基于哈希图的虚拟机实时迁移方法

田俊峰; 屈雪晴; 何欣枫; 李珍

doi:10.11999/JEIT190200

基于哈希图的虚拟机实时迁移方法

doi: 10.11999/JEIT190200

河北大学网络空间安全与计算机学院保定 071002

基金项目: 国家自然科学基金(61802106)

详细信息

作者简介:
田俊峰：男，1965年生，教授，研究方向为信息安全与分布式计算

屈雪晴：女，1994年生，硕士生，研究方向为信息安全与分布式计算

何欣枫：男，1976年生，副教授，研究方向为云计算，可信计算

李珍：女，1981年生，副教授，研究方向为软件安全，漏洞检测

通讯作者:
田俊峰　tjf@hbu.cn

¹⁾ https://docs.hedera.com/docs/hedera-sdks
中图分类号: TP302
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出版历程
- 收稿日期: 2019-03-29
- 修回日期: 2019-08-04
- 网络出版日期: 2019-08-26
- 刊出日期: 2020-03-19

The Method of Virtual Machine Live Migration Based on HashGraph

School of Cyber Security and Computer, Hebei University, Baoding 071002, China

Funds: The National Natural Science Foundation of China (61802106)

摘要

摘要:
跨广域网的虚拟机实时迁移是多数据中心云计算环境的重要技术支撑。当前跨广域网的虚拟机实时迁移受到带宽小和无共享存储的限制而面临着技术挑战，如镜像数据迁移的安全性和一致性问题。为此，该文提出基于哈希图(HashGraph)的跨数据中心虚拟机实时迁移方法，运用去中心化的思想，实现数据中心之间可靠和高效的镜像信息分布式共享。通过HashGraph中Merkle DAG存储结构，改善了重复数据删除在跨数据中心迁移虚拟机镜像时的缺陷。与现有方法相比，该文方法缩短了总迁移时间。
- 云计算 /
- 虚拟机实时迁移 /
- 跨数据中心 /
- 哈希图 /
- 重复数据删除 /
- 3层镜像结构
Abstract:
Live migration of Virtual Machines(VMs) across WANs is an important support for multi-datacenter cloud computing environments. The current live migration of VMs across WANs faces many technical challenges due to the limitations of small bandwidth and no shared storage, such as ensuring the security and consistency of image data migration. Therefore, a method for VM live migration across data centers based on HashGraph is proposed in this paper, decentralized ideas are used to achieve reliable and efficient image distribution between data centers. The Merkle DAG of HashGraph improves the deficiencies of deduplication when migrating images across data centers. Compared with existing methods, it can reduce total migration time.
- Cloud computing /
- Virtual Machine(VM) live migration /
- Across data center /
- HashGraph /
- Data duplication /
- Three-layer image structure
¹⁾ https://docs.hedera.com/docs/hedera-sdks

HTML全文

图 1 H-GMIG的结构

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图 2 跨数据中心迁移虚拟机的过程

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图 3 不同相似度下单次VM迁移所需的总迁移时间

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图 4 不同负载下单虚拟机迁移的网络流量

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图 5 多虚拟机同时迁移所需的迁移总时间

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图 6 多虚拟机迁移的网络流量

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图 7 DDOS攻击测试下总迁移时间的增加量

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表 1 不同距离下的共识时间

距离(km) 最大共识时间(s) 最小共识时间(s) 平均共识时间(s)

10 0.057 0.011 0.019
1000 0.751 0.138 0.590
3000 1.654 0.548 1.050

下载: 导出CSV

表 2 不同距离下的总迁移时间和共识时间对比

距离(km) 10 1000 3000

总迁移时间(s) 25.52 26.84 27.03
共识时间(s) 0.032 0.261 0.751

下载: 导出CSV

参考文献(15)

CLARK C, FRASER K, HAND S, et al. Live migration of virtual machines[C]. Proceedings of the 2nd Conference on Symposium on Networked Systems Design & Implementation, Berkeley, USA, 2005: 273–286.

