Heterogeneous Resource Allocation in Datacenters

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dc.contributor.advisorVarman, Peter Jen_US
dc.creatorParvez Khan, Mohammad Shahriaren_US
dc.date.accessioned2020-04-27T19:16:28Zen_US
dc.date.available2020-04-27T19:16:28Zen_US
dc.date.created2020-05en_US
dc.date.issued2020-04-24en_US
dc.date.submittedMay 2020en_US
dc.date.updated2020-04-27T19:16:28Zen_US
dc.description.abstractVirtualized datacenters are considerably cost-effective and convenient to their clients who routinely deploy clusters of communicating Virtual Machines (VMs) on physical infrastructures to create a distributed ensemble of servers for Web applications. These applications require multiple resources such as compute, memory, storage and network bandwidth for execution, motivating the need for fair allocation policies. Here, we present a new model for allocating multiple resources among clients, and our results show that we can obtain significantly better utilization than existing approaches, while provably maintaining good fairness properties like Envy Freedom and Sharing Incentive. We also look at datacenter optimization from an opposite standpoint, i.e., VM placement. It is necessary to place a high number of virtual servers per physical host to maximize the benefits of a shared infrastructure. We present a framework to automate the placement of VMs in several scenarios alongside the corresponding ILP optimization models and numerical results.en_US
dc.format.mimetypeapplication/pdfen_US
dc.identifier.citationParvez Khan, Mohammad Shahriar. "Heterogeneous Resource Allocation in Datacenters." (2020) Master’s Thesis, Rice University. <a href="https://hdl.handle.net/1911/108393">https://hdl.handle.net/1911/108393</a>.en_US
dc.identifier.urihttps://hdl.handle.net/1911/108393en_US
dc.language.isoengen_US
dc.rightsCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.en_US
dc.subjectData Centeren_US
dc.subjectResource Allocationen_US
dc.subjectHeterogeneous Resourcesen_US
dc.subjectQoSen_US
dc.subjectFairnessen_US
dc.subjectEnvy Freedomen_US
dc.subjectSharing Incentiveen_US
dc.subjectBandwidth Allocationen_US
dc.subjectScalabilityen_US
dc.subjectPlacementen_US
dc.subjectVirtual Machinesen_US
dc.subjectVirtual Clustersen_US
dc.subjectConnectivity Constraintsen_US
dc.titleHeterogeneous Resource Allocation in Datacentersen_US
dc.typeThesisen_US
dc.type.materialTexten_US
thesis.degree.departmentElectrical and Computer Engineeringen_US
thesis.degree.disciplineEngineeringen_US
thesis.degree.grantorRice Universityen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Scienceen_US
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