Efficient Tree Aggregation and Processing Time for Wireless Sensor Networks

Tree-based data aggregation suffers from increased data delivery time because the parents must wait for the data from their leaves. In this paper, we propose an Efficient Tree-based Aggregation and Processing Time (ETAPT) algorithm using Appropriate Data Aggregation and Processing Time (ADAPT) metric. A tree structure is built out from the sink, electing sensors having the highest degree of connectivity as parents; others are considered as leaves. Given the maximum acceptable latency, ETAPT’s algorithm takes into account the position of parents, their number of leaves and the depth of the tree, in order to compute an optimal ADAPT time to parents with more leaves, so increasing data aggregation gain and ensuring enough time to process data from leaves. Simulations were performed in order to validate our ETAPT. The results obtained show that our ETAPT provides a higher data aggregation gain, with lower energy consumed and end-to-end delay compared to Aggregation Time Control (ATC) and Data Aggregation Supported by Dynamic Routing (DASDR).