BRADFORD R, KOTSOVINOS E, FELDMANN A, et al. Live wide-area migration of virtual machines including local persistent state[C]. Proceedings of the 3rd International Conference on Virtual Execution Environments, San Diego, USA, 2007: 169–179. doi: 10.1145/1254810.1254834.

MASHTIZADEH A J, CAI Min, TARASUK-LEVIN G, et al. XvMotion: Unified virtual machine migration over long distance[C]. Proceedings of 2014 USENIX Conference on USENIX Annual Technical Conference, Philadelphia, USA, 2014: 97–108.

HARNEY E, GOASGUEN S, MARTIN J, et al. The efficacy of live virtual machine migrations over the internet[C]. The 2nd International Workshop on Virtualization Technology in Distributed Computing, Reno, USA, 2007: 1–7. doi: 10.1145/1408654.1408662.

YANG Yaodong, MAO Bo, JIANG Hong, et al. SnapMig: Accelerating VM live storage migration by leveraging the existing VM snapshots in the cloud[J]. IEEE Transactions on Parallel and Distributed Systems, 2018, 29(6): 1416–1427. doi: 10.1109/TPDS.2018.2790389

MUGISHA E and ZHANG Gongxuan. Reliable multi-cloud storage architecture based on erasure code to improve storage performance and failure recovery[J]. International Journal of Advanced Cloud Computing and Applied Research, 2017, 3(1): 26–40. doi: 10.23953/cloud.ijaccar.260

RITEAU P, MORIN C, and PRIOL T. Shrinker: Efficient live migration of virtual clusters over wide area networks[J]. Concurrency and Computation: Practice and Experience, 2013, 25(4): 541–555. doi: 10.1002/cpe.2861

RITEAU P, MORIN C, and PRIOL T. Shrinker: Improving live migration of virtual clusters over WANs with distributed data deduplication and content-based addressing[C]. The 17th European Conference on Parallel Processing, Bordeaux, France, 2011: 431–442. doi: 10.1007/978-3-642-23400-2_40.

UCHIBAYASHI T, APDUHAN B, SUGANUMA T, et al. Toward a secure VM migration control mechanism using blockchain technique for cloud computing environment[C]. The 18th International Conference on Computational Science and Its Applications, Melbourne, Australia, 2018: 177–186. doi: 10.1007/978-3-319-95168-3_12.

ZHANG Fei, FU Xiaoming, and YAHYAPOUR R. LayerMover: Fast virtual machine migration over WAN with three-layer image structure[J]. Future Generation Computer Systems, 2018, 83: 37–49. doi: 10.1016/j.future.2018.01.017

ZHANG Fei, FU Xiaoming, and YAHYAPOUR R. LayerMover: Storage migration of virtual machine across data centers based on three-layer image structure[C]. 2016 International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, London, UK, 2016: 400–405. doi: 10.1109/MASCOTS.2016.27.

ZHANG Fei, FU Xiaoming, and YAHYAPOUR R. CBase: A new paradigm for fast virtual machine migration across data centers[C]. The 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, Madrid, Spain, 2017: 284–293. doi: 10.1109/CCGRID.2017.26.

BAIRD L. The swirlds hashgraph consensus algorithm: Fair, fast, byzantine fault tolerance[R]. Swirlds Technical Report SWIRLDS-TR-2016-01, 2016.

ZHANG Fei, FU Xiaoming, and YAHYAPOUR R. A survey on virtual machine migration: Challenges, techniques, and open issues[J]. IEEE Communications Surveys & Tutorials, 2018, 20(2): 1206–1243. doi: 10.1109/COMST.2018.2794881

VARGHESE B and BUYYA R. Next generation cloud computing: New trends and research directions[J]. Future Generation Computer Systems, 2018, 79: 849–861. doi: 10.1016/j.future.2017.09.020

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