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Disaster Recovery Layer for Distributed OpenStack Deployments
Umeå University, Faculty of Science and Technology, Department of Computing Science.
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2020 (English)In: IEEE Transactions on Cloud Computing, ISSN 2168-7161, Vol. 8, no 1, p. 112-123Article in journal (Refereed) Published
Abstract [en]

We present the Disaster Recovery Layer (DRL) that enables OpenStack-managed datacenter workloads, Virtual Machines (VMs) and Volumes, to be protected and recovered in another datacenter, in case of a disaster. This work has been carried out in the context of the EU FP7 ORBIT project that develops technologies for enabling business continuity as a service. The DRL framework is based on a number of autonomous components and extensions of OpenStack modules, while its functionalities are available through OpenStack's Horizon UI and command line interface. Also, the DRL's architecture is extensible, allowing for the easy and dynamic integration of protection, restoration and orchestration plug-ins that adopt new approaches. A distributed disaster detection mechanism was also developed for identifying datacenter disasters and alerting the DRL. For the evaluation of the DRL, a two (active and backup) datacenters testbed has been setup in respective sites in Umea and Lulea, 265km apart and connected through the Swedish national research and education network. In case of a disaster, traffic is redirected between the datacenters utilizing the BGP anycast scheme. The experiments performed, show that DRL can efficiently protect VMs and Volumes, with minimum service disruption in case of failures and low overhead, even when the available bandwidth is limited.

Place, publisher, year, edition, pages
IEEE Computer Society, 2020. Vol. 8, no 1, p. 112-123
Keywords [en]
Disaster recovery, OpenStack, disaster detection, traffic redirection, testbed, MAN/WAN, inter-datacenter network
National Category
Communication Systems
Identifiers
URN: urn:nbn:se:umu:diva-169481DOI: 10.1109/TCC.2017.2745560ISI: 000519700800010Scopus ID: 2-s2.0-85028711329OAI: oai:DiVA.org:umu-169481DiVA, id: diva2:1421116
Available from: 2020-04-02 Created: 2020-04-02 Last updated: 2023-03-24Bibliographically approved

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Tomás, Luis

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CiteExportLink to record
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