Titulo Estágio
Smart service migration in Cloud-to-Edge environments
Áreas de especialidade
Engenharia de Software
Comunicações, Serviços e Infraestruturas
Local do Estágio
Laboratory of Communications and Telematics (LCT – DEI – UC)
Enquadramento
This master thesis is framed within the scope of the ANI-Portugal 2020 POWER project (https://www.cisuc.uc.pt/en/projects/power).
The thesis will address relevant and currently trendy research topics in the field of 5G networks, Edge/Cloud computing continuum, data-driven technologies, and artificial intelligence, and working with a collaborative team including members from IPN, UC, and Altice Labs. The main goal is to design and develop mechanisms for service migration in the Cloud-to-Edge continuum.
Objetivo
The work will consist of developing intelligent migration mechanisms to be deployed in a controlled testbed for the Cloud-to-Edge continuum. The mechanisms might be pre-existing or newly designed, and must implement heuristics for the migration process at the Edge level in the network infrastructure.
Plano de Trabalhos - Semestre 1
Phase 1: Study of the state-of-the-art on service migration using heuristics based on ML techniques (e.g., federated learning) or other techniques (e.g., particle swarms optimisation, genetic algorithm) applied in Edge (15/09/2022 – 15/10/2022)
Phase 2: Identify the service requirements that need to be supported by the migration framework (16/10/2022 – 31/10/2022)
Phase 3: Identify the techniques and metrics to use in the migration algorithm, considering the requirements previously identified (01/11/2022 – 08/11/2022)
Phase 4: Select and implement a baseline migration algorithm from the SoA (e.g., greedy algorithm) (09/11/2022 – 07/12/2022)
Phase 5: Evaluate and tune the baseline migration algorithm, considering a use-case framed in the POWER context (08/12/2022 – 01/01/2023)
Phase 6: Prepare midterm defence document (15/11/2022 - 15/01/2023)
Plano de Trabalhos - Semestre 2
Phase 7: Implement a migration mechanism based on heuristics (ML or other optimisation techniques) (02/02/2023 - 15/03/2023)
Phase 8: Implement a second migration mechanism based on heuristics (ML or other optimisation techniques) (16/03/2023 - 30/04/2023)
Phase 9: Evaluate and compare the performance of the two mechanisms against the baseline implemented in Phase 4 (01/05/2023 - 31/05/2023)
Phase 10: Apply the migration mechanisms based on a use-case within the context of the POWER project (01/06/2023 - 15/06/2023)
Phase 11: Prepare the dissertation document (01/04/2023 - 30/06/2023)
Condições
The work will be performed in the LCT Laboratory (Departamento de Engenharia Informática, Universidade de Coimbra), in close collaboration between the research teams from other laboratories from CISUC (SSE, ECOS) and from Altice Labs.
Observações
There is the possibility to award the internship with a scholarship, according to the candidate’s profile.
The work will be supervised by: Prof. Karima Velasquez (kcastro@dei.uc.pt)
The work will be co-supervised by: Prof. Bruno Cabral (bcabral@dei.uc.pt)
Orientador
Karima Velasquez : co-orientador Bruno Cabral
kcastro@dei.uc.pt 📩