Clustered Spanning Tree for Integrated Energy Efficient Routing and Optimized Data Collection in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) comprises of sensor nodes performing the function of event detection in a distributed network. With the sensor nodes being heavily energy-constrained, energy efficient routing is highly required. To facilitate energy consumption and reduce end-to-end delay in a sensor network, joint scheduling of tasks and messages has been widely used. However, dynamic routing was compromised. Research works conducted using multi-path dynamic routing reduced data loss and ensured data integrity, but efficient data collection at the sink node received less attention. In this paper, an integrated framework called, Cluster based Routing and Data Collection using Spanning Tree (CR-DCST) is designed to improve the routing efficiency and data collection at the sink node. We first formulate a Cluster based Routing, that uses a dynamic routing to select the cluster head (i.e., efficient route), aiming at reducing the energy consumption of the nodes. The Cluster based Routing uses a neighbor routing table to reduce the end-to-end delay. Then, a Spanning Tree framework based on dynamic routing for efficient data collection at the sink node is performed to improve the throughput of data being collected at the sink node. The Spanning Tree framework for efficient data collection is performed on the basis of constructing the Least Interference Tree (LIT). Finally, Energy Efficient Cluster based Spanning Tree (EECST) algorithm reduces the data loss in Wireless Sensor Networks. The effectiveness of the proposed framework using extensive experimental measurements demonstrated using NS2 confirms reducing the energy consumption and average end-to-end delay. Simulations are also conducted to validate the theoretical results in different test bed settings and show that the proposed framework can substantially improve the throughput and reduce the data loss at sink node during data collection in most scenarios.