Budapest University of Technology and Economics, Faculty of Electrical Engineering and Informatics

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    Cloud Services integration for Intelligent Devices

    A tantárgy neve magyarul / Name of the subject in Hungarian: Felhőszolgáltatások intelligens eszközök támogatására

    Last updated: 2025. november 6.

    Budapest University of Technology and Economics
    Faculty of Electrical Engineering and Informatics     		MSc, Electrical Engineering
    Course ID Semester Assessment Credit Tantárgyfélév
    VITMMA14   2/1/0/v 5  
    3. Course coordinator and department Dr. Simon Csaba,
    Web page of the course https://www.tmit.bme.hu/vitmma14
    4. Instructors Dr. Simon Csaba (Associate Professor, BME TMIT)
    Dr. Maliosz Markosz (Associate Professor, BME TMIT) 

    7. Objectives, learning outcomes and obtained knowledge In several industries, as part of  the digitalization process, the  industry-specific devices are connected to applications installed in the cloud. This leads to a blurring of the boundary between electrical engineering systems and information infrastructure, and a digitalized environment formed by smart devices integrated with the cloud system is realized. During the design, implementation and operation of such a system, it is equally important for electrical engineers to understand the characteristics of the defining element of the IT infrastructure, the cloud-based network. An additional task is to learn about the alternatives for integrating smart devices into the cloud system. The aim of the course is to transfer the above knowledge, illustrate it with the help of use cases, and practice it.

    In the first part of the course, the properties of cloud systems are described, with particular attention to a cloud-based infrastructure and a cloud network. In the second part, the practical implementation of these principles is presented, the focus will be on learning about and using the elements of the system. In the third part, issues of integrating smart devices into the cloud system will be discussed through specific case studies using IoT applications used in departmental research and development projects.

    8. Synopsis 1. Introduction

    Motivation: digitalization of industries. Usage environment: Internet of Things (IoT) devices, possibilities of networked devices, communication needs. Smart devices: the task and role of intelligence in IoT systems. Trends.

    2. Fundamentals of cloud systems

    Background of the development of cloud-based systems, motivation. Definition of cloud systems, categories, use cases, security, monitoring.

    3. Cloud services

    Cloud service models: IaaS, PaaS, SaaS. The microservices model. Virtual machine and container-based systems. Orchestration functions, development of complex services, service chains.

    4. Cloud service providers

    Cloud systems and data centers. Presentation and illustration of the architecture of a cloud system through an OpenStack cloud. Large public service providers (hyperscalers: AWS, Google Cloud and Azure) and their functions.

    5. Container-based systems

    Container-based virtualization (Docker, Podman, Containerd). Container management frameworks (Kubernetes). The relationship between Kubernetes and cloud systems (Amazon EKS).

    6. IoT platforms in the cloud

    The role of cloud-based IoT platforms, their characteristic functions. Case study: Introduction and comparison of Amazon IoT Device Management and Amazon IoT Core services.

    7. Smart devices in the Edge environment

    The edge computing model (Edge Computing). Edge computing for IoT services.

    8. Mobile network conditions for controlling smart devices

    Quality requirements for remote control of smart devices. Properties of 5G networks, conditions provided for machine communication.

    9. IoT support in 5G networks

    IoT support in 5G systems using virtualized functions and MEC. Aspects of deploying smart devices and industrial applications in 5G private networks.

    10. Device control in an industrial environment

    Case study: control tasks during IoT Industry 4.0 work. Task performance conditions, communication and computing requirements.

    11. Cloud-based device control

    Presentation of communication conditions for remote device control. Analysis of QoS requirements.

    12. Orchestration tasks

    Presentation of resource and service orchestration tasks. Ensuring resource requirements for remote device control in a dynamic environment. Maintaining quality of service, ensuring automatic adaptation in the cloud system.

    13. Implementing real-time tasks in cloud systems

    Implementation problems of real-time tasks in cloud systems. Possibility of implementing real-time communication in the cloud network environment. Integration of delay-sensitive networking (Time-Sensitive Networking - TSN) into cloud systems.

    Detailed topics of the exercises/labs:

    1. Getting to know the AWS system
    2. Managing containers in AWS, Amazon Elastic Container Service (ECS). Creating and managing a container.
    3. Kubernetes and AWS: Amazon Elastic Kubernetes Service (EKS). Creating and managing a pod.
    4. Distributed event management in cloud systems: AWS IoT Core.
    5. Presentation of the departmental 5G network. Implementing a container-based service in this network.
    6. Industrial IoT case study. Outsourcing intelligence from the device.
    7. Analyzing the requirements of cloud-based real-world control, setting up task scheduling.

    9. Method of instruction Lectures and practices (in small groups).

    10. Assessment

    During the teaching period

    Succesful completion of one midterm at the middle of the teaching period.

    During the exam period

    Written exam, the result of the midterm weights with 25% (theory and simple exercises). 

    11. Recaps It is possible to write the mid-term exam again on the week of repeat.

    12. Consultations It is possible online, based on agreed schedule with the lecturer.
    13. References, textbooks and resources Preparation is aided by the expanded presentation slides prepared for this purpose, as well as the literature listed below:
        Dinesh G. Dutt, Cloud Native Data Center Networking: Architecture, Protocols, and Tools, O'Reilly Media; 1st edition (December 10, 2019) 

    14. Required learning hours and assignment
    Lectures42
    Preparation for lectures34
    Preparation for midterm exam14
    Preparation of homework0
    Learning based on written material30
    Preparation for exam30
    Total150
    15. Syllabus prepared by Dr. Csaba Simon, Associate Professor, TMIT