January 01, 2018

Providing ultra-reliable low latency services for 5G with unattended datacenters

  • Hilt A.
  • Jaro G.
  • Rotter C.
  • Varga J.

The strict requirements imposed by ultra-reliable low latency (uRLL) services in 5G can be costly for 5G network operators: low latency requires the deployment of distributed datacenters, while ultra-reliability usually means attended datacenters. This paper checks whether it is possible to operate the datacenters hosting uRLL services without on-site support without affecting service availability. Overall, the paper shows that deploying additional redundant hardware and implementing urLL services by exploiting these extra resources, the required availability levels can be maintained without on-site support, which may mean significant OPEX save for 5G network operators planning country-wide coverage for uRLL services.

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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 ...