Nirma University
Institute of Technology
Computer Science and Engineering Department
M.Tech. in Computer Science and Engineering
Detailed Syllabus
Semester – I
3CS1101 High Speed Networks [3 - 1 4]
Learning outcome
• Describe and interpret the basics of high speed networking technologies.
• Apply the concept learnt in this course to optimize and troubleshoot high-speed network.
• Demonstrate the knowledge of network planning and optimization.
• Design and configure network that have outcome characteristics needed to support a specified set of
applications.
Syllabus
Introduction to Computer Networks, Networking Principles, Constant Bit Rate, Variable Bit Rate Network
Services, Network Elements, Multiplexing, Switching, Error Control, Flow Control
Introduction to High Speed Networks, Analysis of Network traffic using deterministic and stochastic Models,
Simulation tools, Tele-traffic engineering, Queuing Models
High Speed TCP Variants, Congestion Control in TCP/IP, ATM
High Speed LAN, Gigabit Ethernet, Distributed Queue Dual Bus (DQDB)
Protocols for QoS Support: IntServ, DiffServ, RSVP, MPLS
Optical Fiber Transmission, TCP/IP Performance over Optical Networks, Fiber Distributed Data Interface,
Switched Multi-Megabit Dual Service(SMDS)
Applications demanding high speed communication, Multimedia IP broadcasting, Error resilience in
Multimedia Transmission, Satellite Broadcasting
Self Learning Component
To be decided by course coordinator at the beginning of semester, which will be a blend of one or more of the
e-Learning Resources, Video Lectures, Online courses, tools, research material, web links etc. along with the
related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at-least 5 experiments are to be carried out.
References:
1. High-speed networks and Internets – Performance and quality of service by William Stallings
2. High Performance TCP/IP Networking: Concepts, issues and solutions: By Mahoob Hassan Raj and
Jain
3. High-speed networks: TCP/IP and ATM design principles by William Stallings
4. High speed networks by Marc Boisseau, Michel Demange, Jean-Marie Munier
5. Multimedia Communications: Applications, Networks, Protocols and Standards, Fred Halsall,
Addison –Wesley
3CS1103 Data Structure and Algorithms [3 – 1 4]
Learning outcome
Appendix C
• Describe the usage of various data structures.
• Explain the operations for maintaining common data structures.
• Recognize the associated algorithms’ operations and complexity.
• Analyze and design efficient algorithms
Syllabus
Elementary Data Structures: Arrays, stack, queues, linked list, sorting techniques, Hash Tables, Binary Search
Trees, B-Trees, Binomial heaps
Mathematical Preliminaries: Algorithm analysis, Algorithm Proof Techniques, Analysis of Algorithms
Growth of Functions: Analyzing Control Structures, Using a barometer, Average case analysis, Amortized
Analysis, Solving recurrences
Greedy Algorithms: Making change, graphs and minimum spanning tree, knapsack problem, Scheduling
Divide and Conquer: General Template, various algorithm implementation eg Binary search , Heap sort,
Quick Sort, Finding the median, matrix multiplication
Dynamic Programming: Introduction of Dynamic Programming, Principle of Optimality, Comparison with
divide and conquer, single source shortest paths, Chained matrix multiplication
Graphs: Elementary Graph Algorithms, DFS, BFS, Backtracking, The knapsack problem, Eight Queens
problem, Branch and bound: The assignment problem
Computational Complexity and NP-Completeness: The classes of P and NP, Polynomial reductions, NPcomplete
problems, NP completeness proofs, NP hard problems, Non-Deterministic algorithms
Self Learning Component
To be decided by course coordinator at the beginning of semester, which will be a blend of one or more of the
e-Learning Resources, Video Lectures, Online courses, tools, research material, web links etc. along with the
related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at-least 5 experiments are to be carried out.
References:
1. Fundamentals of Algorithmics, by Gilles Brassard and Paul Bratley
2. Introduction to Algorithms, by Thomas Cormen, Prentice-Hall India
3. Data structure and Algorithms, by Trembly and Sorenson
3CS1104 Computer Architecture [3 – 1 4]
Learning outcome
• A broad understanding of parallel computer architecture
• To the extent possible, an understanding of the current state-of-the-art in parallel computer
architecture.
