A secure multi-hop routing algorithm based-on fuzzy logic for IoT communication - Fu, Tao; Han, Guoxin; Qin, Xuming; Li, Jinfang; Lin, Weiting (Engineering science and technology, an international journal, 2025)
•Comprehensive assessment of operational impact of low carbon dwellings on local power infrastructure.•7 low-carbon homes with ASHP and PV constructed meeting UK’s Future Homes Standard are analysed.•Peak demand about 1/3 of the maximum power capacity of each dwelling.•Electricity consumption largely driven by occupancy behaviour.•Importance of diversity-based power network planning over theoretical capacity estimates. The fast growth of the Internet of Things (IoT) into mission-critical applications requires secure and efficient routing protocols. Nevertheless, the resource limitations of IoT devices and their susceptibility to attacks require smart, dynamic solutions. To overcome these challenges, this paper introduces a new, safe, multi-hop routing algorithm that combines the use of fuzzy logic and reinforcement learning. We initially build a high-performance communication backbone over a Connected Dominating Set (CDS) to reduce network overhead. A fuzzy inference system then intelligently considers the possible paths using path energy, distance, and node credibility to choose the best path to transmit the data. A Q-learning model is used to dynamically evaluate the reliability of each node to provide security, and to identify and isolate malicious actors. Our algorithm is shown to be better in experimental results, with the ability to increase the ratio of packet delivery by up to 2.4 percent and at the same time lower the average energy consumption by about 6.53 percent of the current state-of-the-art protocols. These results demonstrate that our hybrid solution has a great potential to improve the reliability and safety of data routing in contemporary IoT networks.