SCHEME OF EXAMINATION FOR M.TECH. (COMPUTER SCIENCE & ENGINEERING) w.e.f. Academic Session 2014-15

Paper Code

Nomenclature of Paper

 

 

Exam

External

Internal

Total

 

 

 

 

 

Time

Marks

Marks

 

 

 

 

 

Marks

 

 

 

 

 

(hrs.)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Max

Pass

Max

Pass

 

 

 

 

 

 

 

 

 

 

 

 

 

 

FIRST SEMESTER

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-11

ADVANCES IN ALGORITHMS

 

 

3

100

40

50

20

150

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-12

ADVANCED WEB TECHNOLOGIES

 

 

3

100

40

50

20

150

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-13

DATA WAREHOUSING & DATA MINING

 

 

3

100

40

50

20

150

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-14

ADVANCED COMPUTER ARCHITECTURE

 

 

3

100

40

50

20

150

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-15

S/W LAB – I BASED ON MT-CSE-14-11

 

 

3

100

40

 

 

100

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-16

S/W LAB – II BASED ON MT-CSE-14-12

 

 

3

100

40

 

 

100

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-17

SEMINAR

 

 

 

 

 

 

50

20

50

 

 

 

 

 

 

 

 

 

 

 

 

 

 

TOTAL

 

 

600

 

250

 

850

 

 

 

 

 

 

 

 

 

 

 

 

 

SECOND SEMESTER

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-21

OBJECT ORIENTED ANALYSIS & DESIGN USING UML

 

3

100

40

50

20

150

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-22

DIGITAL IMAGE PROCESSING

 

 

3

100

40

50

20

150

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-23

ELECTIVE - I

 

 

 

3

100

40

50

20

150

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-24

ELECTIVE - II

 

 

 

3

100

40

50

20

150

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-25

S/W LAB – III BASED ON MT-CSE-14-21

 

 

3

100

40

 

 

100

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-26

S/W LAB – IV BASED ON MT-CSE-14-22

 

 

3

100

40

 

 

100

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-27

SEMINAR

 

 

 

 

 

 

50

20

50

 

 

 

 

 

 

 

 

 

 

 

 

 

 

TOTAL

 

 

600

 

250

 

850

 

 

 

 

 

 

 

 

 

 

 

ELECTIVE PAPERS

 

 

 

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14- 23(i) SOFTWARE QUALITY MODELS & TESTING

MT-CSE-14-24(i) DISTRIBUTED SYSTEMS

 

 

 

 

 

MT-CSE-14-23(ii) HIGH PERFORMANCE NETWORKS

MT-CSE-14-24(ii) BIOMETRICS SYSTEM SECURITY

 

 

 

 

 

MT-CSE-14-23(iii) ADVANCES IN DATABASES

 

MT-CSE-14-24(iii) SECURITY IN COMPUTING

 

 

 

 

 

 

 

 

 

 

 

 

 

 

THIRD SEMESTER

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-31

RESEARCH METHODOLOGY & TOOLS

 

 

3

100

40

50

20

150

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-32

ADVANCED OPERATING SYSTEMS

 

 

3

100

40

50

20

150

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-33

ELECTIVE – I

 

 

 

3

100

40

50

20

150

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-34

ELECTIVE - II

 

 

 

3

100

40

50

20

150

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-35

S/W LAB – V BASED ON MT-CSE-14-31

 

 

3

100

40

 

 

100

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-36

S/W LAB – VI BASED ON MT-CSE-14-32

 

 

3

100

40

 

 

100

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-37

SEMINAR

 

 

 

 

 

 

50

20

50

 

 

 

 

 

 

 

 

 

 

 

 

 

 

TOTAL

 

 

600

 

250

 

850

 

 

 

 

 

 

 

 

 

 

 

ELECTIVE PAPERS

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-33(i) DATA ANALYTICS

MT-CSE-14-34(i) CLOUD COMPUTING

 

 

 

 

 

 

 

MT-CSE-14-33(ii) SOFT COMPUTING

MT-CSE-14-34(ii) WIRELESS NETWORKS AND MOBILE COMPUTING

 

 

 

MT-CSE-14-33(iii) GENETIC ALGORITHMS

MT-CSE-14-34(iii) SEMANTIC WEB AND SOCIAL NETWORKING

 

 

 

 

 

 

 

 

 

 

 

 

FOURTH SEMESTER

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

MT-CSE-14-41

DISSERTATION

EVALUATION

 

 

200

80

100

40

300

 

 

 

 

 

 

 

 

 

 

 

 

VIVA-VOCE

 

 

150

60

 

 

150

 

 

 

 

 

 

 

 

 

 

 

 

 

 

TOTAL

350

 

100

 

450

 

 

 

 

 

 

 

 

 

 

 

 

GRAND TOTAL

2150

 

850

 

3000

 

 

 

 

 

 

 

 

 

 

 


Seminar

 

Each student shall individually prepare and submit a seminar report within stipulated time. A panel consisting of two teachers (internal) should evaluate the seminar report and the presentation. Marks should be distributed considering report writing, presentation, technical content, depth of knowledge, brevity and references and their participation in seminar. The time allotted for presentation is 30 minutes.


 

 

 

MT-CSE-14-11              ADVANCES IN ALGORITHMS

 

Maximum marks: 150 (External: 100, Internal: 50)                                             Time: 3 hours

 

Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks.

 

UNIT – I

 

Algorithms: Role of algorithm in computing, Asymptotic Notations, Standard notations and common functions.

 

Recurrence: The maximum-subarray problem, Strassen's algorithm for matrix multiplication, substitution and recursion-tree method for solving recurrences, master method for solving recurrences, Proof of the master theorem, Probabilistic Analysis and Randomized Algorithms.

 

UNIT – II

 

Sorting: Bubble sort, Heap, Building and maintaining heap, Heapsort, Quicksort, Lower bounds for sorting, Counting sort, radix sort, bucket sort.

 

Advanced Data Structures: Splay Trees, Top-down splay trees, Red-black Trees, Deterministic skip lists, AA-Trees, Trie, Treaps, K-d Trees.

 

UNIT – III

 

Advanced Design and Analysis: Dynamic Programming: matrix-chain multiplication, Longest common subsequence, optimal binary search tree, Greedy algorithms: Huffman codes.

 

Graph Algorithms: Storage of graphs, traversing a graph, Topological sort, Minimum Spanning Trees, Shortest path problems: Single source and All-pairs shortest path, Maximum Flow networks, matching in bipartite graphs.

 

UNIT – IV

 

Miscellaneous Topics: Knapsack Problem and Memory functions, Approximate String Matching, Chinese remainder theorem, Integer factorization, naïve-string matching, Rabin-karp string matching, String matching with finite automata, Knuth-moris-pratt algorithm, finding convex hull, Polynomial time, verification and reducibility, NP-completeness and proofs.

 

Text Books:

 

1.      Cormen, Thomos, Leiserson, “Introduction to Algorithms”, Prentice Hall of India Learning.

 

2.      Horowitz, Ellis and Sahni, Sartaj, “Fundamentals of Computer Algorithms”, University Science Press.

 

Reference Books:

 

2.      Anany Levitin, “Introduction to Design and Analysis of Algorithms”, Pearson Education.

 

3.      Cooper A., “Computability Theory”, Chapman and Hall/ CRC Press.

 

4.      Robert Sedgewick, “Algorithms”, Pearson Education India.

 

5.      Steven Skiena, “The Algorithm Design Manual”, Springer India.

 

6.      Reiter, Johnson, “Limits of Computation”, Chapman and Hall/ CRC Press.


MT-CSE-14-12              ADVANCED WEB TECHNOLOGIES

 

Maximum marks: 150 (External: 100, Internal: 50)                                              Time: 3 hours

 

Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks.

