April 11, 2016

Lean Cloud Computing

  • Bauer E.

Cloud computing enables organizations to shift from traditional, capacity-driven operational models to lean, demand-driven operational models. Lean cloud capacity management can improve operational efficiency, resource utilization and service agility, and thereby reduce costs. This work considers lean cloud computing via three interlocking threads of analysis: 1. Methodically applying lean (i.e., Toyota production system) thinking to the business problem of managing application, virtual resource and physical element capacity in the context of cloud computing 2. Applying insights from electric power generation and grid operations to cloud infrastructure operations 3. Applying insights from inventory management to cloud capacity management.

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 ...