On-Demand State Migration Protocol for Elastic IMS Cloud Components

  • Cucinotta T.
  • Hilt V.
  • Jul E.
  • Meroni A.
  • Sala A.

In the context of Network Functions Virtualisation one of the key feature we have to deal with is elasticity, namely the capability of a Virtualised Network Function to be designed so as to work in dynamic clusters. Usually, to balance the incoming load, a load-balancer is put in front of the cluster; however, because most components embed stateful logic, we need mech- anisms to track state in order to preserve functionalities. Many solutions to this problem have been proposed; in particular, for IP Multimedia Subsystem deployments, various designs that employ stateless components along with elastic Database solutions. In the following we show how this kind of solution could impact performance, and present a different approach, namely by using an application-aware, stateful load-balancer along with a simple state migration protocol, so that we transfer state records from one component’s instance to another on-demand while preserving functionalities without failures.

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 ...