Network Management and Clouds

The course “Network Management and Clouds” focuses on the integration of communication network management techniques with the principles and technologies of Cloud Computing. It presents service models (IaaS, PaaS, SaaS), cloud deployment types (public, private, hybrid), and their extensions into Fog and Edge Computing. It also examines service design and development processes, the use of protocols such as SNMP for network management, as well as the main functions and services of management systems. Finally, emphasis is placed on the role of Artificial Intelligence in the automation, optimization, and prediction of network operations.

Upon successful completion of the course, students will be able to:

• Understand the fundamental principles of Cloud Computing and the differences between IaaS, PaaS, and SaaS models.

• Identify the differences and advantages of Public, Private, and Hybrid Cloud.

• Explain the principles of Fog Computing and how it differs from Cloud and Edge Computing.

• Describe the processes of designing, developing, and delivering services in Cloud and Fog environments.

• Understand the concepts of Network Management, its functional areas, and the core services.

• Interpret the use of SNMP (Simple Network Management Protocol) in network management and explain its operation.

• Analyze the methodologies for designing and implementing network management systems.

• Comprehend the role of Artificial Intelligence (AI) in network management, automation techniques, and problem prediction.

1. Fundamentals of Cloud Computing

   • Introduction to Cloud Computing

   • The need for network and cloud systems management

   • Relationship between network management and cloud infrastructures

   • Infrastructure technologies: Virtualization, Containers, Software-Defined Networking (SDN)

2. Cloud Service Models

   • Infrastructure as a Service (IaaS)

   • Platform as a Service (PaaS)

   • Software as a Service (SaaS)

   • Comparison, advantages, and disadvantages

3. Types of Cloud

   • Public, Private, and Hybrid Cloud

   • Benefits and challenges

   • Case studies (AWS, Azure, Google Cloud)

4. Cloud, Fog, and Edge Computing

   • Differences and similarities

   • Distributed data processing architectures

   • Fog Computing applications in IoT and industrial systems

5. Design and Optimization of Infrastructures

   • Design principles of Cloud and Fog infrastructures

   • Optimization of networking and computing resources

   • Resilience, scalability, and performance

6. Services and Resource Management

   • Data storage and analytics services

   • Load balancing and scaling in Cloud-based applications

   • QoS management in Cloud and Fog environments

7. Fundamentals of Network Management

   • Organization of network management systems

   • Functional areas and core services

   • Characteristics of network management platforms

8. Network Management with SNMP

   • Principles of SNMP operation

   • Structure and functional components (MIB, Agents, Managers)

   • Applications of remote monitoring and management

9. Network Management Platforms

   • Management via web interfaces

   • Tools and platforms: Cisco DNA Center, OpenNMS, Zabbix

10. Performance and Security Management

    • Management of performance, security, software, and network policies

    • The role of SDN in automated management

11. Design of Network Management Systems

    • Design methodologies

    • Requirements analysis and reliability factors

    • Selection and configuration of management software

12. Artificial Intelligence in Network Management

    • AI for traffic prediction and network management

    • AI-driven automation and anomaly detection

    • Applications of Machine Learning and Deep Learning in network management

13. Applications and Case Studies

    • Real-world examples of integrated Cloud/Fog/Edge infrastructures

    • Integration of management techniques with AI and SDN

    • Case studies from industry and research projects

    • Discussion on future perspectives and trends