Trust management for service composition in SOA-based IoT systems

An Internet of Things (IoT) system connects a large amount of tags, sensors, and smart devices often with mobility to facilitate information sharing, enabling a variety of attractive applications. On the one hand, the service oriented architecture (SOA) can provide connectivity and interoperability among heterogeneous IoT devices in the physical network. On the other hand, IoT devices are virtually connected via social networks. In this paper, we analyze the notion of adaptive trust management to support reliable service composition applications in SOA-based IoT systems. Each device records user satisfaction experiences toward devices with which it has interacted, and collects trust feedbacks from other devices sharing social interests. We consider friendship, social contact, and community of interest social relationships to select trust feedbacks. Further we develop a novel adaptive filtering technique to determine the best way to combine direct trust and indirect trust feedbacks dynamically to minimize both convergence time and trust bias. We demonstrate the effectiveness of the proposed trust management through a service composition application in SOA-based IoT systems.