Download Phd-CSE-901: Communication Networks

Phd-CSE-901: Communication Networks
Note: Total 8 questions are to be set by the examiner/teacher covering the entire syllabus
uniformly. A candidate is required to attempt any five questions. All questions shall carry
equal marks.
Total Credits: 4
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4
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Time: 3 Hours
(Examination)
SYLLABUS
COMPUTER NETWORKS
Gigabit Ethernet: Overview of fast Ethernet, Gigabit Ethernet – overview,
specifications, layered protocol architecture, network design using Gigabit Ethernet,
applications, 10GB Ethernet – overview, layered protocol architecture, applications.
Wireless Networks: Existing and emerging standards, Wireless LAN(802.11),
Broadband Wireless(802.16), Bluetooth(802.15) their layered protocol architecture and
security.
MOBILE NETWORKS
Mobile Network Layer: Mobile IP - goals, assumption, requirement, entities,
terminology, IP packet delivery, Agent advertisement and discovery, registration,
tunneling, encapsulation, optimization, reverse tunneling, IPV6.
DHCP. Adhoc Networks - routing, destination sequence distance vector, dynamic
source routing, hierarchical algorithm, alternative metric.
Mobile Transport Layer: Traditional TCP, Indirect TCP, Snooping TCP, Mobile TCP
fast retransmission/ recovery, transmission/time out freezing, selective retransmission,
Transaction oriented TCP.
References:
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“Building high speed Networks”, Tere Parnell, TMH.
“ High Speed Networks and Internets”, William stalling, Pearson Education.
Jochen Schiller,” Mobile Communication” , Pearson Education,2002.
Lee, “ Mobile Cellular Telecommunications” McGRAW- WILL, 2nd Edition.
Phd-CSE-902: Data Mining and Applications
Note: Total 8 questions are to be set by the examiner/teacher covering the entire syllabus
uniformly. A candidate is required to attempt any five questions. All questions shall carry
equal marks.
Total Credits: 4
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4
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Time: 3 Hours
(Examination)
SYLLABUS
Introduction to data mining, data preprocessing, Data mining functionalities- Cluster
analysis, Association analysis, classification and prediction, characterization and
discrimination, outlier analysis, Evolution analysis, classification of data mining system,
Major issues in data mining.
Data mining: Models and techniques such as predictive techniques, classification
techniques, text mining etc.
Data Mining and Knowledge Discovery.
Data Mining Applications and Case Studies such as data mining and network
management, data mining in health care management, data mining in banks, data mining
in insurance etc
Study of few data mining software with practical exposure along with study of atleast
five research papers.
References:
1. Sashikala Parimi, “Data mining”, Vol. I & II, ICFAI University Press.
2. Data Mining- Concepts & Techniques; Jiawei Han & Micheline Kamber- 2001,
Morgan Kaufmann.
3. Data Mining Techniques; Arun Pujar; 2001, University Press; Hyderbad.
4. Data Mining; Pieter Adriaans & Dolf Zantinge; 1997, Pearson.
Phd-CSE-903: Soft Computing
Note: Total 8 questions are to be set by the examiner/teacher covering the entire syllabus
uniformly. A candidate is required to attempt any five questions. All questions shall carry
equal marks.
Total Credits: 4
Time: 3 Hours
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(Examination)
4
SYLLABUS
Introduction to Genetic Algorithms: Basic definitions and fundamentals of evolutionary
algorithms , Working principals of GA, Genome representations, Selection Schemes, GA
operators, Fitness Function. Binary encoding, real encoding and permutation encoding.
Application of GAs to function optimization and data mining.
Implementing a Simple GA in C/C++/JAVA. Genetic algorithm libraries and tools.
Mathematical foundations of GA, Building block hypothesis, Schema theorem.
Scaling mechanism, Multi-objective optimization, Niching, Speciation and crowding.
Parallelism in Genetic Algorithms: Master Slave GA, Island/course grained PGA,
Hierarchical PGA and Fine grained GAs.
Introduction to genetic based systems: Classifier systems, rule and message system,
bucket brigade algorithm
An introduction to rough sets: definitions, lower and upper approximations, reduct, core,
mining rules using rough sets
An introduction to fuzzy sets and operations, fuzzification and defuzzification.
References:
1. Genetic Algorithms in search, optimization and machine learning, David E. Goldberg,
Addison Wesley, 1999.
2. Michalewicz Z., Genetic Algorithms + Data Strucutres = Evolutionary Programs,
Springer Verlag, 3rd edition.
3. Designing efficient parallel genetic algorithms, E. Cantu-Paz, Kluwer Academic
Publishers.
4. Advances in soft Computing Rough Sets, Lech Polkowski, Physica-Verlag.
5. Rough Sets: Theoretical aspects of reasoning about data, Kluwer Academic Press.
6. “Neuro-Fuzzy and Soft Computing” J.-S.R. Jang, C.-T. Sun, E. Mizutani, Prentice
Hall, 1997.
