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DEI - FCTUC
Gerado a 2024-11-01 00:19:45 (Europe/Lisbon).
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Titulo Estágio

ML-guided service placement in the Cloud-to-Edge continuum

Áreas de especialidade

Comunicações, Serviços e Infraestruturas

Sistemas Inteligentes

Local do Estágio

Laboratory of Communications and Telematics (LCT – DEI – UC)

Enquadramento

The Cloud-to-Edge continuum describes a distributed environment that provides network and computing capabilities enabling the deployment of applications and services taking advantage of performance, security, and cost-efficient characteristics that are more suited for each one. However, since the Cloud-to-Edge continuum is a dense and vastly heterogeneous environment, selecting the optimal location for service placement is a big challenge. AI and ML are becoming essential to help process and analyze alternatives to guide different management tasks, including those related to service placement, allowing the Edge nodes to cooperate among themselves to select the location in which service instances should be deployed in order to improve different metrics such as latency or energy consumption.

This work focuses on applying ML techniques to allow cooperation among Edge nodes, enabling a distributed solution for service placement in the Cloud-to-Edge continuum. The work will be developed using simulation tools such as YAFS (https://github.com/acsicuib/YAFS) and MobFogSim (https://github.com/diogomg/MobFogSim).

The work comprises the interaction of an international team, being supervised by researchers from the Laboratory of Communications and Telematics (LCT) in the Centre for Informatics and Systems of the University of Coimbra (CISUC), Portugal, and from the Institute of Computing (IC) from the University of Campinas (UNICAMP), Brazil.

Objetivo

The work consists of designing and developing an ML-based solution for service placement for the Cloud-to-Edge continuum.

Plano de Trabalhos - Semestre 1

Phase 1: Study of the state-of-the-art on Cloud-to-Edge environments

Phase 2: Review of ML techniques for distributed environments such as the Cloud-to-Edge

Phase 3: Familiarization with the simulation environment chosen

Phase 4: Service requirement and network resource definition

Phase 5: Prepare midterm defense document

Plano de Trabalhos - Semestre 2

Phase 7: Implement a baseline service placement mechanism based on ML using the simulator chosen

Phase 8: Implement a second service placement mechanism based on ML using the simulator chosen

Phase 9: Validate the mechanisms and analyze their results

Phase 10: Prepare the dissertation document

Condições

The work will be performed in the LCT Laboratory (Departamento de Engenharia Informática, Universidade de Coimbra, Portugal), in close collaboration with researchers from the Institute of Computing (University of Campinas, Brazil).

Observações

There is the possibility of awarding the internship with a scholarship, according to the candidate’s profile.

This work will be co-supervised by Prof. Nuno Lourenço (DEI-UC, Portugal) and Prof. Luiz Bittencourt (IC-UNICAMP, Brazil).

Orientador

Karima Velasquez
kcastro@dei.uc.pt 📩