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    Internet of Things as a Service (iTaaS): challenges and solutions for management of sensor data on the Cloud and the Fog

    Petrakis, E. and Sotiriadis, Stelios and Soultanopoulos, T. and Tsiachri Renta, P. and Buyya, R. and Bessis, N. (2018) Internet of Things as a Service (iTaaS): challenges and solutions for management of sensor data on the Cloud and the Fog. Internet of Things 3-4 , pp. 156-174. ISSN 2542-6605.

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    Abstract

    Building upon cloud, IoT and smart sensors technologies we design and de- velop an IoT as a Service (iTaaS) framework, that transforms a user device (e.g. a smart phone) to an IoT gateway that allows for fast and efficient data streams transmission to the cloud. We develop a two-fold solution, based on micro-services for the IoT (users’ smart devices) and the cloud side (back-end services). iTaaS includes configurations for (a) the IoT side to support data collection from IoT devices to a gateway on a real time basis and, (b) the cloud back-end side to support data sharing, storage and processing. iTaaS provides the technology foreground to enable immediate application deployments in the domain of interest. An obvious and promising implementation of this technology is e-Health and remote health monitoring. As a proof of concept we implement a real time remote patient monitoring system that integrates the proposed frame- work and uses BLE pulse oximeter and heart rate monitoring sensing devices. The experimental analysis shows fast data collection, as (for our experimental setup) data is transmitted from the IoT side (i.e. the gateway) to the cloud in less than 130ms. We also stress the back-end system with high user concurrency (for example with 40 users per second) and high data streams (for example 240 data records per second) and we show that the requests are executed at around 1 second, a number that signifies a satisfactory performance by considering the number of requests, the network latency and the relatively small size of the Virtual Machines implementing services on the cloud (2GB RAM, 1 CPU and 20GB hard disk size).

    Metadata

    Item Type: Article
    School: Birkbeck Schools and Departments > School of Business, Economics & Informatics > Computer Science and Information Systems
    Research Centre: Birkbeck Knowledge Lab
    Depositing User: Stelios Sotiriadis
    Date Deposited: 18 Sep 2018 09:02
    Last Modified: 02 Oct 2019 06:48
    URI: http://eprints.bbk.ac.uk/id/eprint/23955

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