· Provides a novel service framework to manage crowdsourced sensor data. This service framework aims to provide high-level abstraction (i.e., sensor-cloud service) to model crowdsourced sensor data from functional and non-functional perspectives, seamlessly turning the raw data into "ready to go" services. A creative indexing model is developed to capture and manage the spatio-temporal dynamism of crowdsourced service providers.
· Delivers novel frameworks to compose crowdsourced sensor-cloud services. These frameworks will focus on spatio-temporal composition of crowdsourced sensor-cloud services, which is a new territory for existing service oriented computing research. A creative failure-proof model is also designed to prevent composition failure caused by fluctuating QoS.
· Presents an incentive model to drive the coverage of crowdsourced service providers. A new spati-temporal incentive model targets changing coverage of the crowdsourced providers to achieve demanded coverage of crowdsourced sensor-cloud services within a region.
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