Crowdsourced Coverage as a Service: Two-Level Composition of Sensor Cloud Services
A new two-level composition model for crowdsourced Sensor-Cloud services is proposed based on dynamic features such as spatio-temporal aspects. The proposed approach is defined based on a formal Sensor-Cloud service model that abstracts the functionality and non-functional aspects of sensor data on the cloud in terms of spatio-temporal features. A spatio-temporal indexing technique based on the 3D R-tree to enable fast identification of appropriate Sensor-Cloud services is proposed. A novel quality model is introduced that considers dynamic features of sensors to select and compose Sensor-Cloud services. The quality model defines Coverage as a Service which is formulated as a composition of crowdsourced Sensor- Cloud services. Two new QoS-aware spatio-temporal composition algorithms is proposed to select the optimal composition plan.
Advantages
- Devise the best public transport travel plan
Architecture diagram
Implementation of crowdsourced sensor data