Asynchronous Corona Training Protocols in Wireless Sensor and Actor Networks

Scalable energy-efficient training protocols are proposed for wireless networks consisting of sensors and a single actor, where the sensors are initially anonymous and unaware of their location. The protocols are based on an intuitive coordinate system imposed onto the deployment area, which partitions the sensors into clusters. The protocols are asynchronous, in the sense that the sensors wake up for the first time at random, then alternate between sleep and awake periods both of fixed length, and no explicit synchronization is performed between them and the actor. Theoretical properties are stated under which the training of all the sensors is possible. Moreover, both worst-case and average case analyses of the performance, as well as an experimental evaluation, are presented showing that the protocols are lightweight and flexible.