 

UNIT – I

 

Introduction: Web Browsers, Caching, Downloading and Rendering, Persistent Connections, DNS caching and prefetching, CSS Expressions and performance, Buffering, Weblog

 

Optimization and Security: Parallel Downloading, Controlling caches, Content compression, Control size with minification, Optimizing images, Load balancers, Tuning MYSQL, Using query caching, Optimizing query execution and optimization, Marketing of Website: traffic generation, Newsletters; Security: SQL: query log, SQL injections.

 

UNIT – II

 

Search engines: Searching techniques used by search engines, keywords, advertisements, Search engine optimization for individual web pages: header entries, tags, selection of URL, alt tags, Search engine optimization for entire website: Hyperlinks and link structure, page rank of Google, click rate, residence time of website, frames, scripts, content management system, cookies, robots, Pitfalls in Optimization: optimization and testing, keyword density, doorway pages, duplicate contents, quick change of topics, broken links, poor readability, rigid layouts, navigation styles; tools for optimization: etracking, Google analytics, checklists.

 

UNIT – III

 

Introduction to JavaScript: Introduction, Obtaining user inputs, memory concepts, Operators, Control Structures, Looping constructs, break, continue statements, Programmer defined functions, Scoping rules, Recursion and iteration, Array declaration and allocation, passing arrays to function, Objects: String, Date, Boolean, Window, document; using cookies, Handling Events Using JavaScript.

UNIT – IV

 

Introduction to PHP: Installing and Configuring MySQL and PHP, Basic Security Guidelines, Variables, Data Types, Operators and Expressions, Constants, Flow Control Functions; Switching Flow, Loops, Code Blocks and Browser Output, Objects, Strings Processing, Form processing, Connecting to database, using cookies, dynamic contents.

 

Text Books:

 

1.    Peter Smith, “Professional Website performance”, Wiley India Pvt. Ltd.

 

2.    Maro Fischer, “ Website Boosting: Search Engine, Optimization, Usability, Website Marketing”, Firewall Media, New Delhi.

 

3.    Deitel H.M., Deitel P.J., “Internet & World wide Web: How to program”, Pearson Education.

 

Reference Books:

 

1.      Kogent Learning, “Web Technologies: HTML, JavaScript, PHP, Java, JSP, XML, AJAX – Black Book”, Wiley India Pvt. Ltd.

 

2.      Boronczyk, Naramore, “Beginning PHP, Apache, MySQL Web Development”, Wiley India Pvt. Ltd.


MT-CSE-14-13

DATA WAREHOUSING & DATA MINING

 

Maximum marks: 150 (External: 100, Internal: 50)

Time:

3 hours

 

Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks.

 

UNIT – I

 

Data Warehousing: Need for Data Warehousing, Paradigm Shift, Operational and Informational Data Stores, Data Warehouse Characteristics, Architecture for a Data Warehouse Data Warehouse Sourcing, Acquisition, Cleanup and Transformation tools, Metadata, Access Tools, Data Marts. OLAP Tools: Need for OLAP, Multidimensional Versus Multi relational OLAP, Categorization of OLAP tools, OLAP operations, Identifying Facts and Dimensions, Designing Fact Tables, Designing Dimension Tables

 

Building a Data Warehouse: Data Warehouse Schemas. Steps for the Design and Construction of Data Warehouses. Business consideration, Design consideration, Technical consideration, Integrated Solutions.

 

UNIT – II

 

Data Mining: Introduction: Motivation, Knowledge Discovery Process, Kind of Data, Data Mining Functionalities, Interesting Patterns, Classification of Data Mining Systems, Major issues.

 

Data Preparation: Preprocess, Data Cleaning, Data Integration and Transformation, Data Reduction. Data Mining Primitives, Languages, and System Architectures. Concept Description and Data Generalization by Attribute-Oriented Induction.

 

UNIT – III

 

Mining Frequent patterns, Associations and Correlations: Market Basket Analysis, Frequent Itemsets, Closed Itemsets and Association Rules, Frequent Itemset Mining Methods, Pattern Evaluation Methods.

 

Decision Tree: Basics, Building a Decision Tree, Classifying by using Decision Trees, Building Multiple Decision Trees, Obtaining Prules from Decision Trees.

 

UNIT – IV

 

Clustering: Clustering in Grouping, Agglomerative Hierarchical Clustering, K-means Clustering. Multilayer Neural Nets: Neurodes, Modelling an AND Gate, Or Gate and XOR Gate. Commonly used Neunet Architecture.

 

Nearest Neighbour Classification: Performance of Nearest Neighbour classifier, Modification of Nearest Neighbour Classifier.

 

Text Books:

 

1.    A. Berson, S.J. Smith, “Data Warehousing, Data Mining & OLAP”, Tata McGraw-Hill.

 

2.    J Han, M. Kamber and J. Pei, “Data Mining Concepts and Techniques”, Elsevier India.

 

Reference Books:

 

1.    Rajjan Singhal, “Pattern Recognition Techniques and Applications”, Oxford University Press.

 

2.    Zhao Y., Cen Y., “Data mining Applications with R”, Elsevier India.


MT-CSE-14-14

ADVANCED COMPUTER ARCHITECTURE

Maximum marks: 150 (External: 100, Internal: 50)

Time: 3 hours

 

Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks.

 

UNIT-I

 

Instruction Level Parallelism (ILP): Data dependences and hazards – data dependences, control dependences; Basic Compiler Techniques for Exposing ILP – basic pipeline scheduling and loop unrolling, reducing branch costs with advanced branch prediction, overcoming data hazardous with dynamic scheduling, Tomasulo’s approach, hardware based speculation; Exploiting ILP using Multiple issue and Static Scheduling – VLIW & Superscalar processors, Advanced techniques for Instruction Delivery and Speculation; Limitations of ILP.

 

UNIT-II

 

Data Level Parallelism in Vector, SIMD & GPU Architectures: Vector Architecture – working of vector processors, vector execution time, multiple lanes, vector registers, memory banks, stride, gather-scatter; SIMD Instruction Set Extensions for Multimedia; Graphics Processing Units, Vector architecture vs GPUs, Multimedia SIMD v/s GPUs; detecting and enhancing Loop-Level Parallelism – finding dependences, eliminating dependent computations

 

Thread-Level Parallel Parallelism: Multiprocessor Architecture – centralized shared-memory architectures, cache coherence problem, schemes enforcing coherence, snooping coherence protocol; Extensions to basic coherence protocol; Distributed Shared-Memory and Directory-Based Coherence

UNIT-III

 

Warehouse-Scale Computers (WSC) to Exploit Request-Level and Data-Level Parallelism: Programming models and workloads for WSC, architecture of warehouse-scale computers, physical infrastructure and costs of WSC; Cloud Computing.

 

Memory Hierarchy: Cache performance – average memory access time & processor performance, miss penalty and out-of-order execution processors, cache optimizations; Virtual Memory – fast address translation, selecting page size, protection of virtual memory

 

UNIT-IV

 

MIMD Architectures: Architectural concepts of Distributed & Shared Memory MIMD architectures (UMA, NUMA, COMA, CC-NUMA); Interconnection Networks – direct interconnection networks (Linear Array, Ring, Star, 2D Mesh, Hyper cubes), switching techniques; dynamic interconnection networks (shared bus, crossbar, multistage networks); Specifications of top three super computers of Top500 list

 

Text Books:

 

1.    Hennessy J.D., Patterson D.A., “Computer Architecture A Quantitative Approach”, Elsevier India.

 

2.     Sima D., Fountain T., Kasuk P., “Advanced Computer Architecture-A Design space Approach,” Pearson

 

Education.

