MESA: A formal approach to compute consensus in WSNs

Abstract

Consensus algorithms are implemented over Wireless Sensor Networks (WSN) for computing a distributed variable measurement or performing Data Fusion (DF). In a previous work the main idea of the MESA algorithm presented, but with no mathematical formalization. The MESA approach is a novel consensus algorithm that implements the transmission censoring technique aiming to reduce the energy used for reaching consensus. Moreover, it makes use of neighborhood data, which allows it to perform estimations over unknown distributed variables. This condition renders the proposed approach more efficient than the existing censoring techniques found in the literature. In this article a formalization of the MESA algorithm over cluster based WSN is presented. It is addressed from the statistical point of view of the algorithm, which gives us a better understanding of the consequences of transmission censoring and leads us to predict the results of its utilization.