M.Tech - Information Technology (Networking) … · English and Foreign ... Definitions and Basic Properties of Congruences – Solving Linear Congruences and Quadratic Congruences

M.Tech - Information Technology (Networking)

Curriculum and Syllabus

UNIVERSITY CORE – 27 CREDITS

Course Code Course Title

Course Type L T P J C Category

Prerequisite

Corequisite

Antirequisite

Course Equival

ance

ITE6099 Master’s Thesis Project 0 0 0 0 16 NIL NIL

MAT5002 Mathematics for Computer Engineering Theory 3 0 0 0 3 NIL NIL

SET5001

Science, Engineering and Technology Project - I Project 0 0 0 0 2 NIL NIL

SET5002

Science, Engineering and Technology Project - II Project 0 0 0 0 2 NIL NIL

EFL5097 English and Foreign Language Basket 0 0 0 0 2 NIL NIL

STS6777 Soft Skills Basket 0 0 0 0 2 NIL NIL

PROGRAMME CORE – 18 CREDTIS

Course

Code Course Title

Course

Type L T P J C

Cat

ego

ry

Prereq

uisite

Co-

requisi

te

Anti-

requisi

te

Course

Equiva

lence

ITE5001

Advanced Data Structures

and Algorithms

Embedd

ed -

Theory

& Lab 3 0 2 0 4 NIL NIL

ITE5702

Cloud Computing and

Virtualization Theory 3 0 0 0 3 NIL NONE NIL

ITE5003 Computer Networks

Embedd

ed -

Theory

&

Project 3 0 0 4 4 NIL NIL

ITE5004

Cryptography and Network

Security

Embedd

ed -

Theory

&

Project 3 0 0 4 4 NIL NONE NIL

ITE5005 Open Source Programming

Embedd

ed -

Theory

& Lab 2 0 2 0 3 NIL NONE NIL

PROGRAMME ELECTIVE – 19 CREDITS

Course Code Course Title

Course Type L T P J C

Category

Pre-requisit

e

Co-requis

ite

Anti-

requisite

Course

Equivalence

ITE6001 Network Management

Embedd

ed -

Theory

&

Project 3 0 0 4 4 NIL NIL

ITE6003 High Speed Networks

Embedd

ed -

Theory

&

Project 3 0 0 4 4 NIL ITE5004 NIL

ITE6004 Internet of Things

Embedd

ed -

Theory

&

Project 3 0 0 4 4 NIL NIL NIL

ITE6005 Enterprise Operating Systems Theory 3 0 0 0 3 NIL NONE NIL

ITE6006 Wireless Networks

Embedd

ed -

Theory,

Lab &

Project 3 0 2 4 5 NIL NIL NIL

ITE6007 Advanced Database Systems

Embedd

ed -

Theory

& Lab 3 0 2 0 4 NIL NONE NIL

ITE6008

Advanced Computer

Architecture Theory 3 0 0 0 3 NIL NONE NIL

ITE6009 Network Programming Theory 3 0 0 0 3 NIL NONE NIL

ITE6010 Machine Learning

Embedd

ed -

Theory

&


ITE6011

System Modelling and

Simulation

Embedd

ed -

Theory

&


ITE6012

Advanced Data Mining

Techniques Theory 3 0 0 0 3 NIL NONE NIL

ITE6013 Big Data Analytics

Embedd

ed -

Theory

&


ITE6XXX Software Defined Networking

Embedd

ed -

Theory

&


UNIVERSITY ELECTIVE

Course L T P C

University Elective-I - - - 3

University Elective-II - - - 3

Total - - - 6

BREAKUP OF COURSES

Sl.No. Category Credits

1 University Core 27

2 University Elective 06

3 Programme Core 18

4 Programme Elective 19

Recommended Total Number of Credits 70

Minimum Total Number of Credits (As per Acad. Council) 70

Category No. of Credits

Credit distribution

(%)

Engineering 57 81

Humanities 4 6

Management 6 8.5

Sciences 3 4.5

Total 70 100

Course Code Mathematics for Computer Engineering L T P J C

MAT-5002 3 0 0 0 3

Pre-requisite None Syllabus Version

1.0 xx.xx Course Objectives:

To motivate the learners for understanding the fundamental concepts in mathematics

required for computer engineering such as mathematical logics, proof techniques,

linear algebra, number theory

To explore probability and statistical measures and queuing theory of real-time data.

Expected Course Outcome

On completion of this course, the students are expected to

Implement mathematical ideas in realistic projects of engineering.

Analyze the problems connected with technology and theoretical computer sciences,

computer algorithms, networks and data structures.

Student Learning Outcomes (SLO): 1,2,9

Module:1 Proof Techniques 6 hours SLO: 2,9

Implications, Equivalences, Converse, Inverse, Contrapositive, Negation, Contradiction, Structure,

Direct Proofs, Dis-proofs, Natural Number Induction, Structural Induction, Weak/String Induction,

Recursion and Well Orderings.

Module:2 Linear Algebra 6 hours SLO: 1,9

Eigenvalues and Eigenvectors – Gerschgorin Circles – Rutishauser Method – Rotation and Reflection

Matrices – Face Recognition Application.

Module:3 Number Theory 6 hours SLO: 2,9

Divisibility – Division Algorithm – Euclidean Algorithm – Definitions and Basic Properties of

Congruences – Solving Linear Congruences and Quadratic Congruences – Applications of

Congruences – The Chinese Remainder Theorem – Euler’s Theorem and Fermat’s Little

Theorem – Primarily Checking.

Module:4 Probability 6hours SLO: 1,9

Introduction to Random Variable – Binomial and Poisson Distributions – Normal Distribution –

Weibull, Exponential and Gamma Distributions – Performance Modeling Application.

Module:5 Statistical Measures 6 hours SLO: 1,2

Correlation and Regression – Covariance – Partial and Multiple Correlation – Multiple Regression – Time Series Data Analysis Application

Module:6 Sampling Theory 8 hours SLO: 2,9

Small Sample Tests – Student’s t –test – F-test – Chi-square Test – Goodness of Fit and Independence of Attributes – Basic Principles of Experimentation – Analysis of Variance – Application using Monte- Carlo Methods and Decision Trees.

Module:7 Queuing Theory 5 hours SLO: 1,9

Introduction – Markov Process – Poisson Process – Pure Berth Process –Death Process –

Birth-Death Processes – Queue Notation – Little's Theorem – Queuing Models – M/M/1;

M/M/c and M/M/∞.

Module:8 Contemporary Issues 2 hours

Industry Expert Lecture

Total Lecture hours: 45 hours

Text Book(s)

1. Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers, Keying E. Ye, Probability and Statistics for Engineers and Scientists, 9th Edition, Prentice Hall, 2012.

2. H.A. Taha, Operations Research, 9th Edition, PHI, 2010.

Reference Books

1. Neal Koblitz, A course in number theory and cryptography, Springer, 2002.

2. J.P. Tremblay and R. Manohar, Discrete Mathematical Structures with Applications to Computer Science, Tata McGraw Hill, 2001.