 

Reference Books:

 

1.     Hesham El-Rewini, Mostafa Abd-El-Barr, “Advanced Computer Architecture and Parallel Processing”, Wiley India Pvt. Ltd.

 

2.    Kai Hwang, “Advanced computer architecture – Parallelism, Scalability, Programmability”, Tata McGraw Hill.

 

3.    Rajaraman V. & Murthy C.S.R., “Parallel Computer: Architecture & Programming”, PHI Learning.

 

4.    David Culler, “Parallel Computer Architecture”, Elsevier India.

 

5.     Stallings W., “Computer Organization and Architecture”, Pearson Education.


MT-CSE-14-21

OBJECT ORIENTED ANALYSIS & DESIGN USING UML

Maximum marks: 150 (External: 100, Internal: 50)

Time: 3 hours

 

Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks.

 

UNIT – I

 

UML: History of UML, Goals of UML, nature & purpose of models, UML views & diagrams – static, design, use case, state machine, activity, interaction deployment, model management, profile; relationships in UML – association, dependency, generalization, realization; UML extensibility mechanisms – constraints, stereotypes, tagged values.

 

Unified Process (UP): UP structure, phases of UP

 

UNIT – II

 

Requirements: Meta Model, Workflow, Functional and Non-functional Requirements; Requirement Attributes, Finding Requirements

 

Use Case Modeling: Finding Actors and Use Cases, Use Case Scenario – main flow, branching within a flow, repletion within a flow, modeling alternative flows; relationships among actors and use cases; use case diagrams

 

UNIT – III

 

Analysis: Meta Model, Workflows, Finding Analysis Classes – using noun/verb analysis, CRC analysis, using RUP stereotypes - entity, boundary and control; Modeling Classes – Association (role name, multiplicity, navigability, association classes, qualified association) dependencies (usage, abstraction, permission), class generalization, generalization sets, power types; Analysis Package – nested packages, dependencies, transitivity, package generalization, architectural analysis, finding analysis packages; Concepts of Patterns & Frameworks

 

Use Case Realization – interaction diagram, sequence diagram; Activity Diagrams.

 

UNIT – IV

 

Design: Meta Model, Workflow, design classes – well-formed design classes, inheritance, templates, nested classes, design relationships, aggregation and composition, refining analysis relationships; interfaces and components – provided and required interfaces, interface realization v/s interface, components, finding interfaces, designing with interfaces; interaction diagram in design, modelling concurrency, active classes, concurrency in sequence diagram, concurrency in communication diagram; state machine - state machine diagrams

 

Implementation: Meta model, workflow, deployment diagram

 

Text Books:

 

1.    Jim Arlow, Ila Neustadt, “UML 2 and the Unified Process – Practical Object Oriented Analysis and Design”, Pearson Education.

 

2.    Bernd Bruegge, Allen H. Dutoit, “Object Oriented Software Engineering using UML”, Pearson Education.

 

Reference Books:

 

1.    Rumbaugh J., Jacobson I., Booch G., “The Unifed Modeling Language Reference Manual”, Pearson Education.

 

2.    Blaha M., Rumbaugh J., “Object-Oriented Modeling and Design with UML”, Pearson Education.

 

3.    Timothy C. Lethbridge, Robert Laganiere, “Object Oriented Software Engineering”, Tata McGraw-Hill.

 

4.    Booch G., Rumbaugh J., Jacobson I., “The Unified Modeling Language User Guide”, Pearson education.

 

5.    Satzinger, Jackson, Burd, “Object-Oriented Analysis & Design with the Unified Process”, Course Technology Inc.


MT-CSE-14-22             DIGITAL IMAGE PROCESSING

 

Maximum marks: 150 (External: 100, Internal: 50)                                               Time: 3 hours

 

Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks.

 

UNIT – I

 

Introduction to Digital Image Processing, Applications of digital image processing, Steps in digital image processing, Components of an Image Processing system, Image sampling and Quantization, Relationships between pixels.

 

Image Enhancement: Intensity transformations and spatial filtering, Point and Mask based techniques, Histogram processing, Fundamentals of spatial filtering, Smoothing and sharpening spatial filters.

UNIT – II

 

Filtering in frequency domain: Fourier Series and Transform, Discrete Fourier Transform, Frequency Domain Filtering Fundamentals, Homomorphic Filtering.

 

Color Image Processing: Color Fundamentals, Color characteristics, Color models, RGB, CYK, CMYK, HIS, YIQ models, Pseudo color image processing, full color image processing, color transformations, Smoothening and sharpening of images.

 

UNIT – III

 

Image Restoration: Model of Image Degradation/Restoration process, Noise models, Linear, Inverse filtering, Mean Square Error Restoration, Least Square Restoration.

 

Image Compression Fundamentals: Lossless and Lossy Compression, Basic Compression Methods: Huffman Coding, Run-Length Coding, LZW Coding, Arithmetic Coding, Bit-Plane Coding, Predictive Coding, Transform Coding, Wavelet Coding, Compression standards.

 

UNIT – IV

 

Image Segmentation: Fundamentals, Point, Line and Edge Detection, Thresholding, Region-Based Segmentation.

 

Image Representation: Boundary Representation, Chain Codes, Polygonal Approximations, Signatures, Boundary Descriptors, Simple Descriptors, Shape Numbers, Regional Descriptors, Topological Descriptors, Texture.

 

Text Book:

 

1.    Gonzalez R.C., Woods R.E., “Digital Image Processing”, Pearson Education.

 

2.    Vipula Singh, “Digital Image Processing with MATLAB and LABVIEW”, Elsevier India.

 

Reference Books:

 

1.    Ganzalez R.C., “Digital Image Processing with MATLAB”, Tata McGraw Hill.

 

2.    Sonka Milan, “Image Processing Analysis and Machine vision”, Cengage Learning.

 

3.    William K. Pratt, “Digital Image Processing”, Wiley India Pvt. Ltd.

 

4.    Chanda B., Majumder D. Dutta, “Digital Image Processing and Analysis”, PHI Learning.

 

5.    Jain A.K., “Fundamental of Digital Image Processing”, PHI Learning.

 

6.    Jayaraman S., Esakkirajan S., Veerakumar T., “Digital Image Processing”, Tata McGraw Hill.

 

7.    Annadurai, “Digital Image Processing”, Pearson Education.


MT-CSE-14-23(i)

SOFTWARE QUALITY MODELS & TESTING

Maximum marks: 150 (External: 100, Internal: 50)

Time: 3 hours

 

Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks.

 

UNIT – I

 

Overview of SQM: Concepts of Software Quality, Quality Attributes, Software Quality Models: McCall, Boehm, ISO-9000, CMM.

 

Software testing principles: Need for testing, Psychology of testing, Testing economics, White box, Black box, Grey box testing, Software Development Life Cycle (SDLC) and Testing, Software Verification & Validation, Weyuker's adequacy axioms.

 

UNIT – II

 

Testing strategies: White box testing techniques: Control Flow based testing - Statement coverage, Branch Coverage, Path Coverage; Data flow based testing, Mutation testing, Automated code coverage analysis, Black box testing techniques: Boundary value analysis, Equivalence partitioning, Cause-effect graphing, Robustness testing, Levels of testing - Unit, Integration and System Testing; Acceptance testing: α, β, and γ testing.

