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This paper investigates the problem of distributed network-wide averaging andproposes a new greedy gossip algorithm. Instead of finding the optimal path ofeach node in a greedy manner, the proposed approach utilises a suboptimalcommunication path by performing greedy selection among randomly selectedactive local nodes. Theoretical analysis on convergence speed is also performedto investigate the characteristics of the proposed algorithm. The main featureof the new algorithm is that it provides great flexibility and well balancebetween communication cost and convergence performance introduced by thestochastic sampling strategy. Extensive numerical simulations are performed tovalidate the analytic findings.

Sample Greedy Gossip for Distributed Network-Wide Average Computation