Federated Edge Network Utility Maximization for a Multi-Server System: Algorithm and Convergence

Nurullah Karakoc, Anna Scaglione, Martin Reisslein, Ruiyuan Wu

Research output: Contribution to journalArticlepeer-review

Abstract

We propose a novel Federated Edge Network Utility Maximization (FEdg-NUM) architecture for solving a large-scale distributed network utility maximization (NUM) problem. In FEdg-NUM, clients with private utilities communicate to a peer-to-peer network of edge servers. This represents a departure from the classical distributed NUM master-slave configuration and enables distributed computing harnessing local communications. Compared to a solution using cloud synchronization via Ring AllReduce, we prove that our federated edge computing model has shorter run-time in the presence of network congestion, thanks to its configuration and its ability to make progress in the presence of intermittent links. The paper studies its convergence and run-time performance both analytically and numerically, and illustrates several possible networking applications.

Original languageEnglish (US)
JournalIEEE/ACM Transactions on Networking
DOIs
StateAccepted/In press - 2022

Keywords

  • Computer architecture
  • Convergence
  • Decentralized
  • Edge computing
  • network resource allocation.
  • Optimization
  • Peer-to-peer computing
  • Resource management
  • Servers

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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