Distributed Push–pull Estimation for node localization in wireless sensor networks

A great deal of research achievements on localization in wireless sensor networks (WSNs) has been obtained in recent years. Nevertheless, its interesting challenges in terms of cost-reduction, accuracy improvement, scalability, and distributed ability design have led to the development of a new algorithm, the Push–pull Estimation (PPE). In this algorithm, the differences between measurements and current calculated distances are modeled into forces, dragging the nodes close to their actual positions. Based on very few known-location sensors or beacons, PPE can pervasively estimate the coordinates of many unknown-location sensors. Each unknown-location sensor, with given pair-wise distances, could independently estimate its own position through remarkably uncomplicated calculations. Characteristics of the algorithm are examined through analyses and simulations to demonstrate that it has advantages over those of previous works in dealing with the above challenges.

Research highlights
► Push–pull Estimation (PPE) models the errors between measurements and current calculated distances into forces to ‘move’ the nodes to their better estimated positions.
► PPE is a robust distributed algorithm with low-cost communication and computation.
► PPE can deal with any noise model as long as the measurement is unbiased or a de-biasing function is found.
► PPE gives better performance than that of previous works especially when the measurement error is proportional to the real distance.