 

UNIT – III

 

Configuration Management: Maintaining Product Integrity, Components, configuration items, Change Management, Version Control, Configuration accounting, Reviews, Walkthrough, Inspection, and Configuration Audits.

 

Testing object oriented software: Challenges, Differences from testing non-Object Oriented Software, Class testing strategies, Class Modality, State-based Testing, Message Sequence Specification.

 

UNIT – IV

 

Testability and related issues: Design for Testability, Observability & Controllability, Design by Contract, Precondition, Post condition and Invariant, Regression Testing, Challenges, test optimization.

 

Miscellaneous topics: Stress Testing, Testing Client-server applications, Testing compilers and language processors, Testing web-enabled applications, Ad hoc testing: Buddy testing, pair testing, Exploratory testing, Agile and extreme testing.

 

Text Books:

 

1.    Jorgensen P. C., “Software Testing - A Craftman's Approach”, CRC Press.

 

2.    Mathur P. Aditya, “Foundations of Software Testing”, Pearson Education.

 

Reference Books:

 

1.  Glenford J. Myers, “The Art of Software Testing”, Wiley India Pvt Ltd.

 

2.  Robert V. Binder, “Testing Object-Oriented Systems: Models Patterns and Tools”, Pearson Education.

 

3.  Limaye G. M., “Software Testing – Principles, Techniques, and Tools”, Tata McGraw Hill.

 

4.   Boris Beizer, “Black-Box Testing: Techniques for Functional Testing of Software and Systems”, Wiley India Pvt Ltd.

 

5.   William E. Perry, “Effective Methods for Software Testing”, Wiley India Pvt Ltd.


MT-CSE-14-23(ii)                        HIGH PERFORMANCE NETWORKS

 

Maximum marks: 150 (External: 100, Internal: 50)                                                               Time: 3 hours

 

Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks.

 

UNIT – I

 

History of Networking and Internet; Need for Speed and Quality of Service; Advanced TCP/IP and ATM Networks; Internet Services; Internet Architecture; Backbone Networks; High Performance Networks; TCP Services; TCP format and connection management; SCTP; Encapsulation in IP; UDP Services, Format and Encapsulation in IP; IP Services; Header format and addressing; Fragmentation and reassembly; classless and subnet address extensions; subnetting and supernetting; CIDR; IPv6;

UNIT – II

 

Congestion Control and Quality of Service: Data traffic; Network performance; Effects of Congestion; Congestion Control; Congestion control in TCP and Frame Relay; Link-Level Flow and Error Control; TCP flow control;

 

Quality of Service(QoS): Flow Characteristics, Flow Classes; Techniques to improve QoS; Traffic Engineering; Integrated Services; Differentiated Services; QoS in Frame Relay and ATM;

 

Protocols for QoS Support: Resource Reservation-RSVP; Multiprotocol Label Switching; Real-Time Transport Protocol;

 

UNIT – III

 

High Speed Networks: Frame Relay Networks; Asynchronous Transfer Mode (ATM); ATM protocol Architecture; ATM logical connections; ATM cells; ATM Service categories; ATM Adaptation Layer; ATM Switching and Signaling; Optical Networks: SONET networks; SONET architecture;

 

High-Speed LANs: Bridged and Switched Ethernet; Fast Ethernet; Gigabit Ethernet; Wireless LANs: IEEE 802.11, Bluetooth; Introduction to HIPERLAN; WIMAX; RFID, Sensor Networks; Vehicular Networks;

 

Cellular Telephony; Generations; Cellular Technologies in different generations; GSM, CDMA; Satellite Networks;

 

UNIT – IV

 

Internet Routing: Interior and Exterior gateway Routing Protocols; RIP; OSPF; BGP; IDRP; Multicasting; IGMP; MOSPF; DVMRP, ; Routing in Ad Hoc Networks; AODV, DSR; Routing in ATM: Private Network-Network Interface; Mobile IP and Wireless Application Protocol;

 

Error and Control Messages: ICMP; Error reporting vs Error Correction; ICMP message format and Delivery; Types of messages;

 

Address Resolution: ARP, BOOTP; DHCP; Network Management and SNMP;

 

Text Books:

 

1.    Stallings W., “High-Speed Networks and Internets, Performance and Quality of Service”, Pearson Education.

 

2.    B. Muthukumaran, “Introduction to High Performance Networks”, Vijay Nicole Imprints.

 

Reference Books:

 

1.    James F. Kurose, Keith W. Ross, “Computer Networking, A Top-Down Approach Featuring the Internet”, Pearson Education.

 

2.    Behrouz A. Forouzan, “Data Communications and Networking”, McGraw Hill.

 

3.    Mahbub Hassan, Raj Jain, “High Performance TCP/IP Networking, Concepts, Issues, and Solutions”, Pearson Education.

 

4.    William Stallings, “Wireless Communications & Networks”, Pearson Education

 

5.    Asoke K Talukder, Hasan Ahmed, Roopa R Yavagal, “Mobile Computing”, TATA McGraw Hill.

 

6.    Larry L. Peterson, Bruce S. Davie, “Computer Networks”, Elsevier India.


MT-CSE-14-23(iii)                      ADVANCES IN DATABASES

 

Maximum marks: 150 (External: 100, Internal: 50)                                               Time: 3 hours

 

Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks.

 

UNIT – I

 

Database System Concepts and Architecture: Three - Schema Architecture and Data Independence, ER Diagrams, Naming conventions and Design Issues. Relational Model Constraints and Relational Database Schemas, EER model: Subclasses, Super classes, Inheritance, Specialization and Generalization, Constraints and characteristics of specialization and Generalization.

UNIT – II

 

Object Model: Overview of Object-Oriented concepts, Object identity, Object structure, Type constructors, Encapsulation of operations, Methods, and Persistence, Type hierarchies and Inheritance, Complex objects. Query Processing and Optimization: Using Heuristics in Query Optimization, Semantic Query Optimization, Database Tuning in Relational Systems.

 

UNIT – III

 

Databases for Advance Applications: Architecture for parallel database; Distributed database concepts, Data fragmentation, Replication, and allocation techniques, Overview of Client-Server Architecture, Active Database Concept and Triggers, Temporal Databases Concepts, Spatial and Multimedia Databases, Deductive Databases, XML Schema, Documents and Databases

 

UNIT – IV

 

Principles of Big Data: Ontologies and Semantics: Classifications, The Simplest of Ontologies, Ontologies, Classes with Multiple Parents, Choosing a Class Model. Data Integration and Software Interoperability Versioning and Compliance Issues, Stepwise Approach to Big Data Analysis, Failures and Legalities.

 

Text Books:

 

1.    Elmasri and Navathe, “Fundamentals of Database Systems”, Pearson Education.

 

2.    Jules J. Berman, “Principles of Big Data”, Elsevier India.

 

Reference Books:

 

1.    Date C.J., “An Introduction to Database Systems”, Pearson Education.

 

2.    Hector G.M., Ullman J.D., Widom J., “Database Systems: The Complete Book”, Pearson Education.

 

3.    Silberschatz A., Korth H., Sudarshan S., “Database System Concepts”, Tata McGraw Hill.


MT-CSE-14-24(i)                         DISTRIBUTED SYSTEMS

 

Maximum marks: 150 (External: 100, Internal: 50)                                              Time: 3 hours

 

Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks.

 

UNIT – I

 

Introduction: Goals, Distribution Transparency, Types of Distributed Systems, Architectural styles, System architecture: Centralized, Decentralized, Hybrid; Architecture versus Middleware.

