text: In this article, we establish orientation and connectivity based criteria for the agreement algorithm to achieve asymptotic consensus in the context of time-varying topology and communication delays. These criteria unify and extend many earlier convergence results on the agreement algorithm for deterministic and discrete-time multiagent systems.
  @cite_17: This paper gives a lower bound on the convergence rate of a class of network consensus algorithms. Two different approaches using directed graphs as a main tool are introduced: one is to compute the "scrambling constants" of stochastic matrices associated with "neighbor shared graphs" and the other is to analyze random walks on a sequence of graphs. Both approaches prove that the time to reach consensus within a dynamic network is logarithmic in the relative error and is in worst case exponential in the size of the network.
summary: @cite_17 proved that in the case of stochastic matrices with equal positive entries in each row (usually referred to as the equal neighbor model ,), and under assumptions A and B with @math , the agreement algorithm achieves asymptotic consensus when all the communication graphs are oriented. Their convergence result thus coincides with Theorem in the particular case of a synchronous multiagent system and with the equal neighbor model.