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:

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.