 

Process: Process, Threads, Threads in distributed systems, virtualization, Clients, Servers, Server clusters, Code migration.

 

Communication and Naming: Types of communication, Remote procedure calls, message-oriented and stream oriented communication, multicast communication, names, identifiers, addresses, naming techniques, attribute based naming.

 

UNIT – II

 

Synchronization: clock synchronization, Global positioning system, logical clocks, vector clocks, mutual exclusion, election algorithm.

 

Consistency and replication: Introduction to replication in distributed environment, data-centric and client -centric consistency models, replica management, consistency protocols.

 

UNIT – III

 

Fault Tolerance: Faults and failures, failure masking, process resilience, design issues, reliable client server communication, reliable group communication, distributed commit, recovery.

 

Security: Security threats, policies and mechanisms, design issues, cryptography, secure channels, authentication, access control, firewall, denial of service, security management.

 

Distibuted object-based systems: architecture, of distributed objects, processes and object servers, communication of distributed objects, naming and synchronization, security.

 

UNIT – IV

 

Distributed File systems: client server architecture, processes and communication, naming in NFS, File locking and sharing in Coda, File replication in distributed environment, Byzantine failres and other security aspects.

 

Distributed Web and Coordination Based Systems: Traditional web based systems, web server clusters, web proxy caching, replication and security in web based systems, traditional architecture of coordination models, content-based routing, static and dynamic replication.

 

Text Books:

 

1.    Tanenbaum A.S., Steen M.V., “Distributed Systems: Principles and Paradigms”, Prentice Hall of India.

 

2.    Coulouris G., Dollimore J., Kindberg T., “Distributed Systems-Concepts and Design”, Pearson Education.

 

Reference Books:

 

1.    Attiya H., Welch J., “Distributed Computing: Fundamentals, Simulations and Advanced Topics”, Wiley India Pvt. Ltd.


MT-CSE-14-24(ii)                        BIOMETRICS SYSTEM SECURITY

 

Maximum marks: 150 (External: 100, Internal: 50)                                               Time: 3 hours

 

Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks.

 

UNIT – I

 

Introduction to Biometrics, Biometrics technology evolution, Biometric system, Biometric Functionalities; Verification and Identification, Biometric characteristics, Different Biometric traits; physiological and behavioral, Comparison of various biometrics, Biometric deformations, Biometric system errors; false match rate, false non-match rate, failure to capture and failure to enroll.

UNIT – II

 

Unibiometric, Multibiometric, Unimodal and Multimodal biometrics, Fusion of different biometrics, Sources of biometric information for fusion, Levels of fusion; Sensor level fusion, Feature level fusion, Match score level fusion and Decision level fusion, score normalization, Fusion methodologies, Issues in designing a multibiometric system, Advantages and disadvantages of multibiometrics.

 

Unit – III

 

Biometrics Security; Biometric system challenges, Attacks on biometric system, Biometric cryptography, Biometric steganography, Liveness detection in biometrics, Cancelable biometrics, Watermarking techniques; basic framework of watermarking, application of watermarking, attacks on watermarking, general watermarking process, watermarking algorithms.

Unit – IV

 

Biometric sensors; Biometric sensor interoperability, Soft biometrics, Incorporating Ancillary information in biometric systems, Biometric scope and future; biometrics and IT infrastructure, smart card technology and biometrics, DNA biometrics, Biometric standards, API of AADHAAR Schemes. Applications of biometrics; Government sector, Commercial sector and Forensic sector, SFINGE tool.

 

Text Books:

 

1.    Davide Maltoni, Dario Maio, Anil K. Jain, & Salil Prabhakar, “Handbook of Fingerprint Recognition”, Springer India.

 

2.     G.R. Sinha and Sandeep B. Patil, “Biometric: Concepts and Applications”, Wiley India Pvt. Ltd.

 

3.    Arun A. Ross, K. Nandakumar, and Anil K. Jain, “Handbook of Multibiometrics, (International Series on Biometrics)”, Springer India.

 

Reference Books:

 

1.    Anil K.Jain, Patrick Flynn, Arun A. Ross, “Handbook of Biometrics”, Springer India.

 

2.    John Chirillo and, Scott Blaul, “Implementing Biometric Security”, Wiley India Pvt. Ltd.

 

3.    Julian Ashbourn, “Practical Biometrics: From Aspiration to Implementation”, Springer Professional Computing.


MT-CSE-14-24(iii)                      SECURITY IN COMPUTING

 

Maximum marks: 150 (External: 100, Internal: 50)                                               Time: 3 hours

 

Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks.

 

UNIT – I

 

Computer Security Concept, Threats, Attacks and Assets, Security Functional Requirements, Security Architecture for Open System, Scope of Computer Security, Computer Security Trends and Strategy.

 

Cryptography: Terminology and Background, Substitution Ciphers, Transpositions, Cryptanalysis, Data Encryption Standard, DES & AES Algorithms and comparison, Public Key Encryption, Possible Attacks on RSA

 

Malicious Software: Types of Malicious Software, Viruses, Virus countermeasures, Worms, Bots, Rootkits.

 

UNIT – II

 

Protection in General-Purpose Operating Systems: Security Methods of Operating Systems, Memory and Address Protection.

 

Designing Trusted Operating Systems: Security Policies, Models of Security, Designing of Trusted Operating System.

 

Linux Security: Linux Security Model, Linux Vulnerabilities, Linux System Hardening, Application Security, Mandatory Access Control

 

UNIT – III

 

Database Security: Relational Database, Database Access Control, Inference, Statistical Databases, Database Encryption.

 

Data Mining Security: Security Requirements, Reliability and Integrity, Sensitive data, Multilevel Databases, Proposal for Multilevel Security, Data Mining - Privacy and Sensitivity, Data Correctness and Integrity, Data Availability.

 

Trusted Computing: Concept of Trusted System, Trusted Computing and Trusted Platform Module, Common Criteria for Information Technology Security Evaluation.

 

UNIT – IV

 

Security in Networks: Threats in networks, Network security controls, Firewall and Intrusion Prevention Systems: Need, Characteristics, Types of Firewalls, Firewall Basing, Intrusion Prevention Systems. Intrusion Detection Systems.

 

Internet Security Protocols and Standards: Secure Socket Layer (SSL) and Transport Layer Security (TLS), IP4 and IP6 Security, Secure Email.

 

Legal and Ethical Aspects: Cyber crime and Computer Crime, Intellectual Property, Copyrights, Patents, Trade Secrets, Privacy and Ethical Issues.

 

Text Books:

 

1.   Pfleeger C. & Pfleeger S.L., “Security in Computing”, Pearson Education.

 

2.   Stalling W., Brown L., “Computer Security Principles and Practice”, Pearson Education.

 

Reference Books:

 

1.   Schneier B., “Applied Cryptography: Protocols, Algorithms and Source Code in C”, Wiley India Pvt. Ltd.

 

MT-CSE-14-31 RESEARCH METHODOLOGY AND TOOLS Maximum marks: 150 (External: 100, Internal: 50) Time: 3 hours

 

Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks.

 

UNIT – I

 

Foundations of Research: Meaning, Objectives, Motivation, Utility. Concept of theory, empiricism, deductive and inductive theory. Characteristics of scientific method – Understanding the language of research – Concept, Construct, Definition, Variable. Research Process.

