A Clustering-Based Data Collection Wireless Sensor Network Using Concurrent Transmission

This paper presents a clustering-based data collection protocol for wireless sensor networks. Constructive interference-based flooding presents a novel way to achieve global synchronization, yet its communication mechanism requires that each message’s transmission involves a flooding process across the whole network, which suffers from scalability problems, especially for a densely deployed network. Additionally, an increase in the number of transmitting nodes compromises concurrent transmission reliability. This work aims to tackle these problems from a clustering perspective. Firstly, we improved the time synchronization method proposed by constructive inference-based flooding to make it applicable to our protocol. Then, we designed a heuristic algorithm from the balance and connectivity viewpoints to carry out network clustering simultaneously during the data collection process. The prototype was implemented on Tmote Sky sensor nodes. Extensive simulations using the Contiki operating system and experiments on a deployed testbed have verified that the protocol can achieve almost 100% data collection with lower energy consumption.