LAUSR

Predicting the quality of service (QoS) values of fog nodes is essential for IoT devices. In an open and dynamic environment (such as fog computing), the numerous IoT devices contribute unreliable and false ratings to the services which make service recommendation a challenging problem. With the huge growth in service-oriented computing (such as fog computing), numerous fog nodes offer similar services at different performance levels due to which the IoT devices face difficulty in recognising appropriate fog nodes as per its requirement. The literature survey indicates that very few of the prediction approaches have focused on predicting QoS values considering the trust of the IoT devices. This paper proposes an approach for QoS prediction based on the trustworthiness of IoT devices that allows choosing the reliable and trustworthy fog node. The proposed method employs a hybrid technique to combine the item-based user similarity, context-based user similarity and trust computation based on multiple source feedback mechanism that provides a reliable QoS prediction for service recommendation and helps the IoT devices to choose the most suitable service that meet their needs. The result analysis shows that the proposed approach is effective than the existing approaches.