MHM-RTC: Multi-Hop Mobility-Based Real-Time Clustering Algorithm for Wide-Area Wireless Sensor Network

Internet of Things (IoT) and wireless sensor networks (WSN) have significant potential for a wide range of applications. However, these methods are hindered by resource constraints, long-range connectivity and energy challenges. Existing clustering protocols attempt to address some of these problems but fall short when handling the demands of real-time mobility in large-scale WSNs. Many of these algorithms rely on high processing power and offline optimization and fail to account for the dynamic mobility of nodes within the network. This article introduces the Multi-hop Mobility-based Real-Time Clustering (MHM-RTC) algorithm, which utilizes long-range (LoRa) communication between mobile sensor nodes (SNs) and a mobile data sink (DS). Unlike traditional approaches, this algorithm enables dynamic, on-the-fly clustering through the active participation of both SNs and DS. It adapts to continuous topology changes in highly mobile environments, supporting real-time responsiveness and efficient wide-area WSN coverage. The algorithm includes a mathematical model to calculate the clustering time across various network sizes, focusing on energy optimization and extended coverage in mobile networks. The simulation results demonstrate significant improvements over existing mobility-supporting algorithms, such as the Energy Efficient Routing Algorithm (EERA), Energy-Efficient Mobility-Based Cluster Head Selection (EEMCS) and Lightweight Dynamic Clustering Algorithm (LDCA). Specifically, MHM-RTC reduced the clustering time by up to 20%, increased the sensor node coverage by 37-53%, and reduced the average residual energy consumption by 3.77–8.69% when the total number of sensor nodes varied from 100 to 250. These results highlight that MHM-RTC is an effective solution for real-time energy-efficient clustering in large-scale mobile sensor networks.