Exploiting Node Memory for Finite-time Average Consensus over WSNs

Consensus among different entities is a fundamental feature of distributed systems, as it is the prerequisite for complex tasks such as distributed coordination of autonomous agents, network synchronization and localization in wireless sensor networks (WSNs). This paper introduces a novel iterative algorithm which is capable of achieving the distributed average consensus in a finite amount of time. This algorithm exploits the possibility of storing information received from neighboring nodes at each iteration. Moreover, we propose an adaptation to the distributed average consensus problem of the Tagged and Aggregated Sums (TAS) algorithm, which we introduced in a previous paper for the distributed confidence region evaluation. The performance of both algorithms is investigated through simulation and compared with state-of-the-art approaches.