Exploring Relationships In Complex Heterogeneous Networks

  • Sala A.

Current trends are showing that we are at the dawn of a new technological era, which is driven by the digitalization of everything and everyone. In this era, the utmost goal should be to create efficiency in human lives by maximizing our capability to instantly attain anything, thereby saving time. In order to realize this revolution, the network must glue together an increasingly complex landscape of applications and services, many of which are mission critical, such self-driving vehicles, or time-critical, such as human-computer interaction or financial services. This talk will discuss the opportunities and the research challenges of realizing an intelligent network able to satisfy the needs of this upcoming digital era at scale. Specifically, real-time data from end-users and infrastructure will play a significant role in learning the contextual factors of different applications, and leveraging those to proactively respond to their dynamic requirements.

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 ...