Syllabus
Introduction, Flynn’s Taxonomy of Computer Architecture, Introduction to parallel processing, Parallelism in
uniprocessor systems, parallel computer structures, architectural classifications, Input and output subsystem,
virtual memory system, cache memories and management, I/O subsystems, Instruction-Level Parallelism and
its Exploitation, Limits on Instruction-Level Parallelism, Multiprocessors and Thread-Level Parallelism,
Memory Hierarchy Design, instruction and arithmetic pipelines, vector processors and vectorization methods,
SIMD array processors, SIMD computer organizations and interconnection networks, parallel memory
Appendix C
organizations, multiprocessor operating systems, control-flow versus data flow computers
Self Learning Component
To be decided by course coordinator at the beginning of semester, which will be a blend of one or more of the
e-Learning Resources, Video Lectures, Online courses, tools, research material, web links etc. along with the
related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at-least 5 experiments are to be carried out.
References:
1. Computer Architecture and Parallel Processing, K. Hwang and F. A. Briggs. McGraw Hill.
2. Advanced Computer Architecture and Parallel Processing, Hesham El-Rewini, Mostafa Abd-El-Barr,
Wiley
3. Advanced Computer Architecture, H. Stone. Addison Wesley,
4. Interconnection Network for Large Scale Parallel Processing, H. J. Siegel. McGraw Hill
5. Computer Architecture: A Quantitative Approach, 2nd Edition, J. L. Hennessy and D. A. Patterson,
Morgan Kaufmann.
6. Parallel Computer Architecture - A Hardware/Software Approach, D.E. Culler, J.P. Singh, and A.
Gupta, Morgan Kaufmann Publishers.
7. Principles and Practices of Interconnection Networks,W.J. Dally and B. Towles. Morgan Kaufmann
Publishers.
8. Multicore Processors and Systems, S.W. Keckler, K. Olukotun, and H.P. Hofstee. Springer.
9. Research papers from top conferences such as ISCA, HPCA, MICRO, and ASPLOS.
3CS1106 Software Engineering [3 - 1 4]
Learning Outcome
• This subject shall offer the skills for analysis, design, development testing & maintenance of software
towards beneficial for the student in respected profession.
• Students will get acquainted with systematic and organized approach for developing the software
fulfilling the needs of Industries.
• Student will learn an individual as well as teamwork approach for project development which is
essential for their career.
• By upholding the skills of all aspects of system & software production, student’s level of competence
will be enhanced.
Syllabus
Software process and lifecycle: Software Product, Product, Software Processes, , Study of different system
models, Critical Systems, Object Oriented Software Engineering, Formal Methods
Project Management Concepts, Planning and Scheduling, Team organization and people management, Risk
Management, metric and management, software configuration, Software Cost estimation
Software Requirements, Requirements Engineering Processes, Feasibility Studies, Validation and Management
Design principles: Architectural design. Distributed Systems Architecture, Object Oriented Design, Real Time
Software Design, User Interface Design.
Development and Testing: Rapid Software Development, Software Reuse with COTS
Technology, Component Base Software Engineering, Critical systems development, Clean Room software
Engineering ,System Testing
Verification and validation of Software: Software Inspections and Audit, Automates Analysis, CASE Tools
and
Critical systems validation
Software Quality Assurance, Quality Standards, Quality Planning and Control, Software Reliability Models,
Appendix C
Emerging Technologies: Security Engineering, Agile Methods, Service Oriented Software Engineering, Aspect
Oriented Software Development, Software Engineering Aspects of Programming Languages.
Self Learning Component
To be decided by course coordinator at the beginning of semester, which will be a blend of one or more of the
e-Learning Resources, Video Lectures, Online courses, tools, research material, web links etc. along with the
related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at least 5 experiments are to be carried out.
