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There is now a CONTENT FREEZE for Mercury while we switch to a new platform. It began on Friday, March 10 at 6pm and will end on Wednesday, March 15 at noon. No new content can be created during this time, but all material in the system as of the beginning of the freeze will be migrated to the new platform, including users and groups. Functionally the new site is identical to the old one. webteam@gatech.edu
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Title: Dynamic Shared Memory Architecture, Systems, and Optimizations for High Performance and Secure Virtualized Cloud
Qi Zhang
School of Computer Science
College of Computing
Georgia Institute of Technology
Date: Monday, February 27, 2017
Time: 1:00 PM - 3:00 PM EDT
Location: KACB 3402
Committee:
Dr. Ling Liu (Advisor, School of Computer Science, Georgia Institute of Technology)
Dr. Calton Pu (School of Computer Science, Georgia Institute of Technology)
Dr. Mustaque Ahamad (School of Computer Science, Georgia Institute of Technology)
Dr. Douglas M. Blough (School of Electrical and Computer Engineering, Georgia Institute of Technology)
Dr. Jay Lofstead (Sandia National Laboratories)
Abstract:
Dynamic memory consolidation is an important enabler for high performance virtual machine (VM) execution in virtualized Clouds. 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 balloon driver technology facilitate 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 adjust 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 swapping 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.
In this PhD defense exam, I will focus on technical design of SecureStack and MemLego.
