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April 10
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Alex Depoutovich (Friday, 12:30pm, BA5205)
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A Practical Implementation of Clustered Fault Tolerant Write
Acceleration in a Virtualized Environment
Host-side flash storage opens up an exciting avenue for accelerating Virtual Machine (VM) writes in virtualized datacenters. The key challenge with implementing such an acceleration layer is to do so without breaking live VM migration which is essential for providing distributed resource management and high availability. High availability also powers-on VMs on new host when the previous host crashes. We introduce FVP, a fault tolerant host-side flash write acceleration layer that seamlessly integrates with the virtualized environment while preserving dynamic resource management and high availability, the holy tenets of a virtualized environment. FVP integrates with the VMware ESX hypervisor kernel to intercept VM I/O and redirects the I/O to host-side flash devices. VMs experience flash latencies instead of SAN latencies and write intensive applications such as databases and email servers benefit from predictable write throughput. No changes are required to the VM guest operating systems so VM applications can continue to function seamlessly without any modifications. FVP pools together all the host-side flash devices in the cluster so every host can access another host’s flash device preserving VM mobility. By replicating VM writes onto peer host-side flash devices, FVP is able to tolerate multiple cascading host and flash failures. Failure recovery is distributed, requiring no central co-ordination. We describe the workings of the FVP key components and demonstrate how FVP reduces VM latencies to accelerate VM writes, improves performance predictability, and increases virtualized datacenter efficiency.
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Alex Depoutovitch works at PernixData as a Senior Member of Technical Staff since 2014. Previously, he worked for VMware and Novel doing operating system-level development and research. He got his Ph.D. degree in Computer Science at the University of Toronto in 2011 under the supervision of Michael Stumm.
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April 29
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Don Porter (Wednesday, 12:00pm, BA5205)
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Towards Ultra-Lightweight, Secure Application Packages
Packaging an application with all of its software dependencies,
including libraries and an OS API, is essential to deploying
applications across a range of cloud and local systems. This talk
first presents trade-offs in density and security of current packaging
options, including virtual machines and containers. The talk then
describes the Graphene library OS, which strikes a better balance of
density and security. Graphene can package unmodified Linux
applications. The talk concludes by describing ongoing work to
leverage the library OS architecture to improve application security.
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Don Porter is an Assistant Professor and Kieburtz Young Scholar of
Computer Science at Stony Brook University. Porter's research
interests broadly involve developing more efficient and secure
computer systems. Porter earned a Ph.D. and M.S. from The University
of Texas at Austin, and a B.A. from Hendrix College. He has received
awards including the NSF CAREER Award and the Bert Kay Outstanding
Dissertation Award from UT Austin.
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May 12
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Ben Kim (Tuesday, 12:00pm, BA5205)
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Caelus: Verifying the Consistency of Cloud Services with Battery-Powered Devices
Cloud storage services such as Amazon S3, DropBox, Google Drive and Microsoft OneDrive have become increasingly popular. However, users may be reluctant to completely trust a cloud service. Current proposals in the literature to protect the confidentiality, integrity and consistency of data stored in the cloud all have shortcomings when used on battery-powered devices – they either require devices to be on longer so they can communicate directly with each other, rely on a trusted service to relay messages, or cannot provide timely detection of attacks. We propose Caelus, which addresses these shortcoming. The key insight that enables Caelus to do this is having the cloud service declare the timing and order of operations on the cloud service. This relieves Caelus devices from having to record and send the timing and order of operations to each other – instead, they need to only ensure that the timing and order of operations both conforms to the cloud’s promised consistency model and that it is perceived identically on all devices. In addition, we show that Caelus is general enough to support popular consistency models such as strong, eventual and causal consistency. Our experiments show that Caelus can detect consistency violations on Amazon’s S3 service when the desired consistency requirements set by the user are stricter than what S3 provides. Caelus achieves this with a roughly 12.6% increase in CPU utilization on clients, 1.3% of network bandwidth overhead and negligible impact on the battery life of devices.
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Ben is a PhD student working with Prof. David Lie. His research interest is building secure and reliable computer systems. Ben earned a M.S. and B.Sc. from University of Toronto.
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