An efficient sensor-cloud interactive model for on-demand latency requirement guarantee

This paper proposes an efficient interactive model for sensor-cloud integration to enable the sensor-cloud to provide on-demand sensing services for multiple applications with different latency requirements at the same time. In the model, we design an aggregation mechanism for the sensor-cloud to aggregate application requests so that workloads required for constrained sensor nodes are minimized to save energy. Sensing packet delivery latency from sensor-to-cloud is controlled by the sensor-cloud based feedback control theory. Based on feedbacks from the sensor-cloud, physical sensor nodes optimize their scheduling accordingly to save energy while satisfying latency requirements of all applications. Analysis and experimental results show that our proposed system effectively controls the latency of sensing flows with low signaling overhead and high energy efficiency compared to the state-of-the-art scheme.