Dynamic Balanced Spanning Tree (DBST) for data aggregation in Wireless Sensor Networks

Data gathering is one of the most popular energy-efficient routing protocols in Wireless Sensor Networks (WSNs). In this research, we introduce a Dynamic Balanced Spanning Tree (DBST) for data aggregation in WSNs which considers several criteria to balance the energy consumption between sensor nodes. A cost function is presented which can follow the conditions of network. It considers various factors such as distance, residual energy, and node weight and also controls the trade-off between these factors. DBST not only minimizes the maximum energy consumption among the sensor nodes, but also can balance the traffic load in the network by dynamic design of the routing tree. DBST is equipped with a root selection mechanism which only needs localized information and considers both distance and residual energy criteria. In this way, the role of the root is distributed among the nods fairly. Furthermore, it guarantees that critical nodes are not selected as root node. DBST also uses a discrete first order radio model which is adaptable to the limitation of Sensor hardware platforms. Our extensive experiments demonstrate efficiency of the proposed DBST in balancing the traffic loads in the network.