Consensus on the Average on Arbitrary Strongly Connected Digraphs Based on Broadcast Gossip Algorithms

—In this paper we propose a new decentralized algorithm to solve the consensus on the average problem on arbitrary strongly connected digraphs through a gossip algorithm based on broadcasts. We directly extend previous results by not requiring that the digraph is balanced. Our algorithm is an improvement respect to known gossip algorithms based on broadcasts in that the average of the initial state is preserved after each broadcast. The nodes are assumed to know their out-degree anytime they transmit information. The algorithm convergence analysis is preliminary and performance is shown by simulations.