Asynchronous broadcast-based convex optimization over a network

Angelia Nedić

Research output: Contribution to journalArticle

Abstract

We consider a distributed multi-agent network system where each agent has its own convex objective function, which can be evaluated with stochastic errors. The problem consists of minimizing the sum of the agent functions over a commonly known constraint set, but without a central coordinator and without agents sharing the explicit form of their objectives. We propose an asynchronous broadcast-based algorithm where the communications over the network are subject to random link failures. We investigate the convergence properties of the algorithm for a diminishing (random) stepsize and a constant stepsize, where each agent chooses its own stepsize independently of the other agents. Under some standard conditions on the gradient errors, we establish almost sure convergence of the method to an optimal point for diminishing stepsize. For constant stepsize, we establish some error bounds on the expected distance from the optimal point and the expected function value. We also provide numerical results.

Original languageEnglish (US)
Article number5585721
Pages (from-to)1337-1351
Number of pages15
JournalIEEE Transactions on Automatic Control
Volume56
Issue number6
DOIs
StatePublished - Jun 1 2011

Keywords

  • Asynchronous algorithms
  • convex optimization
  • distributed multi-agent system
  • random broadcast network

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Electrical and Electronic Engineering

Fingerprint Dive into the research topics of 'Asynchronous broadcast-based convex optimization over a network'. Together they form a unique fingerprint.

  • Cite this