Mode of Evaluation

Digital Assignments (Solutions by using soft skills), Continuous Assessment Tests, Final Assessment Test

Recommended by Board of Studies

Approved by Academic Council No. Date

Course code Fundamentals of Communication Skills L T P J C

ENG5001 0 0 2 0 1

Pre-requisite Not cleared EPT (English Proficiency Test) Syllabus Version

1.0

Course Objectives:

To enable learners learn basic communication skills - Listening, Speaking, Reading and

Writing and apply them for various purposes in academic and social contexts

Expected Course Outcome:

Ability to communicate effectively in social and academic contexts

Student Learning Outcomes (SLO): 16,18

Module:1 Listening 8 hours SLO: 16

Understanding Conversation - Listening to Speeches - Listening for Specific Information

Module:2 Speaking 4 hours SLO: 16

Exchanging Information - Describing Activities, Events and Quantity

Module:3 Reading 6 hours SLO: 16,18

Identifying Information - Inferring Meaning - Interpreting text

Module:4 Writing: Sentence 8 hours SLO: 16

Basic Sentence Structure – Connectives - Transformation of Sentences - Synthesis of Sentences

Module:5 Writing: Discourse 4 hours SLO: 16,18

Instructions - Paragraph - Transcoding

Total Practical hours: 30 hours

Text Book(s)

1. Redston, Chris, Theresa Clementson, and Gillie Cunningham. Face2face Upper Intermediate Student's Book. 2013, Cambridge University Press.

Reference Books

1.

2.

3.

4.

5.

6.

Chris Juzwiak . Stepping Stones: A guided approach to writing sentences and Paragraphs

(Second Edition), 2012, Library of Congress.

Clifford A Whitcomb & Leslie E Whitcomb, Effective Interpersonal and Team

Communication Skills for Engineers, 2013, John Wiley & Sons, Inc., Hoboken: New Jersey.

Arun Patil, Henk Eijkman & Ena Bhattacharya, New Media Communication Skills for Engineers and IT Professionals,2012, IGI Global, Hershey PA. Judi Brownell, Listening: Attitudes, Principles and Skills, 2016, 5th Edition, Routledge:USA John Langan, Ten Steps to Improving College Reading Skills, 2014, 6th Edition, Townsend Press:USA Redston, Chris, Theresa Clementson, and Gillie Cunningham. Face2face Upper Intermediate Teacher's Book. 2013, Cambridge University Press.

List of Challenging Experiments (Indicative) SLO: 16,18

1. Familiarizing students to adjectives through brainstorming adjectives

with all letters of the English alphabet and asking them to add an

adjective that starts with the first letter of their name as a prefix.

2 hours

2. Making students identify their peer who lack Pace, Clarity and 4 hours

Volume during presentation and respond using Symbols.

3. Using Picture as a tool to enhance learners speaking and writing skills 2 hours

4. Using Music and Songs as tools to enhance pronunciation in the

target language / Activities through VIT Community Radio

2 hours

5. Making students upload their Self- introduction videos in Vimeo.com 4 hours

6. Brainstorming idiomatic expressions and making them use those in to

their writings and day to day conversation

4 hours

7. Making students Narrate events by adding more descriptive adjectives

and add flavor to their language / Activities through VIT Community

Radio

4 hours

8 Identifying the root cause of stage fear in learners and providing

remedies to make their presentation better

4 hours

9 Identifying common Spelling & Sentence errors in Letter Writing and

other day to day conversations

2 hours

10. Discussing FAQ’s in interviews with answers so that the learner gets

a better insight in to interviews / Activities through VIT Community

Radio

2 hours

Total Practical Hours 30 hours

Recommended by Board of Studies 22-07-2017

Approved by Academic Council No. 46 Date 24-08-2017

Course code Professional and Communication Skills L T P J C

ENG5002 0 0 2 0 1

Pre-requisite ENG5001 Syllabus Version

1.0

Course Objectives:

To enable students develop effective Language and Communication Skills

To enhance students’ Personal and Professional skills

Expected Course Outcome: Students will be able to apply the acquired skills and excel in a professional environment.


Module:1 Personal Interaction 2 hours SLO: 16,18 Introducing Oneself- one’s career goals

Activity: SWOT Analysis

Module:2 Interpersonal Interaction 2 hours SLO: 16,18 Interpersonal Communication with the team leader and colleagues at the workplace

Activity: Role Plays/Mime/Skit

Module:3 Social Interaction 2 hours SLO: 18 Use of Social Media, Social Networking, gender challenges

Activity: Creating LinkedIn profile, blogs

Module:4 Résumé Writing 4 hours SLO: 18

Identifying job requirement and key skills

Activity: Prepare an Electronic Résumé

Module:5 Interview Skills 4 hours SLO: 16,18

Placement/Job Interview, Group Discussions

Activity: Mock Interview and mock group discussion

Module:6 Report Writing 4 hours SLO: 16,18

Language and Mechanics of Writing

Activity: Writing a Report

Module:7 Study Skills: Note making 2 hours SLO: 16,18

Summarizing the report

Activity: Abstract, Executive Summary, Synopsis

Module:8 Interpreting skills 2 hours SLO: 16,18

Interpret data in tables and graphs

Activity: Transcoding

Module:9 Presentation Skills 4 hours SLO: 16

Oral Presentation using Digital Tools

Activity: Oral presentation on the given topic using appropriate non-verbal cues

Module:10 Problem Solving Skills 4 hours SLO: 16,18

Problem Solving & Conflict Resolution

Activity: Case Analysis of a Challenging Scenario

Total Practical hours: 30 hours

Text Book(s)

1. Bhatnagar Nitin and Mamta Bhatnagar, Communicative English For Engineers And

Professionals, 2010, Dorling Kindersley (India) Pvt. Ltd.

Reference Books

1.

2.

3.

4.

5.

Clifford A Whitcomb & Leslie E Whitcomb, Effective Interpersonal and Team

Communication Skills for Engineers, 2013, John Wiley & Sons, Inc., Hoboken: New Jersey.

Arun Patil, Henk Eijkman & Ena Bhattacharya, New Media Communication Skills for Engineers and IT Professionals,2012, IGI Global, Hershey PA.

John Adair, Decision Making and Problem Solving Strategies,2010, Replika Press, New

Delhi.

