  Simulated annealing (SA) method has had significant recent success in
designing distributed control algorithms for wireless networks. These SA based
techniques formed the basis of new CSMA algorithms and gave rise to the
development of numerous variants to achieve the best system performance
accommodating different communication technologies and more realistic system
conditions. However, these algorithms do not readily extend to networks with
noisy environments, as unreliable communication prevents them from gathering
the necessary system state information needed to execute the algorithm. In
recognition of this challenge, we propose a new SA algorithm that is designed
to work more robustly in networks with communications that experience frequent
message drops. The main idea of the proposed algorithm is a novel coupling
technique that takes into account the external randomness of message passing
failure events as a part of probabilistic uncertainty inherent in stochastic
acceptance criterion of SA. As a result, the algorithm can be executed even
with partial observation of system states, which was not possible under the
traditional SA approach. We show that the newly proposed algorithm finds the
optimal solution almost surely under the standard annealing framework while
offering significant performance benefits in terms of its computational speed
in the presence of frequent message drops.
