Dynamic and Scalable Routing to Perform Efficient Data Aggregation in WSNs

Abstract

Data aggregation is one of the main methods to conserve energy in wireless sensor networks (WSN). Redundant data can be aggregated at intermediate nodes of a WSN reducing the number of messages exchanged and, consequently, reducing communication costs. Most data aggregation protocols are generally based on a static routing scheme. Although those protocols can save energy by eliminating data redundancy, in dynamic scenarios, they can incur in high overhead to reconstruct the routing tree. In this work we consider the problem of constructing a dynamic and scalable structure for data aggregation in WSNs. To tackle these challenges we propose a novel routing protocol called Dynamic and Scalable Tree (DST), which can adapt to different scenarios without incurring the overhead of the other methods. DST maximizes the number of overlapping routes and selects routes with the highest aggregation rate. DST was extensively compared with two solutions reported in the literature regarding communication costs, aggregation rate efficiency and quality of the routing tree. Simulation results show that the routing tree built by DST provides the best efficiency compared with other algorithms outperforming them for different scenarios in all evaluations performed.