Asynchronous broadcast-based convex optimization over a network

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211 Scopus citations


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
Issue number6
StatePublished - Jun 2011
Externally publishedYes


  • 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


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