Nirma University
Institute of Technology
Computer Science and Engineering Department
M.Tech. CSE (Networking Technologies)
Detailed Syllabus
Semester – I
3CS1103 Data Structure and Algorithms [3 – 1 4]
Learning outcome
• Describe the usage of various data structures.
• Explain the operations for maintaining common data structures.
• Recognize the associated algorithms’ operations and complexity.
• Analyse 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, PHI
2. Introduction to Algorithms, by Thomas Cormen, Prentice-Hall India
3. Data structure and Algorithms, by Trembly and Sorenson
3CS3103 Communication Techniques [3 1 - 4]
Learning outcome
• Fundamentals in analog and digital communication system
• Application of probability and random processes in communication systems
• Learn various modulation techniques, multiplexing techniques
• Develop the ability to compare and contrast the strengths and weaknesses of various communication
Appendix D
Systems
• Understand the different channel coding methods
• Different radio propagation issues in communication systems
Syllabus
Probability and random variables, functions of one random variable, two random variables, stochastic
processes, stationary, non-stationary and ergodic processes,
Modulation and Coding Trade-Offs: Goals of the Communications system Designs- Error Probability Plane-
Nyquist Minimum Bandwidth- Shannon –Hartley Capacity theorem- Bandwidth Efficiency Plane- Modulation
and Coding Trade –Offs- Design and Evaluation of Digital Communication Systems- Bandwidth –Efficient
Modulation, Modulation and Coding for Band limited channels- Trellis-Coded Modulation .
Synchronization: Introduction- Receiver Synchronizer- Network Synchronization
Multiplexing and Multiple Access: Allocation of the Communications Resource- Multiple Access
Communications System and Architecture- Access Algorithms
Information and coding theory: Entropy, channel capacity, Vector spaces, basis, independence, linear codes,
block codes, convolutional codes, viterbi decoding, turbo codes, LDPC codes.
Fading Channels: Introduction - Characterizing Mobile-Radio Propagation- - Signal Time –Spreading,- Time
Variance of the Channel Caused by Motion- Mitigating the Degradation Effects of Fading- Key Parameters
Characterizing Fading Channels,- Mitigating the Effects of Frequency-Selective channel.
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).
Tutorial
A minimum of eight assignments based on the topics of the syllabus and the recent trends in the area will be
assigned to the students.
References
1. Digital Communications: Design for the Real World, Andy Bateman, Prentice Hall
2. Digital communications: fundamentals and applications, Bernard Sklar, Prentice Hall
3. Digital Communications, Proakis, McGraw-Hill
4. Probability, random variables and stochastic processes, Papoulis, McGraw-Hill
5. Error control coding , Shu Lin, Pearson Education
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
Appendix D
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
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, Prentice
Hall
2. High Performance TCP/IP Networking: Concepts, issues and solutions: By Mahoob Hassan Raj and Jain,
PHI
3. High-speed networks: TCP/IP and ATM design principles by William Stallings, Prentice Hall
4. High speed networks by Marc Boisseau, Michel Demange, Jean-Marie Munier, Wiley
5. Multimedia Communications: Applications, Networks, Protocols and Standards, Fred Halsall,
Addison –Wesley
3CS3104 Advance Computing Systems [3 - 1 4]
Learning outcome
• Fundamentals of parallel scientific computing
• Study various parallel architectures and programming models
• Understanding of various issues like load balancing, communication, and synchronization overhead for
HPC systems
• Knowledge of techniques/methods for energy aware computing
Syllabus
Requirements and General Issues of High performance computing,
Overview of Parallel Processing Concepts, Levels of parallelism (instruction, transaction, task, thread,
memory, function), Models(SIMD, MIMD, SIMT, SPMD, Dataflow Models, Demand-driven Computation
etc), Architectures: N-wide superscalar architectures, multi-core, multi-threaded
Scheduling Parallel jobs on HPC systems, Run time parallelization, Job and Resource Management Systems
Constructing Scalable Services, Performance Models and Simulations, Meta-Computing: Harnessing Informal
Supercomputers, Specifying Resources and Services in Meta-Computing Systems
Load Balancing over High Speed Networks, Network RAM, Distributed Shared Memory
Programming languages extensions for HPC, Execution profiling, timing techniques, and benchmarking for
modern single-core and multi-core processors
Power-Aware Computing and Communication: Power-aware Processing Techniques, Power-aware Memory
Design, Power-aware Interconnect Design, Software Power Management
Advanced Topics: Petascale Computing, Optics in Parallel Computing, Quantum Computers, Recent
developments in the area of High Performance Architectures and its impact on HPC
Appendix D
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 Performance Cluster Computing Architectures and Systems– By Rajkumar Buyya, Prentice Hall
