SLA-aware multiple migration planning and scheduling in SDN-NFV-enabled clouds

In Software-Defined Networking (SDN)-enabled cloud data centers, live migration is a key approach used for the reallocation of Virtual Machines (VMs) and Virtual Network Functions (VNFs). Using live migration, cloud providers can address their dynamic resource management and fault tolerance objectiv...

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Veröffentlicht in:The Journal of systems and software 2021-06, Vol.176, p.110943, Article 110943
Hauptverfasser: He, TianZhang, Toosi, Adel N., Buyya, Rajkumar
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Sprache:eng
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Zusammenfassung:In Software-Defined Networking (SDN)-enabled cloud data centers, live migration is a key approach used for the reallocation of Virtual Machines (VMs) and Virtual Network Functions (VNFs). Using live migration, cloud providers can address their dynamic resource management and fault tolerance objectives without interrupting the service of users. However, performing multiple live migrations in arbitrary order can lead to service degradation. Therefore, efficient migration planning is essential to reduce the impact of live migration overheads. In addition, to prevent Quality of Service (QoS) degradations and Service Level Agreement (SLA) violations, it is necessary to set priorities for different live migration requests with various urgency. In this paper, we propose SLAMIG, a set of algorithms that composes deadline-aware multiple migration grouping algorithm and on-line migration scheduling to determine the sequence of VM/VNF migrations. The experimental results show that our approach with reasonable algorithm runtime can efficiently reduce the number of deadline misses and has a good migration performance compared with the one-by-one scheduling and two state-of-the-art algorithms in terms of total migration time, average execution time, downtime, and transferred data. We also evaluate and analyze the impact of multiple migrations on QoS and energy consumption. •Deadline-aware multiple migration scheduling and planning.•Maximal concurrent grouping with minimum weight based on migration resource dependency graph.•On-line migration scheduler to manage different concurrent groups.•Evaluation of total migration time, execution time, downtime, and transferred data.•Impact of multiple migrations on Quality of Services and energy consumption.
ISSN:0164-1212
1873-1228
DOI:10.1016/j.jss.2021.110943