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Cicada: Predictive Guarantees for Cloud Network Bandwidth

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dc.contributor.advisor Hari Balakrishnan
dc.contributor.author LaCurts, Katrina en_US
dc.contributor.author Mogul, Jeffrey C. en_US
dc.contributor.author Balakrishnan, Hari en_US
dc.contributor.author Turner, Yoshio en_US
dc.contributor.other Networks & Mobile Systems en
dc.date.accessioned 2014-03-31T20:15:06Z
dc.date.available 2014-03-31T20:15:06Z
dc.date.issued 2014-03-24
dc.identifier.uri http://hdl.handle.net/1721.1/85975
dc.description.abstract In cloud-computing systems, network-bandwidth guarantees have been shown to improve predictability of application performance and cost. Most previous work on cloud-bandwidth guarantees has assumed that cloud tenants know what bandwidth guarantees they want. However, application bandwidth demands can be complex and time-varying, and many tenants might lack sufficient information to request a bandwidth guarantee that is well-matched to their needs. A tenant's lack of accurate knowledge about its future bandwidth demands can lead to over-provisioning (and thus reduced cost-efficiency) or under-provisioning (and thus poor user experience in latency-sensitive user-facing applications). We analyze traffic traces gathered over six months from an HP Cloud Services datacenter, finding that application bandwidth consumption is both time-varying and spatially inhomogeneous. This variability makes it hard to predict requirements. To solve this problem, we develop a prediction algorithm usable by a cloud provider to suggest an appropriate bandwidth guarantee to a tenant. The key idea in the prediction algorithm is to treat a set of previously observed traffic matrices as "experts" and learn online the best weighted linear combination of these experts to make its prediction. With tenant VM placement using these predictive guarantees, we find that the inter-rack network utilization in certain datacenter topologies can be more than doubled. en_US
dc.format.extent 13 p. en_US
dc.relation.ispartofseries MIT-CSAIL-TR-2014-004
dc.rights Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International *
dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/4.0/ en_US
dc.subject networking en_US
dc.subject machine learning en_US
dc.subject traffic prediction en_US
dc.title Cicada: Predictive Guarantees for Cloud Network Bandwidth en_US
dc.date.updated 2014-03-31T20:15:06Z


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