Jon Kirkman and Christopher Turk, Effective Writing: Improving Scientific, Technical and

Business Communication, 2015, Routledge

Diana Bairaktarova and Michele Eodice, Creative Ways of Knowing in Engineering, 2017,

Springer International Publishing


1. SWOT Analysis – Focus specially on describing two strengths and two weaknesses

2. Role Plays/Mime/Skit -- Workplace Situations

3. Use of Social Media – Create a LinkedIn Profile and also write a page or two on areas of

interest

4. Prepare an Electronic Résumé and upload the same in vimeo

5. Group discussion on latest topics

6. Report Writing – Real-time reports

7. Writing an Abstract, Executive Summary on short scientific or research articles

8 Transcoding – Interpret the given graph, chart or diagram

9 Oral presentation on the given topic using appropriate non-verbal cues

10. Problem Solving -- Case Analysis of a Challenging Scenario

Total Laboratory Hours 30 hours



FRE5001 FRANÇAIS FONCTIONNEL L T P J C 2 0 0 0 2 Pre-requisite NIL Syllabus Version Course Objectives: 1.0

This course is designed to introduce French through a study of Language with special focus

on the cultural aspects.


Having interest in lifelong learning.

Having adaptive thinking and adaptability.

Having a good working knowledge of communicating in French

Having critical thinking and innovative skills

Student Learning Outcomes (SLO): 11,12,16,18 Module:1 3 hours SLO: 11,12 Les Salutations, Les nombres (1-100), Les jours de la semaine, Les mois de l’année, Les Pronoms

Sujets, Les Pronoms Toniques, La conjugaison des verbes réguliers, La conjugaison des verbes

irréguliers- avoir / être / aller / venir / faire etc.

Savoir-faire pour: Saluer, Se présenter, Etablir des contacts.

Module:2 3 hours SLO: 11,12 La conjugaison des verbes Pronominaux, La Négation,

L’interrogation avec ‘Est-ce que ou sans Est-ce que’.

Savoir-faire pour: Présenter quelqu’un, Chercher un(e) correspondant(e), Demander des

nouvelles d’une personne

Module:3 4 hours SLO: 11,12 L’article (défini/ indéfini), Les prépositions (à/en/au/aux/sur/dans/avec etc.), L’article contracté,

Les heures en français, La Nationalité du Pays, L’adjectif (La Couleur, l’adjectif possessif, l’adjectif

démonstratif/ l’adjectif interrogatif (quel/quelles/quelle/quelles), L’accord des adjectifs avec le

nom, L’interrogation avec Comment/ Combien / Où etc.,

Savoir-faire pour : Situer un objet ou un lieu, Poser des questions

Module:4 6 hours SLO: 11,12,16 La traduction simple :(français-anglais / anglais –français),

Savoir-faire pour : Faire des achats, Comprendre un texte court, Demander et indiquer le chemin.

Module:5 5 hours SLO: 11,12,16

L’article Partitif, Mettez les phrases aux pluriels, Faites une phrase avec les mots donnés, Exprimez

les phrases données au Masculin ou Féminin, Associez les phrases.

Savoir-faire pour:

Trouver les questions, Répondre aux questions générales en français,

Module:6 3 hours SLO: 11,12,16,18 Décrivez :

La Famille /La Maison/L’université /Les Loisirs/ La Vie quotidienne etc.

Module 7 4 hours SLO: 11,12,16,18

Dialogue :

a) Réserver un billet de train

b) Entre deux amis qui se rencontrent au café

c) Parmi les membres de la famille

d) Entre le client et le médecin

Module 8 Contemporary Discussion 2 hours


Text Book(s) 1

Echo-1, Méthode de français, J. Girardet, J. Pécheur, Publisher CLE International, Paris 2010.

2 Echo-1, Cahier d’exercices, J. Girardet, J. Pécheur, Publisher CLE International, Paris 2010.

Reference Books

1 CONNEXIONS 1, Méthode de français, Régine Mérieux, Yves Loiseau ,Les Éditions Didier, 2004.

2 CONNEXIONS 1, Le cahier d’exercices, Régine Mérieux, Yves Loiseau, Les Éditions Didier, 2004.

3

ALTER EGO 1, Méthode de français, Annie Berthet, Catherine Hugo, Véronique M. Kizirian,

Béatrix Sampsonis, Monique Waendendries , Hachette livre 2006.

4 ALTER EGO 1, Le cahier d’activités, Annie Berthet, Catherine Hugo, Béatrix Sampsonis,

Monique Waendendries , Hachette livre 2006.

Approved by Academic Council 41st Academic council Date 17.06.2016

GER5001 DEUTSCH FUER ANFAENGER L T P J C

2 0 0 0 2

Pre-requisite NIL Syllabus Version

Anti-requisite 1.0

Course Objectives:

This course is designed to introduce German through a study of Language with special focus

on the cultural aspects.


Having interest in lifelong learning.

Having adaptive thinking and adaptability.

Having a good working knowledge of communicating in German.

Having critical thinking and innovative skills

Student Learning Outcomes (SLO): 11,12,16,18

Module:1 3 hours SLO: 11,12 Einleitung,Begrüssungsformen, Landeskunde, Alphabet, Personalpronomen, Verb Konjugation,

Zahlen (1-100), W-fragen, Aussagesätze, Nomen – Singular und Plural

Lernziel:

ElementaresVerständnisvon Deutsch, Genus- Artikelwörter Module:2 3 hours SLO: 11,12 Konjugation der Verben (regelmässig /unregelmässig) die Monate, die Wochentage,

Hobbys,Berufe, Jahreszeiten, Artikel, Zahlen (Hundert bis eine Million), Ja-/Nein- Frage,

Imperativ mit Sie

Lernziel :

Sätzeschreiben, über Hobbyserzählen, überBerufesprechenusw. Module:3 4 hours SLO: 11,12 Possessivpronomen, Negation, Kasus- AkkusatitvundDativ (bestimmter, unbestimmterArtikel),

trennnbareverben, Modalverben,Adjektive, Uhrzeit, Präpositionen, Mahlzeiten, Lebensmittel,

Getränke

Lernziel :

Sätze mit Modalverben, VerwendungvonArtikel, über Länder undSprachensprechen,

übereineWohnungbeschreiben.

Module:4 6 hours SLO: 11,12 Übersetzungen : (Deutsch – Englisch / Englisch – Deutsch)

Lernziel :

Grammatik – Wortschatz – Übung

Module:5 5 hours SLO: 11,12,16 Leseverständnis,Mindmapmachen,Korrespondenz- Briefe, Postkarten, E-Mail

Lernziel :

WortschatzbildungundaktiverSprachgebrauch

Module:6 3 hours SLO: 11,12,16 Aufsätze :

MeineUniversität, Das Essen, mein Freund odermeineFreundin, meineFamilie,einFest in

Deutschlandusw.

