On the Construction of Data Aggregation Tree with Maximizing Lifetime in Large-Scale Wireless Sensor Networks

Data aggregation protocols are generally utilized to extend the lifetime of sensor networks by reducing the communication cost. Traditionally, tree-based structured approaches that are a basic operation for the sink to periodically collect reports from all sensors were concerned about many applications. Since the data aggregation process usually proceeds for many rounds, it is important to collect these data efficiently, that is, to reduce the energy cost of data transmission. Under such applications, a tree is usually adopted as the routing structure to save the computation costs when maintaining the routing tables of sensors. In our previous work, we have demonstrated that multiple trees, as well as split trees, can provide additional lifetime extensions when certain nodes are deployed in a wireless sensor network. In this paper, we explore how the number of the family-set of trees influences the lifetime gain, and we work on the problem of constructing data aggregation trees that minimizes the total energy cost of data transmission under diverse set of scenarios and network query region. Through dividing query area, the sensory and aggregation data have been returned through a number of different forwarding trees within each sub query area, which reduces the network hot spots. To evaluate the performance of the proposed approach, we have compared and analyzed an angular division routing algorithm and query region division routing with LEACH. Theoretical and experimental results illustrate that the query region division algorithm based on angle leads to lower energy cost in comparison with the models reported in the literature.