October 12, 2017

Edge Computing in the ePC --- A Reality Check

  • Abe Y.
  • Hadzic I.
  • Woithe H.

Mobile Edge Computing (MEC) has received much attention from the research community in recent years. A significant part of the published work has studied the telecom-centric MEC architecture, which assumes that the computing resource is located at the edge of the mobile access network (e.g., the Evolved Packet Core), typically at the first aggregation level. Many authors make a silent assumption in their analyses that the latency at this stage of the network is negligible. In this paper we show not only that this assumption false, but that in some common cases the latency of the first-aggregation stage dominates the end-to-end latency. We challenge the latency argument in the context of present-day access networks and discuss what must be done to pave the way for practical deployments of MEC.

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 ...