References
1. Software Engineering – Ian Sommerville (Addison – Wesley)
2. Software Engineering A Practitioners Approach – Roger Pressman (McGraw Hill Publication)
3. Fundamentals of Software Engineering – Rajib Mall (Prentice Hall of India)
4. Object Oriented Software Engineering A use case Approach -By Ivar Jacobson Pearson
3CS1107 Database Systems [3 – 1 4]
Learning outcome
• Understand database concepts and applications
• Understand storage organizations concepts
• Evaluate contemporary database architectures and database management issues
• Analyze and design efficient algorithms
Syllabus
Overview of Database Management System
Data storage: Using data storage efficiently, File Organization & Record formats, Heap sorted & Hashed Files,
other primary file of Indexing, Clustered-unclustered primary & secondary indexes, Multilevel Index, B+ Tree
Indexes & Operations, Hashing & Index,
Coping with Disk Failure, Index Structures for Single Dimensional and Multidimensional Databases Query
Execution, Algebra for Queries, Physical-Query-Plan-Operators, Algorithms for Database Operations,
Algorithms for Joins, Algorithms for Sorting, hash and Index Based Algorithms, Buffer Management, Parallel
Algorithms for Relational Operators.
Query Compiler: Algebraic Foundation for Improving Query Plans, Estimating Cost of Operations, Cost
Based Plan Selection, Choosing Order of Joins, Optimization of Queries for Parallel, Distributed,
Multidimensional and Text Database.
Coping with System Failure, Concurrency Control, Optimizing Locking Strategy, Handling Long Duration
Transactions, Distributed DBMS Reliability.
Information Integration, OLAP and Data Cube Operations.
Self Learning Component
To be decided by course coordinator at the beginning of semester, which will be a blend of one or more of the
e-Learning Resources, Video Lectures, Online courses, tools, research material, web links etc. along with the
related assessment component(s).
Laboratory Work
Practicals will be based on various administrative and tuning aspects in any latest database system or may be
also conducted by assigning project based on above fundamentals.
Appendix C
References:
1. Data Base System Implementation, Garcia Molina, Ullman, Widom, Pearson education
2. Database System Concepts, Silberschatz ,Korth,Sudarshan, Mc Graw Hill
3. Fundamentals of Database System, Ramez Elmasri, Shamkant B Navathe, Pearson Education
4. Database Management Systems, Raghu Ramakrishnan & Johannes Gehrke, McGraw Hill
5. Principles of Distributed Database Systems, M.Tamer Ozsu, Patrick Valduriez, S.Sridhar, Pearson
Education
3SP1103 Communication Skills for Engineers [- 1 - -]
Learning outcome
• Develop effective communication skills (spoken and written).
• They will be more aware of the dynamics behind effective communication.
• Develop effective recruitment skills.
• Conduct effective business correspondence.
• Students will be able to make professional presentations.
• Student will be able to shrug off the fear of public speaking to some extent.
Syllabus
Communication Skills: Communication cycle, types and flows of Communication, barriers to communication.
Non-verbal Communication and Cross-cultural communication
Listening Skills: Types of listening, Barriers to effective listening, tips to improve listening skills.
Business Communication: Various types of Letters and format, agenda and minutes of meeting, types of
memo and Resume and job application, Email etiquettes
Speaking Skills: Group Discussion, Personal Interview, Seminar Presentation
Writing Abstract, Research paper and Dissertation, Summarizing technical material , References and styling
Writing Business Proposal
Report Writing
References:
1. Basic Communication Skills for Technology – Andrea J Rutherford (Person)
2. Technical Writing Process and Product – Shron J. Gerson (Person)
3. Business Communication, Lesiker and Petit: MCGraw Hill Publications, 1995
4. Business Correspondence and Report Writing – R.C. Sharma, Krishna Mohan (Tata McGraw)
3CS1105 Comprehensive Assessment - I [- - - 1]
Learning Outcome
• Students will be able to realize the collective understanding of various courses studied in the semester.
Syllabus
Student will be assessed on the basis of all the courses learned till end of the respective semester.
