Complexity and Flexible Grid Networks

  • Morea A.

Flexible grids promise to revolutionize the net- work design and control plane of future optical networks by providing increased adaptability of spectral resources to heterogeneous network conditions. Unfortunately, flexibility is often provided at the cost of additional complexity in the network management. In this paper, we consider the optimization of routing and spectrum allocation in FlexiGrid Networks and explore the trade-off between network cost and problem complex- ity according to the following aspects: traffic grooming, regeneration, modulation/baud-rate assignment. We provide slice-based and channel-based Integer Linear Programming models which cover multiple network settings and compare their performance in terms of computational complexity and minimization of the overall spectrum occupation or transceiver utilization. Numerical results show TBD

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 ...