Phd-CSE-904: Software Testing and Quality Assurance
Note: Total 8 questions are to be set by the examiner/teacher covering the entire syllabus
uniformly. A candidate is required to attempt any five questions. All questions shall carry
equal marks.
Total Credits: 4
L
T
P
4
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Time: 3 Hours
(Examination)
SYLLABUS
A perspective on Testing, STLC, Functional testing: Boundary value testing, Equivalence
–class testing, Decision Table Testing etc., Retrospective on Functional Testing;
Structural testing: path testing, data flow testing, mutation testing, etc. Retrospective
testing, Levels of testing: Integration testing, system testing, acceptance testing, Objectoriented Testing, Interaction testing, Testing of Web Applications, Testing metrics,
Testing Paradigms: Scripted testing, Exploratory testing, Test planning, Supporting
Technologies: Defect taxonomies, Testing tools and standards, Case studies.
Introduction to Software Quality, Quality Models: McCall’s Model , Hierarchical model
FCMM , Measuring Software Quality, Quality Metrics: Process, Product, Quality Control
Tools, Quality assurance concept, importance, Requirements for SQA works, Pareto
Principle to SQA, Costs of Software Quality, SQA metrics, Audit Review, Walk
through, Inspection techniques, SQA plan., Quality standards: SEI-CMM, ISO 9000
series, comparison between SEI CMM and ISO 9000.
References:
1) A Practitioner’s Guide to Test Case Design by LEE Copland , Artech House
Publishers, Boston - London.
2) Software Testing – A Craft’s man Approach, Paul C. Jorgensen , A CRC Press LLC.
3) Software Quality Theory and Management by Alan C. Gillies, Chapman & Hall.
4) Software Quality by Galrry S. Marliss , Thomson.
5) Metrics and Models in Software Quality Engineering by Stephen H. Kan , Pearson
Education.
6) Handbook of Software Quality Assurance by G. Gordon Sculmeyer, Artech House
Publishers, Boston –London.
Phd-CSE-905: Information Processing and Data Hiding
Note: Total 8 questions are to be set by the examiner/teacher covering the entire syllabus
uniformly. A candidate is required to attempt any five questions. All questions shall carry
equal marks.
Total Credits: 4
L
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4
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Time: 3 Hours
(Examination)
SYLLABUS
Format of Image, Video and Audio
Different formats of multimedia files such as images, videos and audios will be studied
Search Engine Strategies
How search engine works? How to make information accessible on net? How to get
better rating and preference in search engines?
Information Compression
Different information compression algorithms and their working, Information Storage,
Redundancy.
Information Security
Cryptography, Key exchange methods such as public and private key, Digital Signatures
Steganography
History of steganography, Hiding data in multimedia files, Least significant bit method,
Latest algorithms for data hiding. Comparison of different steganographic techniques,
Applications of steganography
Watermarking
Copy right protection mechanisms, Latest Watermarking Algorithms, Comparison of
watermarking techniques, Applications of Watermarking
Fingerprinting
Latest Algorithms for fingerprinting, Fingerprinting protocols, Codes for Fingerprinting.
Boneh –Shaw fingerprinting scheme, Applications of Fingerprinting
References:
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Disappearing Cryptography: Being and Nothingness on the Net
Wayner, Peter. 1996
Information Hiding: Steganography and Watermarking - Attacks and
Countermeasures (Advances in Information Security, Volume 1)
Johnson, Neil F. / Duric, Zoran / Jajodia, Sushil G. 2001.
Information Hiding: Techniques for Steganography and Digital Watermarking ,
Katzenbeisser, Stefan / Petitcolas, Fabien A. P. 2000
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“ Security in Computing (Second Edition)”, Charles P. Pfleeger, Prentic- Hall
International, Inc., 1996.
“ Applied Cryptography Protocols, Algorithms, and Source Code in C (Second
Edition)”, Bruce Schneier, John Wiley & Sons, Inc., 1995.
“ Security Technologies for World Wide Web”, Rolf Oppliger, Artech House:
Inc.
“Introduction to Cryptography with Coding Theory”, Wade Trappe, Lawrence
C. Washington, Pearson Education.
“Network Security: Complete Reference”, TMH
Phd-CSE-906: Performance Modeling and Evaluation
Note: Total 8 questions are to be set by the examiner/teacher covering the entire syllabus
uniformly. A candidate is required to attempt any five questions. All questions shall carry
equal marks.
Total Credits: 4
L
T
P
4
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Time: 3 Hours
(Examination)
SYLLABUS
The queuing paradigm, Single queuing systems.
M/M/1, M/M/1/N, M/M/∞, M/M/m, M/M/m/m, M/G/1 queuing systems
Networks of queues, Numerical solutions of models, Simulation of Communication
Networks.
Discrete time queuing systems.
Network traffic modeling.
References:
1. Thomas G. Robertazzi, “ Computer Networks and Systems- Queuing Theory and
Performance Evaluation”, 3rd edition, Springer.
2. Kishore S. Trivedi, “Probability & Statistics with Reliability, Queuing and Computer
Sc. Applications”, PHI.