3SP1104 ICT Tools [- 1 - 0]
Learning Outcome
At the end of the course, students will be:
• Aware of some of the latest ICT tools available for general purpose, academic and research use.
• Able to use ICT tools for application development / Research / Academic / Personal development in
the related field of study.
Syllabus
Appendix C
At least 5 tools have to be explored by the students as per their need to be decided in consultation with the
respective Course Coordinator for the respective Program.
Semester – II
3CS1202 Real Time Systems [3 - 1 4]
Learning outcome
• Knowledge of software and system design process for microcontroller based real time systems
• Knowledge of the inner workings of real time operating systems
• Gaining experience in programming of real time systems
• Able to assess and design fault tolerant systems
Syllabus
Introduction: Issues in Real Time Computing, Structure of a Real Time System. Task Classes, Performance
Measures for Real Time Systems, and Estimating Program Run times. Task Assignment and Scheduling:
Classical Uniprocessor scheduling algorithms, UniProcessor scheduling of IRIS Tasks, Task Assignment,
Mode Changes, and Fault Tolerant Scheduling.
Programming Language and Tools – Desired Language characteristics, Data Typing, Control structures,
Facilitating Hierarchical Decomposition, Packages, Run time (Exception) Error handling, Overloading and
Generics, Multitasking, Low Level programming, Task scheduling, Timing Specifications, Programming
Environments, Run time Support.
Real Time Databases: Basic Definition, Real time Vs General Purpose Databases, Main Memory Databases,
Transaction priorities, Transaction Aborts, Concurrency Control Issues, Disk Scheduling Algorithms, Twophase
Approach to improve Predictability, Maintaining Serialization Consistency, Databases for Hard Real
Time systems.
Real Time Communication: Communications Media, Network Topologies Protocols, Fault Tolerant Routing.
Fault Tolerance Techniques: Fault Types, Fault Detection. Fault Error containment Redundancy, Data
Diversity, Reversal Checks, Integrated Failure handling.
Reliability Evaluation Techniques: Obtaining Parameter Values, Reliability Models for Hardware Redundancy,
Software Error models.
Clock Synchronization: Clock, A Nonfault Tolerant Synchronization Algorithm, Impact of Faults, Fault
Tolerant Synchronization in Hardware, Fault Tolerant Synchronization in Software.
Self Learning Component
To be decided by course coordinator at the beginning of semester, which will be a blend of one or more of
the e-Learning Resources, Video Lectures, Online courses, tools, research material, web links etc. along with
the related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at-least 5 experiments are to be carried out.
References:
Appendix C
1. Real Time Systems by C.M. Krishna, Kang G. Shin, McGraw Hill International Editions.
2. Real Time Computer Control - An Introduction by Stuart Bennett, Prentice Hall PTR.
3. Real time Micro Computer System Design – An Introduction by Peter D. Lawrence, McGraw Hill.
4. Introduction to real time software design by S.T. Allworth and R.N. Zobel, Macmillan.
5. An Introduction to Real Time Systems by R.J.A Buhur, D.L. Bailey, Prentice Hall International.
6. Real Time System Design and Analysis by Philip. A. Laplante, PHI.
3CS1203 Compiler Design [3 – 1 4]
Learning Outcome
• To enable the students to understand the structure and the basics of implementing compilers for
programming languages used in High Performance Computing
Syllabus
Overview of Lexical analysis and Syntax analysis, Intermediate code generation, Syntax directed translation,
symbol table management and error handlers, Introduction to various Intermediate representation and Run
time support, Control flow analysis, Data flow analysis, Dependence analysis and dependence graphs,
Introduction to optimizations, Redundancy elimination, Loop optimizations, procedure optimizations,
Register allocation, introduction to code scheduling, control flow and low level optimizations
Self Learning Component
To be decided by course coordinator at the beginning of semester, which will be a blend of one or more of
the e-Learning Resources, Video Lectures, Online courses, tools, research material, web links etc. along with
the related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at least 6 experiments are to be carried out.
References
1. Steven S. Muchnick.Advanced Compiler Design Implementation, Morgan Kauffman Publishers,
1997.