PTR
2. Software Optimization for High Performance Computing: Creating Faster Applications" by K.R.
Wadleigh and I.L. Crawford, Hewlett-Packard professional books, Prentice Hall.
3. Sourcebook of Parallel Programming" by J. Dongara, I. Foster, G. Fox, W. Gropp, K. Kennedy, L.
Torczon, and A. White (eds), Morgan Kaufmann.
4. Advanced Computer Architecture: Parallelism, Scalability, Programmability", by Kai Hwang, McGraw
Hill
5. Petascale Computing: Algorithms and Applications, David A. Bader (Ed.), Chapman & Hall/CRC
Computational Science Series
6. Parallel Computer Architecture: A hardware/Software Approach, by David Culler Jaswinder Pal
Singh, Morgan Kaufmann
7. Scalable Parallel Computing", by Kai Hwang, McGraw Hill
8. Research Papers on advanced topics from Journals/Conference Proceedings
3CS1105 Information and Network Security [3 – 1 4]
Learning Outcome
• Students will be able to relate the Operating System Development from the Security Perspective
• Students will have an understanding about the various attacks and their counter-measures
• The subject will enable students to realize the Security concern from the initial phase of application
development.
Syllabus
Protection and in Operating systems, memory and addressing, protecting objects and files, user authentication,
security in distributed systems, design of trusted operating systems, encryption algorithms, Encrypted file
systems. Network security architectures, IP security, Firewall engineering, Encapsulating payloads,
authentication header, key exchange, Security in wireless networks access control, WPA, RSN, RADIUS etc.
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 Security by Charles Pflegger and Pflegger
2. IPSec by N. Doraswamy and Dan Harkins
3. Cryptography and Network Security by William Stallings, PHI
Appendix D
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
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).
References
1. Basic Communication Skills for Technology – Andrea J Rutherford, Pearson
2. Technical Writing Process and Product – Shron J. Gerson, Pearson
3. Business Communication, Lesiker and Petit: MCGraw Hill Publications,
4. Business Correspondence and Report Writing – R.C. Sharma, Krishna Mohan, TMH
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 - -]
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
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.
Appendix D
Semester – II
3CS3201 Network Embedded Systems [3 - 1 4]
Learning Outcome:
• Students will learn the fundamentals of embedded systems programming, real-time operating
systems
• Students will develop understanding of power-aware protocols for networks of small devices
• Exposure to a large set of newly developed methods in embedded systems and ubiquitous
computing
Syllabus
Introduction to Networked Embedded Systems, Embedded Distributed Systems, Embedded Processors
Overview, Operating Systems for Communication-Centric Devices, Sensor Network Applications, Sensor
Network Platforms, Embedded Systems Programming, Signal Behaviors and Sensor Interfaces, Location
Discovery Algorithms, Localization Techniques, Time Synchronization and Calibration, Radio Technologies
and Medium access protocols, Data Aggregation, Clustering and Aggregation, Mobility and Collaborative
Control, Collaborative Signal Processing, Robust Embedded Networking, IP-based Wireless Sensor
Networks, 6LoWPAN and IP Concepts, Constrained Application Protocol with 6LoWPAN, Embedded Web
Services, Security Issues and Data Integrity for Wireless Embedded Systems, Firmware and Applications for
the Internet of Things
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. Principles of Embedded Network Design, Pottie and Kaiser, Cambridge University Press
2. Wireless Sensor Networks, An Information Processing Approach, Zhao and Guibas, Morgan
Kaufmann
3. Analysis, Instrumentation, and Visualization of Embedded Network Systems: A Testbed-based
Approach, Andrew Ryan Dalton, ProQuest
4. Embedded, Everywhere: A Research Agenda for Networked Systems of Embedded Computers,
National Academies Press
3CS3202 Information Retrieval System [3 - 1 4]
Learning outcome
• Develop understanding of concepts, algorithms, data/file structures necessary to design, and implement
Information Retrieval (IR) systems
• Learn methodology for the design and evaluation of information retrieval systems
• Learn about major types of information retrieval systems, the different theoretical foundations underlying
these systems
• Develop the practical skills for information retrieval systems
Appendix D
Syllabus
Overview of IR Systems, Architecture of information retrieval systems
Document Representation: Statistical Characteristics of Text, Basic Query Processing.