Module:7 4 hours SLO: 11,12,16,18 Dialoge:

e) Gespräche mit Familienmitgliedern, Am Bahnhof,

f) GesprächebeimEinkaufen ; in einemSupermarkt ; in einerBuchhandlung ;

g) in einemHotel - an der Rezeption ;einTerminbeimArzt.

h) TreffenimCafe

Module:8 Contemporary issues 2 hours


Text Book(s)

1. Text Book: Studio d A1 Deutsch alsFremdsprache, Hermann Funk, Christina Kuhn, SilkeDemme : 2012

Reference Books

1. Netzwerk Deutsch alsFremdsprache A1, Stefanie Dengler, Paul Rusch, Helen Schmtiz,

Tanja Sieber, 2013

2. Lagune ,HartmutAufderstrasse, Jutta Müller, Thomas Storz, 2012.

3. Deutsche SprachlehrefürAUsländer, Heinz Griesbach, Dora Schulz, 2011

4. ThemenAktuell 1, HartmurtAufderstrasse, Heiko Bock, MechthildGerdes, Jutta Müller und Helmut Müller, 2010

Web site adresses : --www.goethe.de;wirtschaftsdeutsch.de ; hueber.de ; klett-sprachen.de

www.deutschtraning.org; https://bpb.de/lernen

Approved by Academic Council 41 Date 17.06.2016

https://bpb.de/lernen

Course code Essentials of Business etiquettes L T P J C

STS5001 3 0 0 0 1


1.0

Course Objectives:

Having problem solving ability

Having Computational thinking


Enabling students to use relevant aptitude and appropriate language to express themselves

To communicate the message to the target audience clearly

Student Learning Outcomes (SLO): 7, 9

Module:1 Business Etiquette: Social and Cultural

Etiquette and Writing Company Blogs and

Internal Communications and Planning and

Writing press release and meeting notes

9 hours SLO: 7

Value, Manners, Customs, Language, Tradition, Building a blog, Developing brand message,

FAQs', Assessing Competition, Open and objective Communication, Two way dialogue,

Understanding the audience, Identifying, Gathering Information,. Analysis, Determining,

Selecting plan, Progress check, Types of planning, Write a short, catchy headline, Get to the Point

–summarize your subject in the first paragraph., Body – Make it relevant to your audience,

Module:2 Study skills – Time management skills

3 hours SLO: 9

Prioritization, Procrastination, Scheduling, Multitasking, Monitoring, Working under pressure and adhering to deadlines

Module:3 Presentation skills – Preparing presentation

and Organizing materials and Maintaining

and preparing visual aids and Dealing with

questions

7 hours SLO: 7

10 Tips to prepare PowerPoint presentation, Outlining the content, Passing the Elevator Test, Blue

sky thinking, Introduction , body and conclusion, Use of Font, Use of Color, Strategic

presentation, Importance and types of visual aids, Animation to captivate your audience, Design of

posters, Setting out the ground rules, Dealing with interruptions, Staying in control of the

questions, Handling difficult questions

Module:4 Quantitative Ability -L1 – Number properties

and Averages and Progressions and

Percentages and Ratios

11 hours SLO: 9

Number of factors, Factorials, Remainder Theorem, Unit digit position, Tens digit position,

Averages, Weighted Average, Arithmetic Progression, Geometric Progression, Harmonic

Progression, Increase & Decrease or successive increase, Types of ratios and proportions

Module:5 Reasoning Ability-L1 – Analytical Reasoning

8 hours SLO: 9

Data Arrangement(Linear and circular & Cross Variable Relationship), Blood Relations,

Ordering/ranking/grouping, Puzzle test, Selection Decision table

Module:6 Verbal Ability-L1 – Vocabulary Building

7 hours SLO: 7,9

Synonyms & Antonyms, One word substitutes, Word Pairs, Spellings, Idioms, Sentence

completion, Analogies


Reference Books

1. Kerry Patterson, Joseph Grenny, Ron McMillan, Al Switzler(2001) Crucial Conversations:

Tools for Talking When Stakes are High. Bangalore. McGraw‐Hill Contemporary

2. Dale Carnegie,(1936) How to Win Friends and Influence People. New York. Gallery Books

3. Scott Peck. M(1978) Road Less Travelled. New York City. M. Scott Peck.

4. FACE(2016) Aptipedia Aptitude Encyclopedia. Delhi. Wiley publications

5. ETHNUS(2013) Aptimithra. Bangalore. McGraw-Hill Education Pvt. Ltd.

Websites:

1. www.chalkstreet.com

2. www.skillsyouneed.com

3. www.mindtools.com

4. www.thebalance.com

5. www.eguru.ooo

Approved by Academic Council No. 45 Date 15/06/2017

http://www.chalkstreet.com/

http://www.skillsyouneed.com/

http://www.mindtools.com/

http://www.thebalance.com/

http://www.eguru.ooo/

Course code Preparing for Industry L T P J C

STS5002 3 0 0 0 1

Pre-requisite Syllabus Version

1.0

Course Objectives:

Having problem solving ability Having a clear understanding of professional and ethical responsibility


Enabling students to simplify, evaluate, analyze and use functions and expressions to simulate real

situations to be industry ready.

Student Learning Outcomes (SLO): 9, 10

Module:1 Interview skills – Types of interview and

Techniques to face remote interviews and

Mock Interview

3 hours SLO: 9,10

Structured and unstructured interview orientation, Closed questions and hypothetical questions,

Interviewers' perspective, Questions to ask/not ask during an interview, Video interview¸ Recorded

feedback, Phone interview preparation, Tips to customize preparation for personal interview, Practice

rounds

Module:2 Resume skills – Resume Template and Use of

power verbs and Types of resume and

Customizing resume

2 hours SLO: 10

Structure of a standard resume, Content, color, font, Introduction to Power verbs and Write up, Quiz on types of resume, Frequent mistakes in customizing resume, Layout - Understanding different company's requirement, Digitizing career portfolio

Module:3 Emotional Intelligence - L1 – Transactional

Analysis and Brain storming and

Psychometric Analysis and Rebus

Puzzles/Problem Solving

12 hours SLO: 9

Introduction, Contracting, ego states, Life positions, Individual Brainstorming, Group Brainstorming,

Stepladder Technique, Brain writing, Crawford's Slip writing approach, Reverse brainstorming, Star

bursting, Charlette procedure, Round robin brainstorming, Skill Test, Personality Test, More than one

answer, Unique ways

Module:4 Quantitative Ability-L3 – Permutation-

Combinations and Probability and Geometry

and mensuration and Trigonometry and

Logarithms and Functions and Quadratic

Equations and Set Theory

14 hours SLO: 9

Counting, Grouping, Linear Arrangement, Circular Arrangements, Conditional Probability, Independent

and Dependent Events, Properties of Polygon, 2D & 3D Figures, Area & Volumes, Heights and distances,

Simple trigonometric functions, Introduction to logarithms, Basic rules of logarithms, Introduction to

functions, Basic rules of functions, Understanding Quadratic Equations, Rules & probabilities of Quadratic

Equations, Basic concepts of Venn Diagram

Module:5 Reasoning ability-L3 – Logical reasoning and

Data Analysis and Interpretation

7 hours SLO: 9

Syllogisms, Binary logic, Sequential output tracing, Crypto arithmetic, Data Sufficiency, Data

interpretation-Advanced, Interpretation tables, pie charts & bar chats

Module:6 Verbal Ability-L3 – Comprehension and

Logic

7 hours SLO: 9

Reading comprehension, Para Jumbles, Critical Reasoning (a) Premise and Conclusion, (b) Assumption &

