An Adaptive Spanning Tree-Based Data Collection Scheme in Wireless Sensor Networks

Abstract

In-network data aggregation is a widely used method for collecting data efficiently in wireless sensor networks (WSNs). The authors focus on how to achieve high aggregation efficiency and prolonging networks’ lifetime. Firstly, this paper proposes an adaptive spanning tree algorithm (AST), which can adaptively build and adjust an aggregation spanning tree. Owing to the strategies of random waiting and alternative father nodes, AST can achieve a relatively balanced spanning tree and flexible tree adjustment. Then a redundant aggregation scheme (RAG) is illustrated. In RAG, interior nodes help to forward data for their sibling nodes and thus provide reliable data transmission for WSN. Finally, the simulations demonstrate that (1) AST can prolong the lifetime and (2) RAG makes a better trade-off between storage and aggregation ratio, comparing to other aggregation schemes.