Abstract
Internet of Things (IoT) evolves very rapidly over time, since everything such as sensors/actuators linked together from around the world with use of evolution of ubiquitous computing through the Internet. These devices have a unique IP address in order to communicate with each other and transmit data with features of wireless technologies. Fog computing or so called edge computing brings all Cloud features to embedded devices at edge network and adds more features to servers like pre-store data of Cloud, fast response, and generate overhasty users reporting. Fog mediates between Cloud and IoT devices and thus enables new types of computing and services. The future applications take the advantage of combing the two concepts Fog and Cloud in order to provide low delay Fog-based and high capacity of storage Cloud-based. This paper proposes an IoT architecture for healthcare network based on Fog to Cloud and Data in Motion (F2CDM). The proposed architecture is designed and implemented over three sites: Site 1 contains the embedded devices layer, Site 2 consists of the Fog network layer, while Site 3 consists of the Cloud network. The Fog layer is represented by a middleware server in Al-Nahrain University with temporary storage such that the data lives inside for 30 min. During this time, the selection of up-normality in behavior is send to the Cloud while the rest of the data is wiped out. On the other hand, the Cloud stores all the incoming data from Fog permanently. The F2CDM works using Message Queue Telemetry Transport (MQTT) for fast response. The results show that all data can be monitored from the Fog in real time while the critical data can be monitored from Cloud. In addition, the response time is evaluated using traffic generator called Tsung. It has been found that the proposed architecture reduces traffic on Cloud network and provides better data analysis.
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Al-Joboury, I.M., Al-Hemiary, E.H. (2017). F2CDM: Internet of Things for Healthcare Network Based Fog-to-Cloud and Data-in-Motion Using MQTT Protocol. In: Sabir, E., García Armada, A., Ghogho, M., Debbah, M. (eds) Ubiquitous Networking. UNet 2017. Lecture Notes in Computer Science(), vol 10542. Springer, Cham. https://doi.org/10.1007/978-3-319-68179-5_32
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DOI: https://doi.org/10.1007/978-3-319-68179-5_32
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