Predictable edge resource management
Title: |
Predictable edge resource management |
DNr: |
SNIC 2021/5-233 |
Project Type: |
SNIC Medium Compute |
Principal Investigator: |
György Dán <gyuri@kth.se> |
Affiliation: |
Kungliga Tekniska högskolan |
Duration: |
2021-05-01 – 2022-05-01 |
Classification: |
20204 |
Homepage: |
https://www.tecosa.center.kth.se/ |
Keywords: |
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Abstract
The project investigates algorithmic solutions for managing computational and communication resources in multi-access edge computing. In this context our focus is on game theoretical models and approaches to developing scalable algorithms for resource management, evaluating models of learning and adaptation in a multi-agent setting. Our expected results give insight in the interaction between strategic user behavior and strategic behavior of a network operator, and allow to define scalable adaptive policies for resource management.