Distributed averaging describes a class of network algorithms for the decentralized
computation of aggregate statistics. Initially, each node has a scalar data value, and the goal …

This paper proposes an approach to accelerate local, linear iterative network algorithms
asymptotically achieving distributed average consensus. We focus on the class of algorithms …

In this paper, we develop algorithms for distributed computation of averages of the node
data over networks with bandwidth/power constraints or large volumes of data. Distributed …

This thesis is concerned with distributed control and coordination of networks consisting of
multiple, potentially mobile, agents. This is motivated mainly by the emergence of large …

In the past few years, the problem of distributed consensus has received a lot of attention,
particularly in the framework of ad hoc sensor networks. Most methods proposed in the …

This paper focuses on the consensus averaging problem on graphs under general imperfect
communications. We study a particular class of distributed consensus algorithms based on …

Distributed averaging problems are a subclass of distributed consensus problems, which
have received substantial attention from several research communities. Although many of …

Recently there has been a significant amount of research on developing consensus based
algorithms for distributed optimization motivated by applications that vary from large scale …

Distributed consensus algorithms have recently gained large interest in sensor networks as
a way to achieve globally optimal decisions in a totally decentralized way, that is, without the …

We consider a discrete-time distributed averaging algorithm over multi-agent networks with
measurement noises and time-varying random graphs. Each agent updates its state by a …