Service Recommendation Model Based on Trust and QoS for Social Internet of Things
Shaozhong Zhang, Dingkai Zhang, Yaohui Wu, Haidong Zhong
Abstract
The Social Internet of Things (SIoT) is a novel network that integrates social relations among objects and facilitates the interconnection between humans and smart devices through the Internet of Things (IoT). However, with the growing number of users and their devices in SIoT, ensuring high quality of service (QoS) and trust relations among users poses significant challenges. Therefore, this article proposes a SIoT services recommendation model based on trust and QoS. Our model combines user trust relations and QoS prediction, including the availability, reliability, and efficiency of services. To achieve this, we propose a three-layer services recommendation model consisting of a social network layer, a devices layer, and a services layer. We suggest using direct trust and joint trust to accurately calculate users' trust relations. Additionally, we introduce an Levenberg-Marquardt (L-M) -based algorithm for social network users' trust community clustering and a Random Service System (RSS) -based algorithm for QoS prediction. Experimental results show that our proposed model effectively recommends services in SIoT that exhibit high trustworthiness and quality.