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Minimum-Impact First: Scheduling Virtual Machines Under Maintenance Scenarios

Published: 10 January 2020 Publication History

Abstract

Virtual Machine (VM) migration is an important feature for ensuring smooth operations during maintenance and disaster recovery scenarios. The migration might be inter-site and in such a case the inter-site bandwidth which is typically Wide Area Network (WAN) might be a bottleneck. In such a case, the bandwidth is affected by the amount of inter-VM traffic that becomes separated during the migration process. The amount of separated traffic might not only cause degradation of the of the Quality of Service (QoS) of inter-communicating VMs but can also delay the migration process due to the congestion of the migration link. The state-of-the-art algorithm due to Yazidi et al. is an affinity aware algorithm that does not consider the completion time of the migration. The first stage of our algorithm is identical to Yazidi et al. where we resort to graph partitioning theory in order to partition the VMs into groups with high intra-group communication. In the second stage, we devise a greedy algorithm for controlling the order of the migration groups by considering their inter-group traffic that greedily selects groups with the lowest impact in terms of volume of separated traffic which we denominate Minimum-Impact First (MIF). We also design a latency-aware algorithm that only schedules the quickest migration first. The latter simple heuristic interestingly outperforms legacy works in the case of migration over a non-dedicated link. We find that our MIF algorithm consistently outperforms the state-of-the-art algorithms by a clear margin using real-traffic traces by a margin larger than 40%. We show that the MIF algorithm ensures the lowest amount of separated traffic in both dedicated-link and non-dedicated-link scenarios.

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MEDES '19: Proceedings of the 11th International Conference on Management of Digital EcoSystems
November 2019
350 pages
ISBN:9781450362382
DOI:10.1145/3297662
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 10 January 2020

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Author Tags

  1. Graph Partitioning
  2. Live Migration
  3. Migration Scheduling
  4. Separated Traffic

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MEDES '19 Paper Acceptance Rate 41 of 102 submissions, 40%;
Overall Acceptance Rate 267 of 682 submissions, 39%

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