Post-doc researcher (M/F) Robust network embedding for network slices

16 Mar 2024
Job Information

Organisation/Company

CNRS

Department

Laboratoire d’analyse et d’architecture des systèmes

Research Field

Computer science
Mathematics » Algorithms

Researcher Profile

First Stage Researcher (R1)

Country

France

Application Deadline

5 Apr 2024 – 23:59 (UTC)

Type of Contract

Temporary

Job Status

Full-time

Hours Per Week

35

Offer Starting Date

1 Oct 2024

Is the job funded through the EU Research Framework Programme?

Not funded by an EU programme

Is the Job related to staff position within a Research Infrastructure?

No

Offer Description

Network Function Virtualization (NFV) opens up the possibility to replace hardwired middle-boxes implementing specific network functions (e.g., firewalls or Web proxies) by Virtual Network Functions (VNFs) running in datacenters and operated as cloud services. In addition to reducing the cost and complexity of the network, this approach enables to deploy and compose VNFs so as to create network slices on demand. Network slices are isolated logical networks coexisting simultaneously on the same Physical Substrate Network (PSN), each one being tailored to the needs of a specific application. The ordered set of VNFs composing a network slice as well as the virtual links established between them are described by a VNF Forwarding Graph (VNF-FG).

We shall study the online problem by assuming that requests for new network slices arrive according to some known stochastic processes. We shall consider several classes of network slice requests, each one being characterized by an ordered sequence of VNFs, a traffic volume and a random lifetime of known statistical distribution. We shall assume that the objective is to minimize the blocking rates of requests due to lack of resources in the physical network. We shall formulate the network embedding problem as a Markov decision process and propose simple network embedding policies whose performance will be compared against that of the optimal policy. The robustness of the proposed policies with respect to the quality of the predictions on the request arrival rates will also be investigated.

— Modelling the problem as an MDP
— Design of heuristics
— Perform numerical experiments
— Write scientific reports and articles
— Give presentations on this work

The work will be done within the SARA team of LAAS-CNRS, Toulouse, France.
.

Requirements

Research Field

Computer science

Education Level

PhD or equivalent

Research Field

Mathematics

Education Level

PhD or equivalent

Languages

FRENCH

Level

Basic

Research Field

Computer science

Years of Research Experience

None

Research Field

Mathematics » Algorithms

Years of Research Experience

None

Additional Information
Eligibility criteria

— PhD in computer science, electrical enginneering, or applied mathematics
— Good knowledge of MDPs and/or linear programming
— Knowledge of 5G networks will be a plus
— Ability to write code and perform numerical experiments

Website for additional job details

https://emploi.cnrs.fr/Offres/CDD/UPR8001-BALPRA-008/Default.aspx

Work Location(s)

Number of offers available

1

Company/Institute

Laboratoire d’analyse et d’architecture des systèmes

Country

France

City

TOULOUSE

Geofield

Where to apply

Website

https://emploi.cnrs.fr/Candidat/Offre/UPR8001-BALPRA-008/Candidater.aspx

Contact

City

TOULOUSE

Website

http://www.laas.fr

STATUS: EXPIRED