2. Wolfe. High Performance Compilers for Parallel Computing.
3. Zima and Chapman.Supercompilers for Parallel and Vector Computers.
4. Utpal Banerjee. Dependence analysis for supercomputing.
5. Wolfe. Optimizing Supercompilers for Supercomputers.
6. Ellis.Bulldog: A Compiler for VLIW Architectures
3CS1204 Distributed and Parallel Systems [3 - 1 4]
Learning Outcome
• Students will understand the programming aspects of Parallel Architectures
• Students will be able to correlate the engineering in high computing standards
Syllabus
Introduction to Parallel and Distributed Programming
Parallel Computing Architectures, Advanced Processors and Interconnects - Multicore Processors and Highbandwidth
Networks, Paradigms & Issues
Scalable Multiprocessors and Multicomputers - Distributed CC-NUMA and cluster Scalability.
Physical and Virtual Clusters - Server clusters, high availability, and Disaster Recovery
Processes, inter-process communication, multithreaded programming, thread synchronization, and
programming parallel virtual machines (PVM and MPI), Concurrent programming primitives (semaphores,
locks, monitors)
Shared Memory Models and Distributed Memory Models
Distributed Programming Issues and Algorithms
Appendix C
Remote procedure calls, process management, migration, mobile agents, distributed coordination, fault
tolerance
Distributed File Systems, synchronization, fault tolerance, coordination and consensus, replication and
sharing, security
Peer-to-Peer Computing Systems: - P2P systems, Overlay networks, and Content Distribution.
Distributed Computing Tools & Technologies - P2P systems, TeraGrid, MapReduce, Clusters, Hadoop,
Twister, Dryad, BigTable, GFS
Self Learning Component
To be decided by course coordinator at the beginning of semester, which will be a blend of one or more of
the e-Learning Resources, Video Lectures, Online courses, tools, research material, web links etc. along with
the related assessment component(s).
Laboratory Work
Above concepts are to be implemented and at least 5 experiments are to be carried out.
References
1. Distributed Computing, Fundamentals, Simulations, and Advanced Topics by H. Attiya, J. Welch,
Wiley
2. Parallel Programming: Techniques and Applications Using Networked Workstations and Parallel
Computers, Barry Wilkinson and Michael Allen, Prentice Hall
3. Principles of Parallel Programming by Calvin Lin, Larry Snyder
4. K. Hwang and Z. Xu, Scalable Parallel Computing, McGraw-Hill
5. Ian Taylor: From P2P to Web Services and Grids, Springer-Verlag
6. F. Berman, G. Fox, and T. Hey (Editors), Grid Computing, Wiley
3CS1201 Research Seminar [- - 1 1]
Candidates have to select any Research Topic as Self Study for their Research Seminar. They will be required
to present the progress of their Study in front of the Reviewing Panel at Regular intervals. During the final
review, students are required to submit the report of Seminar.
3SP1204 Research Methodology [- 1 - -]
Learning outcome
• Ability to ascertain basic objectives and motivation of research for societal development.
• Ability to critically evaluate current research and propose possible alternate directions for further
work
• Awareness of various data collection and analysis using qualitative methods and modern data
processing tools
• Ability to develop hypothesis and methodology for research
• Ability to comprehend and deal with complex research issues in order to communicate their scientific
results clearly for peer review.
• Ability to document research work accomplished
Syllabus
Objective of research, motivation in research, types of research, interdisciplinary research, scientific methods
of research, criteria of good research, and characteristics of a good researcher.
Defining Research Problem: Art of literature review, user of ICT in effective literature review, formulation of
problem, formulation of hypothesis, developing research plan, meaning of research design, types of research
design, basic principles of experimental design, selection of relevant variables, validity of experiments.
Data Collection and Utilization: Types of data, methods & techniques of data collection, sampling,
characteristic of a good sample design, methods used in sampling, sampling errors, tests of hypothesis.
Appendix C
Quantitative Methods: Data presentation, statistical analysis and interpretation of data, types of analysis,
simple regression analysis, correlation, coefficient of determination (r2), z-test, t-test, ANOVA, Chi-square
test, multi-variate analysis of data, multiple regression.