 

Problem Identification & Formulation: Research Question, Investigation Question, Measurement Issues, Hypothesis, Qualities of a good Hypothesis, Null Hypothesis & Alternative, Research Design: Concept and Importance in Research – Features of a good research design – Exploratory Research Design: Concept, types and uses, Descriptive Research Designs: concept, types and uses. Experimental Design: Concept of Independent & Dependent variables. Qualitative and Quantitative Research: Qualitative research, Quantitative research, Concept of measurement, causality, generalization, replication. Merging the two approaches.

 

UNIT – II

 

Measurement: Concept of measurement, Problems in measurement in research – Validity and Reliability. Levels of measurement – Nominal, Ordinal, Interval, Ratio.

 

Layout of a Research Paper, Journals in Computer Science, Impact factor of Journals, Ethical issues related to publishing, Plagiarism and Self-Plagiarism.

 

Thesis Writing: Writing - introduction, review of literature, results, abstract, summary, synopsis, Reference citing and listing.

UNIT – III

 

Introduction to R: Functions and packages in R; working with dataset in R; use of R for doing statistical analysis and graphics; R commands, Working with objects.

 

Packages in R – “caronline” for getting familiar with Database, Data Structures and visualization in R, “CORElearn” for introduction to correlation, regression and feature evaluation. BOOTFS: feature selection for classification, CARET – classification and regression training, “klaR” for classification and visualization, Plot diagrams and charts using R packages, Mining algorithms: “rminer”, Text mining: “tm”.

 

UNIT – IV

 

Introduction to MATLAB/SCILAB/OCTAVE: Environment, Variables, Classes of variables, Statements, Operators, Expressions, Vectors and Matrices, Control and Loop constructs, Scripts and Functions, Input and Output statements, Using File Input and File output, User defined Functions, Program organization, String variable, Cell array and structures array, MAT-files and Input/Output, Function handles, Plot function, Animation, 2-D and 3-D plotting (line, pie, bar, Histogram, Polar, Contour, volumes, polygons), Customizing plots, Customizing plots, Creating applications with Graphical User Interface (GUI), Initialize and Designing GUI interfaces, Code and FIG files, Callback functions: Push buttons, toggle buttons, radio button, Check box, Slider, Pop-up menu , Adding components to GUIDE layout area, panels and Button groups, Axes, tables, ActiveX Component, Menus for GUI.

 

Reference Books:

 

3.         Donald Cooper & Pamela Schindler, Business Research Methods, McGraw Hill.

 

4.         Alan Bryman & Emma Bell, Business Research Methods, Oxford University Press.

 

5.         Kothari C.K. (2004), Research Methodology Methods and Techniques (New Age International, New Delhi) 2nd Ed.

 

6.         N. Gurumani, Scientific Thesis Writing and Paper Presentation, MJP Publishers.

7.         Montgomery, Douglas C., Design and Analysis of Experiments, Wiley India Pvt. Ltd.

 

8.         Gardener M., “BEGINNING R: THE STATISTICAL PROGRAMMING LANGUAGE”, Wiley India Pvt. Ltd.

9.         Bansal R.K., Goel A., Sharma M.K., “MATLAB and its Applications in Engineering”, Pearson Education.

 

10.     Gilat A., “MATLAB: An Introduction with applications”, Wiley India Pvt. Ltd.


MT-CSE-14-32 ADVANCED OPERATING SYSTEMS Maximum marks: 150 (External: 100, Internal: 50) Time: 3 hours

 

Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks.

 

UNIT – I

 

DISTRIBUTED OPERATING SYSTEMS: Introduction, Issues, Communication Primitives, Inherent Limitations, Lamport’s Logical Clock; Vector Clock; Causal Ordering; Global State; Cuts; Termination Detection. Distributed Mutual Exclusion, Non Token Based Algorithms, Lamport’s Algorithm, Token Based Algorithms.

Suzuki Kasami’s Broadcast Algorithm, Distributed Deadlock Detection Issues, Centralized Deadlock Detection Algorithms, Distributed Deadlock Detection Algorithms, Agreement Protocols Classification, Solutions, Applications.

 

UNIT – II

 

DISTRIBUTED RESOURCE MANAGEMENT : Distributed File Systems, Design Issues, Distributed Shared Memory, Algorithms for Implementing Distributed Shared memory, Issues in Load Distributing, Scheduling Algorithms, Synchronous and Asynchronous Check Pointing and Recovery.

 

UNIT – III

 

REAL TIME AND MOBILE OPERATING SYSTEMS : Basic Model of Real Time Systems, Characteristics, Applications of Real Time Systems, Real Time Task Scheduling, Handling Resource Sharing, Mobile Operating Systems, Micro Kernel Design, Client Server Resource Access, Processes and Threads, Memory Management.

 

UNIT – IV

 

INTRODUCTION TO ANDROID: Android Application package (APK), Working with Eclipse and Android, Application Design, Controls and User Interface, Basic Graphics ad View class, Using Google Maps in applications, Applications with multiple screens, Adding Menus and popup menus in applications, Working with images, working with text files, tables and XML, Building client server applications, Publishing your application.

 

Reference Books:

 

1. Mukesh Singhal and Niranjan G. Shivaratri, “Advanced Concepts in Operating Systems - Distributed, Database, and Multiprocessor Operating Systems”, Tata McGraw Hill.

7.  Abraham Silberschatz; Peter Baer Galvin; Greg Gagne, “Operating System Concepts”, Wiley India Pvt. Ltd.

 

8.  Rajib Mall, “Real Time Systems: Theory and Practice”, Pearson Education India.

9.  James C.S. “Android Application development”, CENGAGE Learning.

 

10.              Gargenta M., Nakamura M., “Learning Android”, OREILLY Publishers.


MT-CSE-14-33(i)         DATA ANALYTICS

 

Maximum marks: 150 (External: 100, Internal: 50)                                                 Time: 3 hours

Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks.

 

UNIT – I

 

Introduction: Need of Big Data, Big Data vs. conventional data, Big Data Platform, Statistical Concepts: Sampling Distributions - Re-Sampling - Statistical Inference - Prediction Error.

 

Introduction to Data Science & Analytics, Business value of Analytics and Data Science, Typical problems solved with data science, Analytics Modeling, Analytic Processes and Tools - Analysis vs Reporting - Modern Data Analytic Tools.

 

UNIT – II

 

DATA ANALYSIS : Regression Modeling - Multivariate Analysis - Bayesian Modeling - Inference and Bayesian Networks - Support Vector and Kernel Methods - Analysis of Time Series: Linear Systems Analysis - Nonlinear Dynamics - Rule Induction, Confidence Interval and Tests of Significance, Inferential statistics and predictive analytics, Chi square, Test of independence, ANOVA

 

UNIT – III

 

FRAMEWORKS AND VISUALIZATION : MapReduce – Hadoop, Hive, MapR – Sharding – NoSQL Databases - Casandra - Hadoop Distributed File Systems – Visualizations - Visual Data Analysis Techniques - Interaction Techniques; Systems and Analytics Applications - Analytics using Statistical packages-Approaches to modeling in Analytics – correlation, regression, decision trees, classification, association- Intelligence from unstructured information-Text analytics.

 

UNIT – IV

 

NoSQL Database concepts, Schema, Two Phase Commit, Sharding & Share Nothing Architecture, Feature Based, Key Based, Lookup Table Based, Cassandra Definition & Features, Distributed & Decentralized, Elastic Scalability, High Availability & Fault Tolerance, Tuneable Consistency, Strict & Casual Consistency, Column Orientation, Schema Free, High Performance.

