February 06, 2017

Reconciling Resource Abstraction, Allocation and Routing Optimization

  • Colle D.
  • Demeester P.
  • Papadimitriou D.

Resource abstraction aims at enabling flexible allocation of capacity to serve demands by aggregating physical resources taken out of distributed resource pools accessible via dedicated gateways. This paradigm sits at the heart of many networking models including resource virtualization and other cloud computing. In this paper, we show this generic problem can be modeled by combining and extending the Hub Location with the Location Routing Problem, referred to as the Hub-Location Routing Problem (HLRP). A mixed- integer program for the HLRP is proposed and evaluated using representative settings. We compare the results with those obtained when modeling the initial problem as an Location Routing Problem only; hence, obtain a quantitative assessment of the performance tradeoffs between resource abstraction, (al)location and routing.

View Original Article

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 ...