A distributed algorithm for building approximate MSTs in random-distributed WSNs

In this work the authors propose a distributed algorithm for building approximate Minimum Spanning Trees (MSTs) for energy-efficient gathering and aggregation of sensed data in randomly-distributed, multi-hops, wireless sensor networks (WSNs). The MST created, obtained through global organization based on local interactions among each sensor and its neighbors, exploits an innovative joining mechanism that guarantees, at the same time, the creation of a near-optimal energy-efficient MST and the avoidance of cycles. The led simulations have demonstrated that the proposed solution gives, in terms of expected quality of built trees, better performance then the UDG-Nearest Neighbor Algorithm (UDG-NNT) that is, currently, the best known solution for building approximate, energy-efficient, MSTs in multi-hop WSNs.