A trust model mechanism based on quality of service to reduce energy consumption in the internet of things network - Hikmat, Ameer Nadhum (2022)
The Internet of Things (IoT) is a network of connected devices that have emerged as a promising technology to handle small network-based devices. In recent years, adoption of this relatively new technology has grown immensely. The energy consumption for IoT devices is regarded as one of the most critical factors affecting IoT networks’ lifespan. Quality of Service (QoS) is considered one of the leading research concerns in IoT networks. Communication between IoT devices needs a suitable and reliable service model to meet the requirements of IoT applications to handle the levels of QoS and maximize network lifespans. Therefore, this study aims to propose a trust model mechanism to provide different levels of QoS (QoST-IoT) and maximize IoT network lifespans. The QoS trust model includes four main steps. The first step is trust level calculation, which is calculated for each of the IoT nodes to find the trust level. Then, in the second step, query trust, the IoT node sends the trust values of various components to the cluster head (CH). The third step involves the clustering of the IoT nodes. Subsequently, the fourth step deals with the trust level update. The experiments conducted in this study revealed that the proposed QoS trust model mechanism (QoST-IoT) reduced the energy consumption compared to the trust model mechanisms previously proposed in the literature. The results of the first simulation round showed that the QoST-IoT outperformed the security & trusted devices in the context of IoT (STD-IoT) by 41.2%, trust-based adaptive security in IoT (TAS-IoT) by 43.7%, and the context-aware and multiservice approach in IoT (Context-IoT) by 45.2%. In addition, the second simulation round showed that the QoST-IoT consumed less energy than STD-IoT by 47.5%, TAS-IoT by 50.5%, and Context-IoT by 53.8%. The findings of this study extend the understanding of designing a QoS trust model with energy consumption reduction for IoT networks, which could be beneficial for researchers, IoT developers, and policymakers.