Inference, (c) Strengthening & Weakening an Argument


Reference Books

1. Michael Farra and JIST Editors(2011) Quick Resume & Cover Letter Book: Write and Use an Effective Resume

in Just One Day. Saint Paul, Minnesota. Jist Works

2. Daniel Flage Ph.D(2003) The Art of Questioning: An Introduction to Critical Thinking. London. Pearson

3. David Allen( 2002) Getting Things done : The Art of Stress -Free productivity. New York City. Penguin Books.

4. FACE(2016) Aptipedia Aptitude Encyclopedia.Delhi. Wiley publications

5. ETHNUS(2013) Aptimithra. Bangalore. McGraw-Hill Education Pvt. Ltd.

Websites:

1. www.chalkstreet.com

2. www.skillsyouneed.com

3. www.mindtools.com

4. www.thebalance.com

5. www.eguru.ooo

Approved by Academic Council No. 45 Date 15/06/2017

http://www.chalkstreet.com/

http://www.skillsyouneed.com/

http://www.mindtools.com/

http://www.thebalance.com/

http://www.eguru.ooo/

Course code Advanced Data Structures and Algorithms L T P J C

ITE 5001 3 0 2 0 4


1.0

Course Objectives:

To learn Algorithms and Data structures as more productive computer scientist

To facilitate the students to develop more efficient algorithms and employ appropriate Data

structures for solving a problem and to aid them in implementing the same.

Expected Course Outcome: On completion of this course, the students will be able to

Design an efficient algorithm for a problem using a specified paradigm along with a proper data

structure.

Choose an appropriate design paradigm that solves the given problem efficiently along with

appropriate data structures.

Map real-world problems to algorithmic solutions.

Analyze algorithms asymptotically and compute the performance analysis of algorithms with the

same functionality.

Identify the existence of problems which defy algorithmic solution


Module:1 Advanced Algorithm Design 6 hours SLO: 1 Dynamic Programming - Rod Cutting, Matrix chain multiplication, Longest Common Subsequence Greedy Algorithms – Activity selection problem, Matroids and Greedy methods

Module:2 Primary Data Structures 6 hours SLO: 1 Sorting – Quick and Heap Sort, Radix Sort, AVL trees, Graph Traversals

Module:3 Time and Space Complexity Analysis 6 hours SLO: 1 Asymptotic notations, conditional asymptotic notations, Amortized analysis, NP complete and NP hard

Time and Space complexity analysis by solving recurrence equations

Module:4 Optimization Data structures 6 hours SLO: 14 Search Trees, building Optimal search trees, Height balanced and Weight balanced trees

B –trees, Red Black Trees and Splay trees

Module:5 Data Structures for sets of Intervals 6 hours SLO: 14 Interval Trees - Segment Trees, Trees for Weighted Intervals, Higher dimensional Segment Trees Range Counting and Semi group model

Module:6 Geometric and Heap Structures 6 hours SLO: 14 K-d trees, Orthogonal Range trees, Leftist heap, Skew heap, Binomial heap and Fibonacci heaps

Module:7 Data structures for Strings & Transformations 6 hours SLO: 14 Dynamic Structures, Persistent Structures, Tries , Compressed Tries, Suffix Trees and Suffix Arrays



Text Book(s)

1. Peter Brass, “Advanced Data Structures”, Cambridge University Press, 2014.

Reference Books

1. Thomas H.Cormen, Charles E.Leiserson, Ronald L.Rivest, Clifford Stein, “Introduction to

Algorithms: Third Edition”, The MIT Press, 2014.

2 Thomas H.Cormen, “Algorithms Unlocked”, The MIT Press, 2013

3 Mark Allen Weiss, “Data structures and algorithm analysis in C++”, Florida International

University, 4th edition, Pearson education, 2014

List of Challenging Experiments SLO: 1, 14

1. For a workshop organized by SITE, a gallery which can accommodate a maximum of 100

participants is booked and the participants are allowed to do online registration. Organizing

Committee stores the names of all the online applicants. Due to unavoidable reasons, the venue has

to be changed and as the capacity of the new venue is just 70, it is decided to render live streaming of

the lectures in a different room, for the remaining 30 participants. Those who did last minute

registration are chosen for this. If you are a part of the Organizing committee, which ADT will you

use for storing the participants’ names to suit the above mentioned scenario? Develop code to

implement the same.

2. Design an algorithm or code to read the following four details of a student who appears for VITEE –

Name, Marks scored (out of 100) in Physics, Chemistry and Mathematics. Calculate the average of

all the three subjects. Create a singly linked list to store only the name and average of ‘n’ students, in

the increasing order of average. Later, display only those students’ details whose average is 60% or

more, as selected. Also display the count of selected candidates

3. Implement the algorithm to convert the infix form of a given expression into prefix form. Apply your

algorithm for the example given below and display the resulting prefix expression.

3*((7+4)/(5-2))<8%6

Also extend the logic to work for logical, unary and bitwise operators

4. Implement a Queue using two Stacks and a Stack using two Queues.

5. Assume that a doubly linked list is used for storing the contact details (name & phone number) in

your smart phone. For every call that is made, the list is searched from the beginning to find out the

details of the caller you are searching for. It is inevitable that certain numbers in the list are called

very frequently. To speed up the search operation, it is proposed that the caller detail that is found out

currently is to be added to the beginning of the list.

Example: If the list has the following 3 contact details, and a call has to be made for ‘BBB’, the list

is searched from the beginning and the caller detail is found in the second node.

6 Write a program to insert the following elements in a binary search tree in the order of arrival and

display the tree

51,12, 17, 68, 5,73,90,36,89,24

Now display all the nodes of the tree wherein all the even numbers are shown first in ascending order

followed by all the odd numbers in descending orde

7 With Trie data structures, develop a program that can be used in the web browser to auto complete

the text or show many possibilities of the text that the user is trying to write.

8 Suggest a suitable data structure to create a file server with optimal access to files, with the restriction

that each folder can store N files maximum. Implement the same.

9 You are supposed to build a Social Cop in your smartphone. Social Cop helps people report crimes

to the nearest police station in real-time. Use k-d tree to search for the police station nearest to the

crime location before attempting to report anything by constructing a 2 dimensional k-d tree from the

locations of all the police stations in your city, and then querying the k-d tree to find the nearest

police station to any given location in the city.

10 For ITE5001 lab, 28 students have enrolled for a particular faculty. Every week the faculty evaluates

his/her students’ work one by one. If the faculty cannot evaluate all the 28 students, she continues the

evaluation for the remaining students in the following week. After completing the first phase of

evaluation, the next phase is started from the beginning. If the faculty has to store the register number

of his/her students and keep track of which student he has to evaluate for the next week, suggest an

appropriate ADT. Design a program to perform all possible operations in it.




