High Altitude Platform Station-Greedy Clustering of Wireless Sensor Networks for the Massive IoT
Anastassia Gharib · 2024
Wireless sensor networks (WSNs) play an important role in the Internet of Things (IoT). These are networks of sensor nodes that are clustered to collect and exchange locally sensed data. In each cluster, a cluster head (CH) gathers data from its cluster members, aggregates it, and sends it to the sink node. To serve IoT applications, the sink node then shares this data with the other CHs. Nevertheless, clustering a massive collection of sensor nodes is challenging. This is because these sensor nodes have limited energy resources and are distributed over a vast area. Recently, High Altitude Platform Stations (HAPS) have been shown to improve the connectivity in WSNs by serving as non-terrestrial sink nodes. The quasi-stationary nature of these non-terrestrial platforms can offer vast geographical coverage, and thus, improve WSNs' transmission reliability. This paper proposes HAPS-greedy clustering (HAPS-GC) of WSNs to support massive IoT applications. In contrast to existing HAPSbased WSN clustering schemes, HAPS-GC considers not only the connectivity between sensor nodes within each cluster but also their connectivity with HAPS. Simulation results show that the proposed HAPS-GC approach can significantly increase the WSN throughput while maintaining WSN energy consumption similar to the existing HAPS-based WSN clustering schemes and a scenario, where a terrestrial sink node is used.