Cloud-Assisted Data Fusion and Sensor Selection for Internet-of-Things

Cloud-Assisted Data Fusion and Sensor Selection for Internet-of-Things
The Internet of Things (IoT) is connecting people and smart devices on a scale that was once unimaginable. One major challenge for the IoT is to handle vast amount of sensing data generated from the smart devices that are resource-limited and subject to missing data due to link or node failures. By exploring cloud computing with the IoT, we present a cloud-based solution that takes into account the link quality and spatio-temporal correlation of data to minimize energy consumption by selecting sensors for sampling and relaying data. We propose a multiphase adaptive sensing algorithm with belief propagation (BP) protocol (ASBP), which can provide high data quality and reduce energy consumption by turning on only a small number of nodes in the network.

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