January 19, 2017

Low-Level Frame-Buffer Scraping for GPUs in the Cloud

  • Carroll M.
  • Hadzic I.
  • Woithe H.

We describe and evaluate a software-only implementation of a novel mechanism for accessing and streaming GPU-rendered content from the cloud to low-end user devices. The unique properties of our implementation enable the trivial cloud-deployment of graphics-intensive applications, even ones that were not originally intended to run in the cloud. We achieve this goal by creating virtual GPU nodes that appear to the application like hardware devices, but that do not incur the overhead of virtualization. The low-level access to the frame buffer maximizes the number of applications that work out-of-the-box without the system imposing any specific display manager or windowing system. We call this property application transparency. To our knowledge, no other software-only system achieves this level of transparency.

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Recent Publications

August 09, 2017

A Cloud Native Approach to 5G Network Slicing

  • Francini A.
  • Miller R.
  • Sharma S.

5G networks will have to support a set of very diverse and often extreme requirements. Network slicing offers an effective way to unlock the full potential of 5G networks and meet those requirements on a shared network infrastructure. This paper presents a cloud native approach to network slicing. The cloud ...

August 01, 2017

Modeling and simulation of RSOA with a dual-electrode configuration

  • De Valicourt G.
  • Liu Z.
  • Violas M.
  • Wang H.
  • Wu Q.

Based on the physical model of a bulk reflective semiconductor optical amplifier (RSOA) used as a modulator in radio over fiber (RoF) links, the distributions of carrier density, signal photon density, and amplified spontaneous emission photon density are demonstrated. One of limits in the use of RSOA is the lower ...

July 12, 2017

PrivApprox: Privacy-Preserving Stream Analytics

  • Chen R.
  • Christof Fetzer
  • Le D.
  • Martin Beck
  • Pramod Bhatotia
  • Thorsten Strufe

How to preserve users' privacy while supporting high-utility analytics for low-latency stream processing? To answer this question: we describe the design, implementation and evaluation of PRIVAPPROX, a data analytics system for privacy-preserving stream processing. PRIVAPPROX provides three properties: (i) Privacy: zero-knowledge privacy (ezk) guarantees for users, a privacy bound tighter ...