April 17, 2017

Stimulus-based Sandbox for Learning Resource Dependencies in Virtualized Distributed Applications

  • Aghasaryan A.
  • Bouzid M.
  • Kostadinov D.

In this paper, we describe a profiling sandbox for cloud-based distributed applications where the dependencies on available computing resources can be methodically elucidated by dynamically applying a series of unitary perturbations on the underlying computing resources. Each such perturbation applied to an application node acts as a stimulus which propagates to performance meters of dependent nodes and reveals correlations and causal relations between the respective entities. The prime application of the sandbox is to learn the behavior of a distributed application under various resource insufficiency or fault conditions and to build dependency models for Quality of Service management and Root Cause Analysis.

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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 ...