Creating Keyspace and Column Family, Writing and Reading Data, Cluster, Wide Rows, Skinny Rows, Referential Integrity, Secondary Indexes, Sorting, DeNormalisation, Design Patterns, Materialized Views. CQL-Data Definition language(DDL) Statements, Data Manipulation Language (DML), Create and modify Users, User permission, Capture CQL output to a file, Import and export data, CQL scripts from within CQL, CQL Scripts from the command prompt.

 

REFERENCE BOOKS:

 

4.      Michael Berthold, David J. Hand, “Intelligent Data Analysis”, Springer, 2007.

5.      Anand Rajaraman and Jeffrey David Ullman, “Mining of Massive Datasets”, Cambridge University Press, 2012.

6.      Bill Franks, “Taming the Big Data Tidal Wave: Finding Opportunities in Huge Data Streams with Advanced Analytics”, Wiley India Pvt. Ltd.

7.      Glenn J. Myatt, “Making Sense of Data”, Wiley India Pvt. Ltd.

 

8.      Akerker, “Big Data Computing”, CRC Press.

 

9.      Jiawei Han, MichelineKamber “Data Mining Concepts and Techniques”, Second Edition, Elsevier India, Reprinted 2008.

10.  Big Data for Dummies by Judith Hurwitz, Alan Nugent, Dr. Fern Halper, Elsevier India.

 

11.  Python for Data Analysis by Wes McKinney

12.  Statistics by S. C. Gupta.


MT-CSE-14-33(ii)        SOFT COMPUTING

 

Maximum marks: 150 (External: 100, Internal: 50)                                                 Time: 3 hours

Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks.

 

UNIT – I

 

Basic concepts of neuro-computing: Artificial Neural Network (ANN) and their biological roots and motivations, Mathematical Models of Neurons, ANN architecture, Learning rules, Learning Paradigms-Supervised, Unsupervised and reinforcement Learning, ANN training Algorithms-perceptions, Training rules, Delta, Back Propagation Algorithm, Multilayer Perceptron Model, Applications of Artificial Neural Networks, Competitive learning networks, Kohonen self organizing networks, Hebbian learning; Hopfield Networks, Associative Memories, The boltzman machine; Applications.

 

UNIT – II

 

Introduction to Fuzzy Logic: Classical and Fuzzy Sets: Overview of Classical Sets, Membership Function, Fuzzy rule generation. Operations on Fuzzy Sets: Compliment, Intersections, Unions, Combinations of Operations, Aggregation Operations. Fuzzy Arithmetic: Fuzzy Numbers, Linguistic Variables, Arithmetic Operations on Intervals & Numbers, Lattice of Fuzzy Numbers, Fuzzy Equations. Fuzzy Logic: Classical Logic.

 

UNIT – III

 

Genetic Algorithm (GA): Evolutionary computing, conditions for evolution, Simple Genetic Algorithm (SGA), different types of operators: Selection, Crossover, mutation and replacement, optimization problems and traditional optimization methods, differences between GA & traditional methods, Holland’s schemata theorem, encoding schemes.

 

UNIT – IV

 

Random Optimization, Simulated Annealing, Tabu Search, Ant Colony Optimization, Particle Swarm Optimization, Memetic Algorithms.

 

Text Books:

 

3.      S. N. Sivanandam & S. N. Deepa, Principles of Soft Computing, Wiley India Pvt. Ltd..

 

4.      Goldberg D. E., Genetic Algorithms in Search, Optimization, and Machine Learning, Pearson Education.

 

Reference Books:

 

3.      Jang, Sun, Mizutani, Neuro-Fuzzy and Soft computing, Pearson Education.

 

4.      Haykin, Neural networks: a comprehensive foundation, Pearson Education.

5.      Mitchell M., An Introduction to Genetic Algorithms, Prentice-Hall.

 

6.      Klir G.J. & Yuan B., Fuzzy Sets & Fuzzy Logic, PHI.


MT-CSE-14-33(iii)      GENETIC ALGORITHMS

 

Maximum marks: 150 (External: 100, Internal: 50)                                                 Time: 3 hours

Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks.

 

UNIT – I

 

Introduction: Goal of optimization, local and global optima, Multi-objective optimization, Problems in global optimization like premature convergence to a local optimum, overfitting etc, A brief history of evolutionary computation, The appeal of evolution, Biological terminology, Search spaces and fitness landscapes, Conventional Optimization and Search Techniques - Gradient-Based Local Optimization Method, Random Search, Stochastic Hill Climbing, Simulated Annealing etc.

 

UNIT – II

 

Genetic algorithms(GA), Evolution strategies, Difference between Genetic Algorithm and traditional methods, Selection – elitism, rank selection, tournament selection, Boltzmann selection, steady state selection etc.; Crossover, mutation; Schema theorem – schemata and masks, Wildcards, Holland’s schema theorem and criticism; convergence.

.

UNIT – III

 

Computer Implementation of Genetic Algorithm: Data Structures, Reproduction, Crossover, and mutation, Mapping objective functions to fitness form, Fitness scaling, Different types of encodings - Binary Encoding, Octal Encoding, Hexadecimal Encoding, Permutation Encoding, Value Encoding, Tree Encoding etc.

 

UNIT – IV

 

Advanced operators and techniques in Genetic Search: Dominance, Diploidy, and Abeyance, Inversion and other reordering operators like partially matched crossover, order crossover and cycle crossover, Niche and speciations, Micro-operators, Knowledge based techniques, Genetic algorithm and parallel processors.

Classification of Genetic Algorithm: Simple Genetic Algorithm(SGA), Parallel and Distributed Genetic Algorithm (PGA and DGA), Hybrid Genetic Algorithm (HGA), Adaptive Genetic Algorithm(AGA), Fast Messy Genetic Algorithm (FmGA), Independent Sampling Genetic Algorithm(ISGA).

 

Text Books:

 

3.      Goldberg D. E., Genetic Algorithms in Search, Optimization, and Machine Learning, Pearson Education.

 

4.      Sivanandam S. N. & Deepa S. N., Introduction to Genetic Algorithms, Springer.

 

Reference Books:

 

3.      Mitchell M., An Introduction to Genetic Algorithms, Prentice-Hall.

 

4.      Weise Thomas, Global Optimization Algorithms – Theory and Application, http://www.it-weise.de/ projects/book.pdf.


MT-CSE-14-34(i)         CLOUD COMPUTING

 

Maximum marks: 150 (External: 100, Internal: 50)                                                 Time: 3 hours

Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks.

 

UNIT – I

 

Cloud Computing: Definition, roots of clouds, characteristics, Cloud Architecture – public, private, hybrid, community, advantages & disadvantages of Cloud Computing.

 

Migrating into a Cloud: broad approaches, seven-step model to migrate

 

Virtualization: benefits & drawbacks of virtualization, virtualization types – operating system virtualization, platform virtualization, storage virtualization, network virtualization, application virtualization, virtualization technologies.

 

UNIT – II

 

Cloud Services & Platforms: Compute services, Storage services Database services, Application Services, Queuing services, E-mail services, Notification services, Media services, Content delivery services, Analytics services, Deployment & management services, Identity & access management services. Case studies of these services.

Federated & Multimedia Cloud Computing: architecture, features of federation types, federation scenarios, layers enhancement of federation; Multimedia Cloud.

 

UNIT – III

 

SLA Management in Cloud Computing: traditional approaches to SLA management, types of SLA, life cycle of SLA, SLA management in cloud, automated policy-based management.

 

Cloud Security: challenges, CSA cloud security architecture, authentication, authorization, identity & access management, data security, auditing.

 

Legal Issues in Cloud Computing: data privacy and security issues, cloud contracting models.