Course code Cloud Computing & Virtualization L T P J C

ITE5702 3 0 0 0 3

Pre-requisite Nil Syllabus Version

1.0

Course Objectives:

To learn recent computing paradigms

To introduce the concept of Virtualization and secured environment

To understand Cloud programming paradigms


Design, implement and evaluate a cloud-based system, process, component, or program to meet

desired needs.

An ability to use techniques, skills in secured cloud environment.

An ability to create VM, migrate and provide QOS to the committed users.


Module:1 Introduction 4 hours SLO: 6 Overview of Computing Paradigm, Cloud Computing- Types of Cloud Deployment Models - Private,

Public, Hybrid, Agency Clouds - Cloud Service Models: Infrastructure as a Service(IaaS), Platform as a

Service(PaaS), Software as a Service(SaaS), Anything as a Service(XaaS).

Module:2 Virtualization Basics 5 hours SLO: 6 Virtualization - Types - Implementation Levels –Structures-Tools, CPU, Memory, I/O Devices, Virtual Clusters and Resource management – Virtualization for Data-center Automation

Module:3 Virtualization Techniques 7 hours SLO: 17 Virtualization Techniques – Storage Virtualization – System-level or Operating Virtualization – Control-

Plane Virtualization–Virtual Machine Basics – Taxonomy of Virtual machines - Server Virtualization –

Physical and Logical Partitioning - Types of Server Virtualization

Module:4 Virtual Machine Management 7 hours SLO: 17 Virtual Machine Management- VM Provisioning and Manageability-Virtual Machine Migration Service-

Distributed Management of Virtual Machines-Scheduling Techniques-Capacity Management to meet SLA

Commitment.

Module:5 Cloud Environments 7 hours SLO: 17 Cloud Environments - Case study: One cloud service provider per service model (eg. Amazon EC2, Google App Engine, Sales Force, Azure, Open Source tools) - Cloud application development using third party APIs, Working with EC2 API – Google App Engine API - Facebook API, Twitter API . HDFS, MapReduce Programming Model.

Module:6 Security Overview 7 hours SLO: 6 Security Overview – Cloud Security Challenges and Risks – Software-as-a-Service Security – Security

Governance – Risk Management – Security Monitoring – Security Architecture Design – Data Security

– Application Security – Virtual Machine Security - Identity Management and Access Control –

Autonomic Security.

Module:7 Quality of Service 5 hours SLO: 17

Quality of Service - (QoS) monitoring in a Cloud computing environment –Introduction to Cloud

Middleware- Mobile Cloud -Sensor Cloud



Text Book(s)

1. Rajkumar Buyya, James Broberg, Andrzej M. Goscinski, Cloud Computing: Principles and

Paradigms, Wiley, 2013

Reference Books

1 Barrie Sosinsky, “Cloud Computing Bible” , Wiley-India, 2011

2 Kai Hwang, Geoffrey C Fox, Jack G Dongarra, “Distributed and Cloud Computing: From Parallel

Processing to the Internet of Things”, Morgan Kaufmann Publishers,2013.

3 Ronald L. Krutz, Russell Dean Vines,"Cloud Security: A Comprehensive Guide to Secure Cloud

Computing”, Wiley-India, 2010

4 Tim Mather, Subra Kumaraswamy, and Shahed Latif,” Cloud Security and Privacy”,Oreilly,2009

5 John W.Rittinghouse and James F.Ransome, “Cloud Computing: Implementation, Management, and

Security”, CRC Press, 2010.



Course code Computer Networks L T P J C

ITE5003 3 0 0 4 4


1.0

Course Objectives:

To assist the students community for better understanding of networking.

To facilitate the students for developing more efficient network protocols and standards.


Make use, the correct mix of topologies and setup the dynamic network that works efficiently.

Develop reliable, flexible and efficient routing algorithm for any complex networking scenarios in

the real world.

Sort out the issues in any given network protocols/ scenario built upon networking standards.


Module:1 Foundation 5 hours SLO: 2 Applications – Requirements – Network Architecture – Performance.

Module:2 Connectivity 7 hours SLO: 7 Perspectives on connecting – Encoding – Framing – Error Detection – Reliable Transmission – Ethernet and Multiple Access Networks.

Module:3 Internetworking-I: 7 hours SLO: 5 Switching and Bridging – Basics of Internetworking (IP).

Module:4 Internetworking-II: 7 hours SLO: 7 Routing – Implementation and Performance.

Module:5 End – End Protocols : 4 hours SLO: 2 Simple Demultiplexer (UDP) – Reliable Byte Stream (TCP) – Remote Procedure Call Fundamentals –

Overview of Transport for Real-Time Application (RTP)

Module:6 Congestion Control And Resource Allocation: 7 hours SLO: 2 Issues in Resource Allocation – Queuing Disciplines- TCP Congestion Control – Congestion Avoidance

Mechanisms – Quality of Service.

Module:7 Applications 6 hours SLO: 2 Traditional Applications – Infrastructure Services – Overview of Multimedia Applications and Overlay Networks.

Module:8 Contemporary issues: 2 hours


Text Book(s)

1. Larry L Peterson and Bruce S Davie, “Computer Networks – A Systems Approach”, MK Publishers,

Fifth Edition, 2012

Reference Books

1 James F Kurose and Keith W Ross, “Computer Networking – A Top Down Approach”, Sixth Edition,

Pearson Education, 2013



Course code Cryptography and Network Security L T P J C

ITE5004 3 0 0 4 4


1.0

Course Objectives:

To understand the cryptographic techniques like encryption, key exchange and digital signature

techniques used today.

To learn the security policies such as authentication, integrity and confidentiality.

To understand the security issues in web and network scenario.


On completion of this course, student should be able to

Implement the security policies such as authentication, integrity and confidentiality in the

form of message exchanges.

Implement cryptographic techniques used today and analyse its vulnerabilities against

various threats.

Analyze web and network security threats.


Module:1 Introduction: 5 hours SLO: 2

Symmetric cipher model, substitution and transposition ciphers, DES, strength of DES, Triple

DES, Block cipher design principles.

Module:2 Symmetric ciphers: 5 hours SLO: 2 AES structure, transformation function and key expansion, RC4, RC6, Idea, Blowfish

Module:3 Number Theory concepts: 5 hours SLO: 1

Prime numbers, prime factorization, Euclidean algorithm, Fermat’s and Euler’s theorem, modular

arithmetic, Chinese remainder theorem.

Module:4 Asymmetric ciphers: 7 hours SLO: 2

Principles of public-key cryptosystem, RSA algorithm, attacks over RSA algorithm, Elgamal

crypto system, Elliptic curve cryptography, pseudorandom number generation.

Module:5 Key management and data integrity: 5 hours SLO: 2

Symmetric key sharing using symmetric and asymmetric approach, Distribution of public keys, X.509certificates, public key infrastructure, Two simple hash functions, HMAC, SHA-3, RSA-PSS digital signature algorithm.

