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dc.contributor.advisorLiu, Ling
dc.contributor.authorZhang, Qi
dc.date.accessioned2018-05-31T18:09:11Z
dc.date.available2018-05-31T18:09:11Z
dc.date.created2017-05
dc.date.issued2017-04-07
dc.date.submittedMay 2017
dc.identifier.urihttp://hdl.handle.net/1853/59793
dc.description.abstractDynamic memory consolidation is an important enabler for high performance virtual machine (VM) execution in virtualized Cloud. Efficient just-in-time memory balancing requires three core capabilities: (i) Detecting memory pressure across VMs hosted on a physical machine; (ii) Allocation of memory to respective VMs; (iii) Enabling fast recovery upon making newly allocated memory available at the high pressure VMs. Although the Balloon driver technology facilitates the second task, it remains difficult to accurately predict the VM memory demands at affordable overhead, especially under unpredictable and changing workloads. Furthermore, no prior study analyzed the effect of slow response of VM execution to the newly available memory due to paging based application recovery. In this dissertation research, I have made four original contributions to dynamic shared memory management in terms of architecture, systems and optimizations for improving VM execution performance and security. First, we designed and developed MemPipe, a shared memory inter-VM communication channel for fast inter-VM network I/O. MemPipe increases the shared memory utilization by adaptively adjusting the shared memory size according to workloads demands. It also reduces the inter-VM network communication overhead by directly copying the packets from the sender VM's user space to the shared memory area. Second, we developed iBalloon, a light-weight and transparent prediction based facility to enable automated or semi-automated ballooning with more customizable, accurate, and efficient memory balancing policies among VMs. Third, we developed MemFlex, a novel shared memory swapping facility that can effectively utilizes host idle memory by a hybrid memory swap-out model and a fast swap-in optimization. Fourth, we introduced SecureStack, which is a kernel backed tool to prevent the sensitive data on the function stack from being illegally accessed by the untrusted functions. SecureStack introduces three procedures to protect, restore, and clear the stack in a reliable and low cost manner. It is highly transparent to the users and does not bring any new vulnerability to the existing system. The above research developments are packaged into MemLego, a new memory management framework for memory-centric computing in the big data era.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherGeorgia Institute of Technology
dc.subjectVirtualization
dc.subjectMemory management
dc.subjectShared memory
dc.titleDynamic shared memory architecture, systems, and optimizations for high performance and secure virtualized cloud
dc.typeDissertation
dc.description.degreePh.D.
dc.contributor.departmentComputer Science
thesis.degree.levelDoctoral
dc.contributor.committeeMemberPu, Calton
dc.contributor.committeeMemberAhamad, Mustaque
dc.contributor.committeeMemberBlough, Douglas M.
dc.contributor.committeeMemberLofstead, Jay
dc.date.updated2018-05-31T18:09:11Z


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