Virtual Machines Live Migration for Memory Disaggregation — Zhengwei Qi, Xingguo Jia, et al. · IEEE Transactions on Parallel and Distributed Systems (2025) | TGRS Research Map | TGRS