Data Structure and File Organization for IR, Retrieval Models: Similarity Measures and Ranking, Boolean
Matching, Vector Space Models, Probabilistic Models, Automatic Indexing and Indexing Models
Search and Filtering Techniques: Relevance Feedback, User Profiles, Collaborative Filtering
Automatic classification, Document and Term Clustering, Document Categorization
Heuristic classification, Nearest Neighbor, Naive Bayes Methods, Support Vector Machines
Machine Learning Techniques in IR, Neural Networks, Genetic Algorithms, Symbolic Learning
Indexing and storage issues, Information visualization and usage pattern analysis
IR Systems and the WWW, PageRank and Hyperlink Analysis, Search Personalization
N-Grams in Information Retrieval, Agent-based Information Retrieval
Parallel and Distributed IR, Multimedia IR: Models and Languages
Cross-Language and Multilingual Information Retrieval, Retrieval from noisy documents
Performance Evaluation of Information Retrieval Systems
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. Introduction to Information Retrieval. C.D. Manning, P. Raghavan, H. Schütze, Cambridge UP
2. Modern Information Retrieval. R. Baeza-Yates, B. Ribeiro-Neto, Addison-Wesley
3. Information Retrieval: Algorithms and Heuristics, D.A. Grossman, O. Frieder, Springer
4. Language Modeling for Information Retrieval. W.B. Croft, J. Lafferty, Springer
5. Information Storage and Retrieval Systems. G. Kowalski, M.T. Maybury, Springer
6. A Semantic Web Primer Grigoris Antoniou and Frank van Harmelen, The MIT Press
7. Information Retrieval in Practice. B. Croft, D. Metzler, T. Strohman, Pearson Education
3CS3203 Wireless Networks [3 - 1 4]
Learning outcome
• Fundamentals of wireless communications: channel capacity, antennas, signal fading, encoding, spread
spectrum
• build understanding of all layers of wireless networking and the interactions between them
• Learn about security, energy efficiency, mobility, scalability, and their unique characteristics in wireless
networks
• Learn basics of Cellular networks and various issues like channel allocation, Capacity planning
• TCP/IP extensions for mobile and wireless networking
Fundamentals of Wireless Communication; Wireless LAN, PAN, WAN and MAN; Wireless Internet
Cellular Networks, GSM, Channel allocation, Network planning, Security, CDMA, DSSS, Spreading code, IS-
95 Standard, Mobile IP, Cellular IP, GPRS: Architecture and role of the components, Wireless Ad-hoc
Networks: Introduction; Game theory, MAC, Network and Transport layer protocols; QoS, Security and
Energy Management, Topology management, Mobility models
Self Learning Component
Appendix D
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. Ad Hoc Wireless Networks – Architectures an Protocols by C. Siva Ram Murthy and B.S. Manoj,
Pearson Education
2. Wireless Ad hoc Network by Perkins, Pearson Education
3. Mobile Communications by Jochen Schiller, Pearson Education
4. Wireless Communications: Principles and Practice by Theodore Rappaport, Prentice Hall
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 and present the 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.
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
Appendix D
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, Wishwa Publication, New Delhi
2. Research Methodology by D K Bhattacharyya, Excel Books, New Delhi
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 Publication, New Delhi
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.
Semester – III
3SP1301 Practical Training [- - - - ]
Learning Outcome
• 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.
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, that will help them in their PG dissertation work.
3CS1301 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.
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.
Appendix D
• 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.
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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