 

UNIT – IV

 

Developing for Cloud: Design considerations for cloud applications, reference architectures for cloud applications, cloud application design methodologies, data storage approaches

 

Python for Cloud: Python characteristics, data types & data structures, control flows, functions, modules, packages, file handling, date/time operations, classes, Python web application framework – Django.

 

Text Books

 

6.      Arshdeep Bahga, Vijay Madisetti, Cloud Computing – A Hands-on Approach, University Press, 2014

 

7.      Saurabh Kumar, Cloud Computing, 2nd Edition, Wiley India Pvt Ltd.

8.      Rajkumar Buyya, James Broberg, Andrzej Goscinski, Cloud Computing – Principles and Paradigms, Wiley India Pvt. Ltd.

 

Reference Books

 

3.  Barrie Sosinsky, Cloud Computing Bible, Wiley India Pvt. Ltd.

 

4.   Michael Miller, Cloud Computing: Web-Based Applications That Change the Way You Work and Collaborate Online, Que Publishing.

5.  Haley Beard, Cloud Computing Best Practices for Managing and Measuring Processes for On-demand Computing, Applications and Data Centers in the Cloud with SLAs, Emereo Pvt Limited, July 2008.


MT-CSE-14-34(ii) WIRELESS NETWORKS AND MOBILE COMPUTING Maximum marks: 150 (External: 100, Internal: 50) Time: 3 hours

 

Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks.

 

UNIT – I

 

Evolution and Challenges of Wireless Networks; The Electromagnetic Spectrum; Modulation Techniques and Multiple Access for Wireless Systems; Spread Spectrum; Overview of Mobile Computing and its applications; Cellular Networks: Concept; Call Set-up; Frequency Reuse; Channel Assignment; Handoff; Mobility Management; GSM and IS-95 architecture, channels, and Call Establishment; Wireless Data Service; 3G and 4G Cellular Systems.

 

UNIT – II

 

Introduction to Ad Hoc Wireless Networks; Issues in Ad Hoc Wireless Networks; MAC Protocols for Ad Hoc Wireless Networks: Introduction, Issues, Classification, Contention-Based Protocols; Contention-Based Protocols with Reservation Mechanisms; Contention-Based Protocols with Scheduling Mechanisms;

Routing Protocols for Ad Hoc Networks: Introduction, Issues; Classification; Table-Driven Routing Protocols; On-Demand Routing Protocols; Hybrid Routing Protocols; Routing Protocols with Efficient Flooding Mechanisms; Hierarchical Routing Protocols.

 

UNIT – III

 

Multicast Routing in Ad Hoc Networks: Introduction; Issues; Operation of Multicast Routing Protocols; Classification; Tree-Based Multicast Routing Protocols; Mesh-Based Multicast Routing Protocols; Energy Efficient Multicasting;

 

Transport Layer For Ad Hoc Wireless Networks: Introduction and Design Issues; TCP over Ad Hoc Wireless Networks;

 

Network Security Requirements and Attacks; Key Management; Secure Routing in Ad Hoc Wireless Networks; WEP protocol.

UNIT - IV

 

Energy Management in Ad Hoc Wireless Networks: Need; Classification of Energy Management Schemes; Transmission Power Management Schemes; System Power Management Schemes;

 

Wireless Sensor Networks: Introduction; Sensor Network Architecture; Data Dissemination; Data Gathering; MAC protocols for Sensor Networks; Location Discovery; Quality of a Sensor Network; Energy Efficiency, Synchronization, Real-Time Communication and Security.

 

Text Books:

 

1. C. Siva Ram Murthy and B.S. Manoj, “Ad Hoc Wireless Networks – Architectures and Protocols”, Pearson Education

 

2. P. Nicopolitidis, M.S. Obaidat, G.I. Papadimitriou, A.S. Pomportsis, “Wireless Networks”, Wiley India Pvt. Ltd.

Reference Books:

 

6.  Jochen Schiller, “Mobile Communications”, Second Edition, Pearson Education.

 

7. Sipra DasBit, Biplab K. Sikdar, “Mobile Computing”, PHI.

 

8. William C.Y.Lee, “Mobile Cellular Telecommunications”, Second Edition, McGraw-Hill.

9. Theodore S. Rapparort, “Wireless Communications- Principles and Practice”, Pearson Education.

 

10.              Stomenovic and Cacute, “Handbook of Wireless Networks and Mobile Computing”, Wiley India Pvt. Ltd.

11.              W. Stallings, “Wireless Communications and Networks”, Pearson Education.

 

12.              Hansmann U., Merk L., Martin S. Nicklons, Stober T., “Principles of Mobile Computing”, Springer.

 

13.              Hazysztof Wesolowshi, “Mobile Communication Systems”, Wiley India Pvt. Ltd.


 

9.Raj               Kamal,               “Mobile               Computing”,              Oxford               Higher               Education.


MT-CSE-14-34(iii)      SEMANTIC WEB AND SOCIAL NETWORKING

 

Maximum marks: 150 (External: 100, Internal: 50)                                                 Time: 3 hours

Note: Examiner will be required to set NINE questions in all. Question Number 1 will consist of objective type/short-answer type questions covering the entire syllabus. In addition to question no. 1, the examiner is required to set eight more questions selecting two from each unit. Student will be required to attempt FIVE questions in all. Question Number 1 will be compulsory. In addition to compulsory question, student will have to attempt four more questions selecting one question from each Unit. All questions will carry equal marks.

 

UNIT – I

 

Web Intelligence Thinking and Intelligent Web Applications, The Information Age ,The World Wide Web, Limitations of Today’s Web, The Next Generation Web, Machine Intelligence, Artificial Intelligence, Ontology, Inference engines, Software Agents, Berners Lee www, Semantic Road Map, Logic on the semantic Web.

Knowledge Representation for the Semantic Web Ontologies and their role in the semantic web, Ontologies Languages for the Semantic Web

 

UNIT – II

 

Resource Description Framework (RDF) / RDF Schema, Ontology Web Language (OWL), UML, XML/XML Schema.

Ontology Engineering: Ontology Engineering, Constructing Ontology, Ontology Development Tools, Ontology Methods, Ontology Sharing and Merging, Ontology Libraries and Ontology Mapping, Logic, Rule and Inference Engines.

 

UNIT – III

 

Semantic Web Applications, Services and Technology Semantic Web applications and services, Semantic Search, e-learning, Semantic Bioinformatics, Knowledge Base ,XML Based Web Services, Creating an OWLS Ontology for Web Services,

 

Semantic Search Technology, Web Search Agents and Semantic Methods.

 

UNIT - IV

 

Social Network Analysis and semantic web: What is social Networks analysis, development of the social networks analysis, Electronic Sources for Network Analysis

 

Electronic Discussion networks, Blogs and Online Communities, Web Based Networks. Building Semantic Web Applications with social network features.

 

Text Books:

 

3.  Berners Lee, Godel and Turing, Thinking on the Web Wiley India Pvt. Ltd.

 

4. Peter Mika, Social Networks and the Semantic Web, Springer, 2007.

 

Reference Books:

 

8.  J.Davies, R.Studer, P. Warren, Semantic Web Technologies, Trends and Research in Ontology Based Systems, Wiley India Pvt. Ltd.

 

9.  Liyang Lu, Semantic Web and Semantic Web Services, Chapman and Hall/CRC Publishers, (Taylor & Francis Group)

10.              Frank Van Harmelen, Information Sharing on the semantic Web Heiner Stuckenschmidt; Springer Publications.

11.              T.Segaran, C.Evans, J.Taylor, Programming the Semantic Web, O’Reilly, SPD.