Development of an IoT data processing system using
distributed technologies based on Kubernetes

Bellos, Nikolas; Μπέλλος, Νικόλας

dc.contributor.author	Bellos, Nikolas	en
dc.contributor.author	Μπέλλος, Νικόλας	el
dc.date.accessioned	2024-04-19T08:33:08Z
dc.date.available	2024-04-19T08:33:08Z
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/59228
dc.identifier.uri	http://dx.doi.org/10.26240/heal.ntua.26924
dc.rights	Αναφορά Δημιουργού - Παρόμοια Διανομή 3.0 Ελλάδα	*
dc.rights.uri	http://creativecommons.org/licenses/by-sa/3.0/gr/	*
dc.subject	Kubernetes	en
dc.subject	IoT	en
dc.subject	Distributed Systems	en
dc.subject	Smart Home	en
dc.subject	Systems Design	en
dc.subject	Cloud Computing	en
dc.title	Development of an IoT data processing system using distributed technologies based on Kubernetes	en
dc.title	Ανάπτυξη συστήματος επεξεργασίας IoT δεδομένων με χρήση κατανεμημένων τεχνολογιών βασισμένο σε Kubernetes	el
heal.type	bachelorThesis
heal.classification	Systems Engineering	en
heal.classification	Distributed Systems	en
heal.language	en
heal.access	free
heal.recordProvider	ntua	el
heal.publicationDate	2024-02-29
heal.abstract	The Internet of Things (IoT) era is here, with the number of internetconnected devices expected to hit over 75.4 billion by 2025. These devices create lots of data that help us understand and control our environment from afar. Traditionally, the systems managing this data have been closedsource and outdated by the time they’re widely available. Now, cloud-native technologies and virtualization make it easier and more efficient to manage IoT systems. Kubernetes, a key tool, helps make building and maintaining IoT infrastructures simpler and less manpower-intensive. This thesis explores the design and implementation of an IoT system using distributed technologies deployed on Kubernetes, an open-source framework for automating container application management, deployment, and scaling. It discusses the need for efficient processing and management of large data volumes generated by numerous IoT devices and how implementation through Kubernetes offers a flexible and dynamically scalable solution. Additionally, it examines technologies like MQTT for efficient message transfer and Apache Kafka for real-time data processing and storage. It also analyzes the importance of using distributed systems to improve performance, scalability, and resilience compared to centralized systems, as well as the challenges encountered in managing distributed data and achieving consensus in such environments. Finally, it presents suggestions for future work, including automated scaling, monitoring metrics, continuous integration/delivery (CI/CD), and the extensive implementation of security techniques.	en
heal.advisorName	Marinakis, Vangelis	en
heal.advisorName	Sarmas, Elissaios	en
heal.committeeMemberName	Marinakis, Vangelis	en
heal.committeeMemberName	Doukas, Haris	en
heal.committeeMemberName	Psarras, John	en
heal.academicPublisher	Εθνικό Μετσόβιο Πολυτεχνείο. Σχολή Ηλεκτρολόγων Μηχανικών και Μηχανικών Υπολογιστών. Τομέας Ηλεκτρικών Βιομηχανικών Διατάξεων και Συστημάτων Αποφάσεων	el
heal.academicPublisherID	ntua
heal.numberOfPages	96 σ.	el
heal.fullTextAvailability	false