Nitro: Network-Aware Virtual Machine Image Management in Geo-Distributed Clouds

Abstract : Recently, most large cloud providers, like Amazon and Microsoft, replicate their Virtual Machine Images (VMIs) on multiple geographically distributed data centers to offer fast service provisioning. Provisioning a service may require to transfer a VMI over the wide-area network (WAN) and therefore is dictated by the distribution of VMIs and the network bandwidth in-between sites. Nevertheless, existing methods to facilitate VMI management (i.e., retrieving VMIs) overlook network heterogeneity in geo-distributed clouds.In this paper, we design, implement and evaluate Nitro, a novel VMI management system that helps to minimize the transfer time of VMIs over a heterogeneous WAN. To achieve this goal, Nitro incorporates two complementary features. First, it makes use of deduplication to reduce the amount of data which will be transferred due to the high similarities within an image and in-between images. Second, Nitro is equipped with a network-aware data transfer strategy to effectively exploit links with high bandwidth when acquiring data and thus expedites the provisioning time. Experimental results show that our network-aware data transfer strategy offers the optimal solution when acquiring VMIs while introducing minimal overhead. Moreover, Nitro outperforms state-of-the-art VMI storage systems (e.g., OpenStack Swift) by up to 77%.
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Jad Darrous, Shadi Ibrahim, Amelie Chi Zhou, Christian Pérez. Nitro: Network-Aware Virtual Machine Image Management in Geo-Distributed Clouds. CCGrid 2018 - 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, May 2018, Washington D.C., United States. pp.553-562, ⟨10.1109/CCGRID.2018.00082⟩. ⟨hal-01745405⟩

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