Efficient Metrics for Data Recovery at Perception Layer: e-health Case Study

Abstract

Abstract The Internet of Things (IoT) is one of the most innovative technologies, which promises to improve and optimize daily life using sensors and smart devices. Semantic Web of Things (SWoT) is an extension of IoT that makes it possible for devices to enhance communication between each other by behaving intelligently. The SWoT comprises seven-layer architecture, where the perception layer is one of the most important layers, which is used for collecting data from devices and for ensuring communication with the devices and associated layer. Due to insufficient resources, unpredictable link, noise, collision, and sensor faults, data loss can occur at sensor nodes of perception. This paper defines the recoverability metric for the perception layer of the SWoT architecture. The contribution of this paper is three folds. First, it describes the main challenges for data communication in the perception layer. Second, it focuses on the recoverability metric that recovers the missing data at the perception layer. Finally, the recoverability metric is evaluated and compared with the ISO-9126-1 standard design quality metrics. To develop the design quality of SWoT, different measures, including efficiency, availability, and recoverability, are considered and proved with e-health case study. The results are statistically proven and demonstrate that the application of the proposed metric can enhance the SWoT performance and overcomes the problem of temporal loss of information.