Module:6 Network and Cloud Security: 8 hours SLO: 2

Network access control, Extensible authentication protocol, IEEE 802.1 port-based network

access control, Cloud security risks and countermeasures, Data protection in the cloud, Cloud

security as a service, IP Security.

Module:7 Internet Security: 7 hours SLO: 2

Transport level security-SSL, HTTPS, Secure Shell, Mobile device security, IEEE 802.11i

Wireless LAN Security, E-Mail Security, E-Business security.



Text Book(s)

1. William Stallings, “Cryptography and Network Security: Principles and Practices”, 6th Edition,

Pearson education, 2014.

Reference Books

1. Charles P.Pfleeger, Shari Lawrence P.Pfleeger, Jonathan Margulies, “Security in Computing”, 5th

Edition, Prentice Hall, 2015

2. Atul Kahate, “Cryptography and Network Security”, 3rd Edition, Tata McGraw Hill, 2013.


Course code Open Source Programming L T P J C

ITE5005 2 0 2 0 3


1.0

Course Objectives:

To introduce the concept of open source tools, software and their license/copyright

policies.

To use open source software and tools to develop software

To understand how to create open source software applications and can publish it over the

Internet and to allow the users to customize the software based on their requirements



Create open source software applications and can publish it over the Internet.

Understand the open source licensing and the importance of using open source products.

Customize their software product with respect to existing products by other developers.

Develop web-enabled software using common software components.


Module:1 Overview of Open Source Software 4 hours SLO: 7

Need of Open Sources, Open source software license; Open source Programming and Tools, Web

Server Installation and PHP Introduction.

Module:2 Open Source Programming Language-PHP 5 hours SLO: 14 Variables, Operators, Constants, Control structures, Arrays, Functions, classes, Handling Files, Server side includes.

Module:3 Working With Forms 4 hours SLO: 2

HTML and PHP code, Processing Forms, Single page submission, User Input, Form Validation,

,String Manipulation and Regular Expression

Module:4 My SQL database programming 4 hours SLO: 2

Introduction to MySQL, Datatypes, MySQL Command-Line, SQL Language, Types of

Commands- DDL, DML, DCL, Constraints, Select, Orderby, Limit, Working with metadata,

Functions - Number, Date, Character, Control Flow, Joins, Groupby, Having, Subquery, Indexing

Module:5 Working with PHPMyAdmin 3 hours SLO: 14 Creating Databases, Database Engines, Creating Fields, Delete Record, Update Record, View Record, Drop Database/Tables, Creating Fields Primary / Foreign Keys, Unique Key, Insert Record

Module:6 Emailing in PHP 4 hours SLO: 7

Mail server configuration, Understanding MIME headers, Sending an email, multipart

messages, Session tracking using PHP, Graphics Input Validators(using PHP image

manipulation functions), cookies

Module:7 Programming in CGI-Perl 4 hours SLO: 7

Script Morphology, Data Types, Scalars, Lists/Arrays, Hash, Variable Scope, Operators, Control

Statements, Files, Functions/ Subroutines, PCRE- Pattern matching.



Text Book(s)

1. Larry Ullman, “PHP and MySQL for Dynamic Web Sites-Visual QuickPro Guide”, Fourth Edition, Peachpit Press, 2012.

Reference Books

1.

2.

3.

Tom Christiansen, Brian D Foy, Larry Wall, Jon Orwant, “Programming Perl”, Fourth

Edition, O’Reilly Media, 2012.

Luke Welling, Laura Thomson, “PHP and MySQL Web Development”, Fifth Edition,

Addison-Wesley Developer’s Library, 2016

M.N. Rao, “Fundamentals of Open Source Software”, PHI Learning Private Limited, 2015.

List of Challenging Experiments SLO: 14,17

1. Write PHP script to mimic STACK and Queue data structure using array.(Design a webpage

to populate the array, and trigger the STACK and Queue operation after clicking a button)

2. Write a PHP Script to demonstrate object oriented programming concepts.

Create a class “Shape” with a constructor to initialize the one parameter “dimension”. Now

create three sub classes of Shapes with following methods:

a) Class “Circle” with methods to calculate the area and circumference of the circle with

dimension as radius.

b) Class “Square” with methods to calculate the area of the square.

c) Class “Sphere” with methods to calculate the volume of the sphere.

Write appropriate main method to create object of each class and test every method.

3. Write a PHP script to implement the below scenario, A final year student named Navin

wanted to develop an app for mobile phone. The functionalities of the application defined by

Navin are: to play music when an unauthorized person trying to unlock the phone, to make a

call to another person, to record the voice call. But, unfortunately he could not complete the

project. After few days another student Kavin took over the project. Kavin has defined first

two functionalities and also he defined an additional functionality such as ‘to make the phone

jump’ and had written code for the same. But he could not complete the project. Later this

project was given to another Student named Pravin who finished this project by defining all

the functionalities. Write a java code for the above scenario

4. Write a PHP script to populate the input file with a set of names by designing a web-page.

Then read those names and segregate the names terminate with a letter “i” as well as “a”, and

move them to one separate file, The set names do not match with above mentioned criteria

should be moved into one more another file.

5. Design a web-page with the following fields to facilitate course registration

Name-Textfield

Register number-Textfield

Password-Password

Date-of -Registration Date –dropdown

Month-Dropdown

Year-dropdown

Core Courses- Drop down should be populated with all available courses

Elective Course-Five courses need to be displayed with radio button

Email-ID-Textfield

Write a PHP script to extract the data which has been submitted using web-page and validate

data (use regular expression) against the below constraints.

i) Name: It must begin with a letter and length should not exceed 8 characters.

ii) Register-Number: It should begin with 16/17 (Eg.16BIT0233/17BIT0111)

iii) Password: It must be of alphanumeric characters.

iv) Date-of-Registration : The number of days should match with a month

( Jan=31days Feb=28 days)

v) Facilitate with multiple selection

vi) The accepted email-id must obey all the qualities of valid email-id account name.

If the provided information is satisfied all the constraints then display them using tabular

format.

6. Maintain the below mentioned tables inside Bank.db.

-branch(branch-name,branch-city,assets)

-customer (customer-name, customer-street, customer-city)

-account (account-number, branch-name, balance)

-loan (loan-number, branch-name, amount)

-depositor (customer-name, account-number)

-borrower (customer-name, loan-number)

-employee (employee-name, branch-name, salary)

Write the necessary MySQL command to extract the data from the above mentioned tables.

a) To find all loan number for loans made at the VIT Indian

bank branch with loan amounts greater than 75000.

b) Find the loan number of those loans with loan

amounts between 50000 and 75000

c) Find the names of all branches that have greater assets than some branch located in

Vellore.

d) Find the customer names and their loan numbers for all customers having a loan at some

branch.

e) Find all customers who have a loan, an account, or both:

f) Find all customers who have an account but no loan.

