Enhancing Service Discovery in Mobile Ad Hoc Networks Using Semantic Clustering and Hybrid Trust Management

Mobile Ad Hoc Networks (MANETs) facilitate communication among mobile devices without relying on fixed infrastructure. However, service discovery in MANETs faces challenges due to the dynamic topology and limited resources of nodes. Existing solutions often lack efficient resource utilization and fail to address trust management adequately. The conventional approaches for service discovery in MANETs are inefficient due to their inability to incorporate semantic clustering and robust trust management. Semantic clustering enhances the accuracy of service discovery by grouping nodes based on similar interests or functionalities. Meanwhile, traditional trust management mechanisms are inadequate in dynamic environments, leading to unreliable service discovery results. The proposed methodology involves developing a semantic clustering algorithm to organize nodes based on their semantic similarities. Additionally, a hybrid trust management system is implemented to assess the reliability of discovered services. The system combines both reputation-based and recommendation-based trust models to enhance the accuracy of trust evaluations. Through extensive simulations and experiments, the effectiveness of the proposed approach is demonstrated. The results indicate that the integration of semantic clustering and hybrid trust management significantly improves service discovery efficiency and reliability in MANETs. The approach achieves higher precision and recall rates compared to conventional methods, even under dynamic network conditions.