Course

PROFESSIONAL ELECTIVES

Electives in Cyber Physical Systems

Unit I

Overview of edge computing and its significance in distributed systems. Edge computing architectures, models, and platforms. Comparison of edge computing with cloud computing and fog computing. Case studies of edge computing applications

Unit II

Resource management in edge computing and its challenges. Resource management techniques for edge computing, including task scheduling algorithms, resource allocation algorithms, and load balancing algorithms. Case studies and applications of resource management in edge computing, such as mobile edge computing, and autonomous vehicles.

Unit III

Metrics for measuring performance in edge computing: latency, throughput, and energy efficiency. Case studies of performance analysis and optimization in edge computing, such as edge-based video streaming, smart transportation systems, and healthcare IoT devices. Emerging trends in edge computing: edge intelligence, serverless computing, edge security, and hybrid cloud and edge architectures.

Course Objectives

• This course aims to teach students about edge computing for cyber-physical systems, including its design, implementation, and evaluation.
• Students will learn about various applications of edge computing in cyber-physical systems, enabling them to gain practical knowledge in the field.
• Upon completion of this course, students will have a solid understanding of edge computing and its role in the emerging field of cyber-physical systems.
• Understand the characteristics of real-time systems in the context of cyber-physical systems (CPS) and differentiate between general-purpose operating systems and real-time operating systems (RTOS) in CPS.
• Explore the design considerations, scheduling algorithms, task synchronization, communication mechanisms, memory management, and protection in RTOS for CPS, as well as real-time file systems and device drivers.
• Develop skills in performance evaluation, analysis, and testing of RTOS in CPS, including measuring key performance metrics, studying performance analysis techniques, and understanding real-time debugging and testing methods. Gain awareness of challenges and open research issues in the field of RTOS for CPS.

Course Outcomes

CO1: Understand the fundamental concepts of edge computing and its significance in the context of distributed systems.

CO2: Ability to design edge computing solutions, including architectures, models, and platforms.

CO3: Develop knowledge of resource management techniques in edge computing, including task scheduling algorithms, resource allocation algorithms, and load balancing algorithms.

CO4: Apply performance analysis and optimization techniques to evaluate the effectiveness and efficiency of edge computing solutions.

CO-PO Mapping

Evaluation Pattern: 70:30

*CA – Can be Quizzes, Assignment, Projects, and Reports

**End Semester can be theory examination/ lab-based examination/ project presentation

Textbook(s)

1. Anitha Kumari, G. Sudha Sadasivam, D. Dharani and M. Niranjanamurthy,“Edge Computing Fundamentals, Advances and Applications”, CRC Press, 2022.

Reference(s)

Xin Sun and Amin Vahdat, “Edge Computing: A Primer”, CRC Press, 2019.

Daniel Situnayake, Jenny Plunkett, “AI at the Edge”, O’Reilly Media, Inc, 2023.

Rajkumar Buyya and Satish Narayana Srirama, “Fog and Edge Computing Principles and Paradigms”, John Wiley & Sons, Inc.