KTU 2024 Scheme · Semester 6 · Computer Science and Engineering

Advanced Computing Systems (PCCST602) Syllabus

Official KTU 2024 Scheme syllabus for Advanced Computing Systems, Semester 6, Computer Science and Engineering (Computer Science and Engineering).

This page compiles APJ Abdul Kalam Technological University's officially published 2024 Scheme syllabus for Computer Science and Engineering, Semester 6, sourced directly from KTU's official website (ktu.edu.in). Learnizo is an independent online tuition platform and is not affiliated with, endorsed by, or officially connected to APJKTU. The university may revise syllabus content after this page was last updated — always cross-check with the official KTU source for the current, authoritative version.

Course Code

PCCST602

Credits

Teaching Hours

3:0:0:0 (L:T:P:R)

CIE Marks

ESE Marks

Exam Duration

2 Hrs 30 Min

Prerequisites

GAEST203, PBCST404 (Computer Organization and Architecture), PCCST403 (Operating Systems)

Semester

Semester 6

Course Objective

To introduce the computational models prevalent in modern distributed systems, and to provide the concepts of computer clusters, virtualization, cloud computing, microservices and containers.

Module-wise Syllabus

Module 1

7 contact hours

Distributed System Models and Enabling Technologies: the age of internet computing — high performance and high throughput computing, centralized/parallel/distributed/cloud computing, design objectives of HPC and HTC, IoT and cyber-physical systems.

Module 2

11 contact hours

Technologies for Network-Based Systems: multicore CPUs and multithreading technologies, GPU computing, virtual machines. System models for distributed and cloud computing: clusters, grids, P2P systems, clouds. Computer Clusters: clustering for massive parallelism — design objectives and issues (ensuring high availability, cluster families, cluster architecture, GPU cluster components), design principles (single system image features, high availability through redundancy, fault tolerant configurations, checkpoint and recovery), cluster job and resource management (scheduling methods, administration, job types, migration schemes).

Module 3

9 contact hours

Virtualization: introduction, virtualization at different levels and comparison, VMM design requirements, OS-level virtualization, virtualization structures and mechanisms, CPU/memory/I/O virtualization, virtual clusters and resource management, live VM migration steps (memory, files and network resources).

Module 4

9 contact hours

Cloud Computing, Microservices and Containers: cloud computing and service models — private/public/hybrid clouds, design objectives and cost model, IaaS/PaaS/SaaS. Microservices: introduction, advantages/disadvantages, interprocess communication (types of interactions, protocol, standard and message format, discovery service, API gateway, service registry). Containers: comparison of VMs and containers, introduction to Docker, case study — Docker containers' architecture, components and examples.

Course Outcomes

CO1Illustrate the key enabling technologies for network-based systems, including multicore CPUs, multithreading, GPU computing, and virtualization, and how these contribute to the performance and efficiency of distributed systems.
CO2Use computer cluster architectures, ensuring high availability, fault tolerance, and massive parallelism, and implement effective job and resource management strategies within cluster environments.
CO3Explain various levels of virtualization, including CPU, memory, and I/O virtualization, and understand the design requirements and mechanisms of Virtual Machine Monitors (VMMs).
CO4Articulate the differences between private, public, and hybrid cloud models, and understand the design objectives and cost considerations associated with different cloud models.
CO5Explain microservices architecture, its advantages and disadvantages, the principles of interprocess communication, and the role of containers in modern computing, with a focus on Docker.

Assessment Pattern (CIE: 40 marks, ESE: 60 marks)

Continuous Internal Evaluation (CIE)

Attendance	5
Assignment / Microproject	15
Internal Examination 1 (Written)	10
Internal Examination 2 (Written)	10

End Semester Examination (ESE)

Total 60 marks, 2 Hrs 30 Min. See the official KTU syllabus document for the exact Part A / Part B question pattern for this course.

Textbooks & Reference Books

Textbooks

Distributed and Cloud Computing: From Parallel Processing to the Internet of Things — Kai Hwang, Geoffrey C. Fox, Jack Dongarra (Morgan Kaufmann, 1st edition, 2013)
Microservices and Containers — Parminder Singh Kocher (Addison-Wesley, 1st edition, 2018)

Reference Books

Patterns of Distributed Systems — Unmesh Joshi (Pearson Education, 1st edition, 2024)
Cluster Computing, Grid Computing, Cloud and Virtualization — Deepa Kalavikatte (DSK Publisher, 1st edition, 2020)
Cloud and Distributed Computing: Algorithms and Systems — Rajiv Misra, Yashwant Singh Patel (Wiley, 1st edition, 2020)

Frequently Asked Questions

How many credits is KTU Advanced Computing Systems (PCCST602)?

3 credits, with 3:0:0:0 (L:T:P:R) teaching hours per week, under the KTU 2024 Scheme.

How many modules are in the PCCST602 syllabus?

4 modules, 36 total contact hours.

What is the CIE and ESE mark split for this course?

CIE (Continuous Internal Evaluation): 40 marks. ESE (End Semester Examination): 60 marks, 2 Hrs 30 Min. Total: 100 marks.

What are the recommended textbooks for PCCST602?

Distributed and Cloud Computing: From Parallel Processing to the Internet of Things (Kai Hwang, Geoffrey C. Fox, Jack Dongarra); Microservices and Containers (Parminder Singh Kocher).

Is this syllabus specific to one branch, or common to others too?

This Semester 6 course is listed under Computer Science and Engineering at KTU under the 2024 Scheme — check the course header above for which branches it's common to.

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