Abstract
In recent years, clustering has emerged as a promising approach to facilitate data routing and data aggregation in Wireless Sensor Network (WSN). Although clustering based routing approaches are appropriate for small-scale networks, they do not fit large scale WSNs as it is the case in LEACH [1]. Indeed, clustering suffers from the adverse effects of isolated nodes in the network and some coverage problems. To deal with these issues, we present LEATCH-L, a Low Energy Adaptive Tier Clustering Hierarchy for Large scale WSNs. The proposed approach makes the major functions of LEACH applicable to large-scale WSNs whose dimension is much larger than the largest transmission radius of the sensor nodes. The latter imposes a dynamic decomposable structure on the network topology which results in a set of smaller subnetworks. Such decompositions are implemented through a smart m-level hierarchical clustering process. Moreover, the proposed approach involves a two level data aggregation. Evaluation results show that the introduced approach is scalable with significantly much better performance than the state-of-the art approaches.