Computer Application: Role of computer in research, data organization, software selection and its
applications, solving problems by using scientific software & tools, sample programmes for analysis of data.
Thesis Writing and Presentation: Significance of writing thesis, different types of research writing; conference
paper, journal paper, patents, thesis etc., different steps in writing thesis, layout of thesis, guidelines for
writing good thesis, precautions in writing thesis, presentations skills, defending the thesis.
References:
1. Research Methodology: Methods & Techniques by C R Kothari, 2e, Wishwa Publication, New Delhi
2. Research Methodology by D K Bhattacharyya, 1 e, Excel Books, New Delhi, 2003
3. How to Research by Loraine Blaxter, Christina Hughes and Molcolm Tight, Viva Books Pvt. Ltd.,
New Delhi
4. Writing Your Thesis by Paul Oliver, Vistaar Pulication, New Delhi, 2006
5. The Research Student’s Guide to Success by Pat Cryer, Viva Books Pvt Ltd., New Delhi
3CS1205 Comprehensive Assessment - II [- - - 1]
Learning Outcome
• Students will be able to realize the collective understanding of various courses studied in the
semester.
Syllabus
Student will be assessed on the basis of all the courses learned till end of the respective semester.
3SP1205 Network and Information Security [- 1 - 0]
Learning Outcome
At the end of the course, students will be able to:
• Understand the need of Security in our day to day communications.
• Identify obvious vulnerabilities in the network and computer system
• Motivated to identify and overcome the loop holes in the technologies
Syllabus
Internet Security: Working of Internet, Working of Hackers, Working of Spyware, Worms and Viruses,
Trojans and Zombies, Websites and privacy, Dangers of Internet Search, Phishing Attacks, Security Dangers
in Browsers, Wi-Fi security dangers and protections, Working of Spam, Denial of Service Attacks and
Protection, Introduction to Web Blocking and Parental Controls
Personal Privacy and Security: Working of Identity Thefts, Credit Card Security, Dangers of Workplace
Surveillance system, Hacking cell phones, Working of Biometrics, Working of Location Tracking, DNA
Matching, Working of Wiretapping and Lie Detectors
References
1. How Personal and Internet Security Work by Preston Galla, Que Publications
2. Computer Security Concepts, Issues and Implementation by Alfred Basta and Wolf Halton, Cengage
Learning
Semester – III
3SP1301 Practical Training [- - - - ]
Learning outcome
Appendix C
• Students will be oriented to decide upon the tools to be used in dissertation depending on their areas
of interest.
• Students will be ready for dissertation work.
Syllabus
During practical training of 4-6 weeks, students will learn required software tools/ methodologies, either in
industry/research organizations/academic institutions etc or there will be a planned in-house training by our
faculty members/experts from other organizations, which will help them in their PG dissertation work.
3CS1304 Project Part I [- - 30 13]
Learning outcome
• Students will be able to think creatively and independently.
• Students will be able to explore other facets of Research through new thinking and ideas.
• Students will be able to analyze systems and find problems.
• Students will be able to communicate effectively.
• Students will have an aptitude for optimization and enhancements in their area of specialization.
• Students will realize the need and importance of Research and the ethics involved in Research.
• Students will be better professionals.
Syllabus
The students will carry out a project with significant technical contribution either in the institute, any R&D
organization or Industry. At the end of the semester III, students will submit a report on the progress of his
work.
Semester – IV
3CS1401 Project Part II [- - 30 14]
Learning outcome
• Students will be able to think creatively and independently.
• Students will be able to explore other facets of Research through new thinking and ideas.
• Students will be able to analyze systems and find problems.
• Students will be able to communicate effectively.
• Students will have an aptitude for optimization and enhancements in their area of specialization.
• Students will realize the need and importance of Research and the ethics involved in Research.
• Students will be better professionals.
Syllabus
The student will continue the project work started in semester III and complete the work defined and submit
final dissertation for evaluation.
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