Date Added: Sep 2011
Consensus algorithms can be used to compute an average value across a multi-hop network in a distributed way. However, their convergence to the right value is not guaranteed in the presence of random packet losses that are common in real life low-power wireless networks. Corrective consensus solves this problem by using a set of auxiliary variables to compensate for the asymmetric state updates caused by packet losses. Nevertheless, one key assumption is that the probability of delivering a packet from node i to a neighboring node j is the same as in the reverse direction, from j to i. This assumption might be violated in real life conditions. The authors' main contribution is showing that corrective consensus converges to the correct average even when this assumption is removed.