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A Data-Centric Internet of Things Framework Based on Azure Cloud
Linköping University, Department of Science and Technology, Physics, Electronics and Mathematics. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-5742-1266
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering.
Linköping University, Faculty of Science & Engineering. Linköping University, Department of Science and Technology, Physics, Electronics and Mathematics.ORCID iD: 0000-0002-4136-0817
Corporate Research, ABB AB, Västerås, Sweden.
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2019 (English)In: IEEE Access, E-ISSN 2169-3536, Vol. 7, p. 53839-53858Article in journal (Refereed) Published
Abstract [en]

Internet of Things (IoT) has been found pervasive use cases and become a driving force to constitute a digital society. The ultimate goal of IoT is data and the intelligence generated from data. With the progress in public cloud computing technologies, more and more data can be stored, processed and analyzed in cloud to release the power of IoT. However, due to the heterogeneity of hardware and communication protocols in the IoT world, the interoperability and compatibility among different link layer protocols, sub-systems, and back-end services have become a significant challenge to IoT practices. This challenge cannot be addressed by public cloud suppliers since their efforts are mainly put into software and platform services but can hardly be extended to end devices. In this paper, we propose a data-centric IoT framework that incorporates three promising protocols with fundamental security schemes, i.e., WiFi, Thread, and LoRaWAN, to cater to massive IoT and broadband IoT use cases in local, personal, and wide area networks. By taking advantages of the Azure cloud infrastructure, the framework features a unified device management model and data model to conquer the interoperability challenge. We also provide implementation and a case study to validate the framework for practical applications.

Place, publisher, year, edition, pages
IEEE, 2019. Vol. 7, p. 53839-53858
Keywords [en]
Internet of Things, Cloud computing, Protocols, Wireless fidelity, Broadband communication, Monitoring, Interoperability, framework, cloud, azure, IoT hub, thread, WiFi, lorawan
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:liu:diva-156704DOI: 10.1109/ACCESS.2019.2913224ISI: 000467047300001OAI: oai:DiVA.org:liu-156704DiVA, id: diva2:1314913
Note

Funding agencies:  Swedish Environmental Protection Agency; Norrkoping Fund for Research and Development, Sweden

Available from: 2019-05-10 Created: 2019-05-10 Last updated: 2019-08-21
In thesis
1. A Data-centric Internet of Things Framework Based on Public Cloud
Open this publication in new window or tab >>A Data-centric Internet of Things Framework Based on Public Cloud
2019 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

The pervasive application of Internet of Things (IoT) has been seen in many aspects in human daily life and industrial production. The concept of IoT originates from traditional machine-to-machine (M2M) communications which aimed at solving domain-specific and applicationspecific problems. Today, the rapid progress of communication technologies, the maturation of Internet infrastructures, the continuously reduced cost of sensors, and emergence of more open standards, have witnessed the approaching of the expected IoT era, which envisions full connectivity between the physical world and the digital world via the Internet protocol. The popularity of cloud computing technology has enhanced this IoT transform, benefiting from the superior computing capability and flexible data storage, let alone the security, reliability and scalability advantages.

However, there are still a series of obstacles confronted by the industry in deployment of IoT services. First, due to the heterogeneity of hardware devices and application scenarios, the interoperability and compatibility between link-layer protocols, sub-systems and back-end services are significantly challenging. Second, the device management requires a uniform scheme to implement the commissioning, communication, authorization and identity management to guarantee security. Last, the heterogeneity of data format, speed and storage mechanism for different services pose a challenge to further data mining.

This thesis aims to solve these aforementioned challenges by proposing a data-centric IoT framework based on public cloud platforms. It targets at providing a universal architecture to facilitate the deployment of IoT services in massive IoT and broadband IoT categories. The framework involves three representative communication protocols, namely WiFi, Thread and Lo-RaWAN, to enable support for local, personal, and wide area networks. A security assessment taxonomy for wireless communications in building automation networks is proposed as a tool to evaluate the security performance of adopted protocols, so as to mitigate potential network flaws and guarantee the security. Azure cloud platform is adopted in the framework to provide device management, data processing and storage, visualization, and intelligent services, thanks to the mature cloud infrastructure and the uniform device model and data model. We also exhibit the value of the study by applying the framework into the digitalization procedure of the green plant wall industry. Based on the framework, a remote monitoring and management system for green plant wall is developed as a showcase to validate the feasibility. Furthermore, three specialized visualization methods are proposed and a neuron network-based anomaly detection method is deployed in the project, showing the potential of the framework in terms of data analytics and intelligence.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2019. p. 43
Series
Linköping Studies in Science and Technology. Licentiate Thesis, ISSN 0280-7971 ; 1850
National Category
Communication Systems
Identifiers
urn:nbn:se:liu:diva-159770 (URN)10.3384/lic.diva-159770 (DOI)9789175190136 (ISBN)
Presentation
2019-09-13, K3, Kåkenhus, Campus Norrköping, Norrköping, 10:15 (English)
Opponent
Supervisors
Available from: 2019-08-21 Created: 2019-08-21 Last updated: 2019-08-26Bibliographically approved

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