Wireless sensor networks (WSNs) utilize a network of small sensor nodes to collect, process, and report observed data back to a central location. A multi-trust paradigm based on hierarchical clustering is implemented in the WSN network to address these concerns. This model is to calculate the trust value for carrying out the safe transmission between the huge sensor nodes that make up the network. In this case, energy trust, communication trust, and data trust all contribute to the multi-trust process. This multi-trust is then compared to a threshold value, if it is more than the threshold, the corresponding node is disregarded or eliminated. It tends to establish multi-level clustering for security enhancement because of the increased multi-trusting. Modified exploration-based pelican optimization algorithm (ME-POA) is used to obtain the most important feature of CH. Finally, the performance is evaluated using multi-objective functions, with distance, latency, energy, and multi-trust serving as the parameters.
TopIntroduction
The Internet of Things (IoT) development and the incorporation of sensors into various intelligent devices are employed in WSN technology to connect the physical world of humans with the virtual world of electronics (Qiu et al., 2019). In order to monitor environmental conditions including noise, mobility, temperature, and vibration, WSNs are a special type of ad hoc network. WSNs have been widely used in numerous applications, such as combat monitoring, healthcare, and environmental monitoring, because of their rapid deployment, simplicity of usage, and reduced costs. Numerous research obstacles are presented by WSNs (Aoyang Zhao et al., 2020), including hardware constraints, coverage gaps, fault tolerance, energy consumption, and localization (Heinzelman.et.al, 2017). When it comes to problems that have yet to be solved, security ranks at the top (Sajjad et al., 2018). The sensor nodes are correctly planned in the clustering approach, which can lower the nodes' power consumption because sensor nodes have limited battery life (Guangjie et al., 2019). Reduced routing delay, balanced loads, improved connections, combined data, scalable resources, robustness in the face of failure, and a more stable topology are all potential gains from a clustered architecture (Fang et al., 2019).
Many clustering strategies used in WSNs are algorithm-specific and so fall under either the deterministic or probabilistic system categories (Sakthidevi et al., 2017). Although the current approaches frequently presume an established clustering architecture before selecting a trustworthy CH . Thus, the most trustworthy nodes must be chosen as the CH before any security model can be used. Clustering the sensor nodes and sending them to the sink node is optional in WSN (Sun et al., 2022). Directly connecting CHs to the washbasin results in higher energy usage, but this issue may be solved without resorting to a routing mechanism because it is unaffected by the overheads of such a system (Prakasam et al., 2020). By working together in different-hop routing, CHs can reduce energy consumption and extend the WSN's useful life. When looking for a trustworthy CH, safety and efficiency are the two most important criteria to consider. The election process is one of the few places where ineffective clustering solutions consider security concerns, such as reputation and trust, while successful cluster systems channel simply energy (Junnarkar et al., 2017).