April 12, 2017

From Scaling Disparities to Integrated Parallelism: A Decathlon for a Decade

  • Neilson D.
  • Winzer P.

Based on a variety of long-term network traffic data across different geographies and applications as well as long-term scaling trends of key information and communication technologies, we identify fundamental scaling disparities between technologies used to generate and process data and technologies used to transport data. These disparities could lead to the transport network falling behind its required capabilities by a factor of about four every five years. By 2024, we predict the need for 10-Tb/s optical interfaces working in 1-Pb/s optical transport systems. To satisfy these needs, multiplexing in both wavelength and space in the form of a WDM x SDM matrix will be required. We estimate the characteristics of such systems and outline their target specifications, which reveals the need for very significant research progress in multiple areas, from system and network architectures to digital signal processing to integrated arrayed device designs, in order to avoid an optical network capacity crunch.

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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 ...