###### Abstract  
The emergence of Internet of Things (IoT)-based heterogeneous wireless sensor network (HWSN) technology has become widespread, playing a significant role in the development of diverse human-centric applications. The role of efficient resource utilisation, particularly energy, becomes further critical in IoT-based HWSNs than it was in WSNs. Researchers have proposed numerous approaches to either increase the provisioned resources on network devices or to achieve efficient utilisation of these resources during network operations. The application of a vast proportion of such methods is either limited to homogeneous networks or to a single parameter and limited-level heterogeneity. In this work, we propose a multi-parameter and multi-level heterogeneity model along with a cluster-head rotation method that balances energy and maximizes lifetime. This method achieves up to a 57% increase in throughput to the base station, owing to improved intra-cluster communication in the IoT-based HWSN. Furthermore, for inter-cluster communication, a mathematical framework is proposed that first assesses whether the single-hop or multi-hop inter-cluster communication is more energy efficient, and then computes the region where the next energy-efficient hop should occur. Finally, a relay-role rotation method is proposed among the potential next-hop nodes. Results confirm that the proposed methods achieve 57.44%, 51.75%, and 17.63% increase in throughput of the IoT-based HWSN as compared to RLEACH, CRPFCM, and EERPMS, respectively. Internet of Things; heterogeneous wireless sensor network; energy balanced routing; hierarchical routing; energy consumption rate; network lifetime; hot spot; energy holes; cluster-head rotation; relay-node rotation +
Footnote †: journal: Sensors  
0024 24 5642 2 various applications does not require a significant paradigm shift [7]. Figure 1 illustrates the overall infrastructure of a WSN-based IoT system. Various sensors with heterogeneous attributes collect real-time environmental data, which is then communicated to a base station using clustered hierarchical routing [15]. The real-time data are made accessible through the IoT cloud, enabling coordinated service delivery in modern infrastructures like smart cities [16]. Although WSN-based IoT systems are appealing because they can operate independently in harsh environments where human presence is impractical [6], these environments also pose challenges to network longevity [17] due to the inability to replace or recharge their limited batteries [18]. Moreover, in hierarchical routing, cluster heads closer to the base station experience excessive relaying loads, leading to their premature failure [15]. Scalable and adaptable energy-efficient routing schemes are a crucial quality of service (QoS) criterion in networks with large-scale device deployment [15]. Moreover, IoT-based WSNs can include sensor nodes with a wide range of capabilities, introducing a more complex variant known as IoT-based HWSN [19]. Figure 2 illustrates an m-level heterogeneous wireless sensor network, where diverse sensor nodes transmit information about the field to the base station (BS), which stores the data in a central repository. Authorised end-users with the appropriate credentials can access any required data from this repository via the internet. The term'm-level' refers to the varying functionalities and corresponding range of resources that a device can possess, such as sensing ranges, sensing tasks, mobility levels, initial energy supplies, and computational capabilities, among others [19]. Figure 1: HWSN-based IoT infrastructure. Figure 2: Multi-parameter and multi-level heterogeneous wireless sensor network. Deploying sensor nodes with diverse functionalities and capabilities results in cost-effective solutions and improved performance. This makes the HWSN-based IoT a more practical alternative to traditional WSN-based IoT systems.