reCloud: Towards Reliable Application Deployment in Cloud

  • Akkus I.
  • Chen R.
  • Hilt V.
  • Rimac I.
  • Viswanath B.

We propose reCloud (dubbed for reliable cloud), a novel cloud reliability framework. It incorporates any pieces of dependency information about a data center that is available to the cloud provider. Such information includes, for instance, the configuration and the states of the hosts, switches, power supplies and cooling systems, as well as their dependency topologies. With this information, our reCloud system can proactively find a cloud application's reliable deployment plans in a data center that fulfill the developer's requirements before the application's actual deployment, and also reCloud can efficiently assess the reliability of these deployment plans in a quantitative manner. reCloud scales well, and it works efficiently even in a large-scale cloud environment.

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 ...