  This paper investigates the problem of distributed network-wide averaging and
proposes a new greedy gossip algorithm. Instead of finding the optimal path of
each node in a greedy manner, the proposed approach utilises a suboptimal
communication path by performing greedy selection among randomly selected
active local nodes. Theoretical analysis on convergence speed is also performed
to investigate the characteristics of the proposed algorithm. The main feature
of the new algorithm is that it provides great flexibility and well balance
between communication cost and convergence performance introduced by the
stochastic sampling strategy. Extensive numerical simulations are performed to
validate the analytic findings.
