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Course Detail

Course Name Edge Computing
Course Code 26CSA683
Program M. C. A.
Credits 1
Campuses Amritapuri, Mysuru

Syllabus

Unit I

IoT & Edge Computing Fundamentals 

  • Study and demonstration of IoT and Edge Computing use cases (Smart home, Healthcare, Smart agriculture). 
  • Comparative analysis of Edge vs Fog vs Cloud Computing using real-world scenarios. 
  • Implementation of M2M communication models using simulation tools. 
  • Design of an Edge computing architecture for a given use case (block diagram and workflow).
Unit II

IoT Architecture & Case Studies 

  • Design and implementation of a basic IoT architecture showing devices, gateways, edge, and cloud. 
  • Analysis of IoT vs M2M vs SCADA with suitable examples. 
  • Case study implementation: Telemedicine / Palliative Care IoT System – requirement analysis and deployment architecture. 
  • Implementation of a sample IoT deployment and evaluation of performance at edge vs cloud. 
Unit III

Raspberry Pi Basics & Device Interfacing 

  • Familiarization with Raspberry Pi hardware, GPIO pin configuration, and OS installation. 
  • Establish SSH-based remote access to Raspberry Pi. 
  • Interface DHT11/DHT22 temperature and humidity sensor with Raspberry Pi. 
  • Configure Raspberry Pi as a web server to display sensor data. 
  • Interface Pi Camera for image and video capture. 
  • Perform basic image and video processing using Raspberry Pi. 
Unit IV

MQTT & Edge-to-Cloud Communication 

  • Install and configure MQTT broker (Mosquitto) on Raspberry Pi. 
  • Implement MQTT publish–subscribe model for sensor data transmission. 
  • Study MQTT packet structure and state transitions through practical demonstration. 
  • Implement MQTT 3.1.1 working example for edge-to-cloud data communication. 
  • Analyze MQTT data formats and QoS levels. 
Unit V

Edge Computing Applications 

  • Develop an Edge computing application using Raspberry Pi (local data filtering/analytics). 
  • Implement Edge-based alert system for industrial or commercial IoT use cases. 
  • Comparative performance analysis of Edge vs Cloud processing (latency, bandwidth). 
  • Mini Project: Industrial/Commercial IoT solution using Edge computing (Smart monitoring system). 

Objectives and Outcomes

Course Description

The course is intended to develop the student’s knowledge and abilities of how edge computing and Internet of Things (IoT) can be used as a way to meet application demands in intelligent IoT systems. This includes an understanding and use of the IoT architecture with its entities and protocols, from the IoT devices, via middle layers like edge and fog, up to the cloud. It also includes the understanding of the computing and communication technologies used for IoT, as well as the analysis of their constraints, as e.g. perfor mance, power efciency, memory size, and communication bandwidth. The course also includes the security and privacy issues related to the area of edge computing, IoT, and big data. Further, it is intended to provide the possibility for the student to, from the basis of relevant literature, reect over and discuss current research and development regarding highly demanding streaming applications, like advanced sen sing or machine learning, at the edge of an IoT system. The student should be able under supervision to implement an edge and IoT systems.

 Course Objectives 

  • build a basic IoT system which includes edge computations
  • investigate, discuss, and compare architectural design options regarding the tradeoff between computations and communication in an IoT system, depending on application demands and resource constraints
  • identify, read, and understand relevant scientfic publications; review, discuss, and summarize them, and present the findings both orally and in written form.

Course Outcomes 

After completing this course, students will be able to: 

COs 

Description 

CO1 

Describe basic requirements of edge computing.

CO2 

Discuss architectures and applications in fog and edge computing.

CO3 

Use fog and edge computing services.

CO4 

Demonstrate tools and its usages 

CO5 

Implement software using standard open-source fog and edge computing software for data analytics.

CO-PO Mapping 

PO/PSO 

PO1 

PO2 

 PO3 

PO4 

PO5 

PO6 

PO7 

PO8 

CO 

CO1 

3 

– 

– 

– 

– 

– 

– 

– 

CO2 

3 

1 

– 

– 

– 

– 

– 

– 

CO3 

1 

– 

3 

– 

– 

– 

– 

– 

CO4 

– 

– 

3 

– 

– 

– 

– 

– 

CO5 

1 

3 

– 

– 

– 

– 

– 

– 

Textbooks / References

  • IoT and Edge Computing for Architects – Second Edition, by Perry Lea, Publisher: Packt Publishing, 2020, ISBN: 9781839214806
  • Raspberry Pi Cookbook, 3rd Edition, by Simon Monk, Publisher: O’Reilly Media, Inc., 2019, ISBN: 978149204322.
  • Fog and Edge Computing: Principles and Paradigms by Rajkumar Buyya, Satish Narayana
  • Srirama, wiley publication, 2019, ISBN: 9781119524984.
  • David Jensen, “Beginning Azure IoT Edge Computing: Extending the Cloud to the
  • Intelligent Edge, MICROSOFT AZURE

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