(no minus operator provided in mysql)

g) Find the number of depositors for each branch.

(Note: use PHP-MySQL integrated functions)

7. Design a login form as given below. Write PHP scripts to do the following.

a) Validate the mandatory fields user name and password.

b) Generate the given CAPTCHA and validate it.

8. Write a Perl program to validate a credit card number using the following algorithm. It has

two parts. If part I fails, immediately return with an error message.

Part I

This includes checking the total number of digits and the number prefix. The table below

shows acceptable values for some of the major credit cards.

Card Type Starts with Length

American Express 34, 37 15

MasterCard 51-55 16

VISA 4 13, 16

Part-II

Starting from the right hand side of the card number, skip the last digit.

Double every alternate number. [from length-1 to 0]

If the doubled number has 2 digits, add both the digits

Add together all the doubled numbers with the other non-doubled numbers.

If the sum is divisible by 10, then the card is valid.

Example: Valid Visa Card:4 0 1 2 8 8 8 8 8 8 8 8 1 8 8 1



Course code Network Management L T P J C

ITE6001 3 0 0 4 4

Pre-requisite NIL Syllabus version

1.00

Course Objectives:

To introduce the principles and practices of network management models and protocols.

learn logic circuits and converters

To study the recent trends in network management technologies.


On completion of this course , student should be able

To understand and apply principles of network management models, protocols and

technical aspects of network systems.

To manage the networked systems using SNMP protocol.

To apply network management tools for various applications.

An ability to design and conduct experiments, as well as to analyze and interpret data.


Module:1 Network management overview 4 hours SLO: 2

Goals, Organization and functions-Network Management Architecture and Organization-Current

Status and future of Network management

Module:2 Basic foundations: standards, models and

language

8 hours SLO: 2

Network management standards-Network management Models-Organization, Information, Communication and Functional Models.

Module:3 SNMPv1 8 hours SLO: 5

SNMP Model-Organization Model-System Overview-Information Model-Communication and

Functional Models.

Module:4 SNMPv2 7 hours SLO: 5

Major changes in SNMPv2-System architecture-Structure of Management Information-MIB-

SNMPv2 protocol

Module:5 SNMPv3 7 hours SLO: 5 Key features-Architecture-Applications-MIB-Security-User Based Security Model-Access Control

Module:6 RMON 5 hours SLO: 2

What is Remote Monitoring?-RMON SMI and MIB-RMONI-A Case Study on Internet Traffic.

Module:7 Network management tools 3 hours SLO: 17

System utilizes for Management-Basic tools, SNMP tools and Protocol Analyzer.

Module:8 Industry Expert Lecture 3 hours SLO: 2

Total Lecture hours:

#Mode: Flipped Class Room, [Lecture to be

videotaped],Use of physical and computer models to

45 hours

lecture, Visit to Industry Min of 2 lectures by

industry experts

Text Book(s)

1. Mani Subramanian,” Network Management-Principles and Practice”-Pearson Education Ltd,

2010.

Reference Books

1. William Stallings, ”SNMP, SNMPv2, SNMPv3 and RMON1 and 2,”Pearson Education,

2012.

2. Richard Burke J, “Network Management-Concepts and Practice: A Hands-on Approach”,

Pearson Education, 2011.



Course code High Speed Networks L T P J C

ITE6003 3 0 0 4 4

Pre-requisite ITE5004 Syllabus version

1.00

Course Objectives:

To highlight the features of different technologies involved in High Speed Networking and

their performance.

To familiar with the basic concepts, architectures, protocols, advantages and limitations,

and the recent development of various high-speed networking technologies.


On completion of this course student should be able

Analyze a network performance by applying the concept of queuing analysis.

Apply the concept learnt in this course to optimize and troubleshoot high-speed network.

Design and configure network that have outcome characteristics needed to support a

specified set of applications.


Module:1 High Speed Networks Overview 6 hours SLO: 2

Frame Relay Networks-Asynchronous transfer mode : ATM Protocol Architecture, ATM logical,

Connection, ATM Cell, ATM Service Categories, AAL.

Module:2 High Speed LANs and Queuing Analysis 5 hours SLO: 1 Fast Ethernet, Gigabit Ethernet, Fiber Channel and Wireless LANs-Queuing Models-Single Server Queues.

Module:3 Congestion and Traffic management 4 hours SLO: 17

Effects of Congestion – Congestion Control-Traffic Management-Congestion Control in Packet

Switching Networks-Frame Relay Congestion Control.

Module:4 Traffic and Congestion control in TCP 6 hours SLO: 17

TCP Flow control –TCP Congestion Control: Retransmission Timer Management and Window

management –Performance of TCP over ATM

Module:5 Traffic and Congestion control in ATM 6 hours SLO: 17 Requirements-Attributes-Traffic Management Framework-Traffic Control-ABR traffic Management-GFR traffic management.

Module:6 Integrated and Differentiated Services 7 hours SLO: 17

Integrated Services Architecture – Queuing Discipline: FQ, PS, BRFQ, GPS and WFQ-Random

Early Detection-Differentiated Services.

Module:7 Protocols for QoS Support 8 hours SLO: 17

RSVP – Goals & Characteristics, Data Flow, RSVP operations ,Protocol Mechanisms-

Multiprotocol Label Switching-Operations, Label Stacking, Protocol details – RTP-Protocol

Architecture, Data Transfer Protocol, RTCP

Module:8 Industry Expert Lecture 3 hours SLO:2



videotaped],Use of Physical and computer

models to lecture, Visit to Industry, Min of 2

Lectures by industry experts

45 hours

Text Book(s)

1. William Stallings, “HIGH SPEED NETWORKS AND INTERNET”, Pearson Eductaion

,Second Edition, 2008.

Reference Books

1. Warland & Parvin Varaiya , “HIGH PERFORMANCE COMMUNICATION

NETWORKS”,JEAN Harcount Asia Pvt. Ltd., II Edition,2004.

.

2. Irvan Pepelnjk, Jim Guichard and Jeff Apcar, “MPLS and VPN architecture”, Cisco Press,

Volume 1 and 2, 2008.

3. Abhijit S.Pandya, Ercan Sea, “ATM Technology for Broad Band Telecommunication

Networks”, CRC Press, New York, 2004.



Course code Internet of Things L T P J C ITE6004 3 0 0 4 4


1.0

Course Objectives:

To study the hardware design of IoT objects

To understand the software development framework for Internet of things.

To learn the cross platform enabling technologies in IOT applications


To develop prototypes for domain specific IoTs.

To implement IoT applications for various domains.

To customize real time data for IoT applications.


Module:1 Building IoT 6 hours SLO: 2

Characterization of IoT - Physical design- Things in IoT- IoT protocols- Logical Design. Enabling

Technologies

Module:2 IoT Systems 5 hours SLO: 2 IoT levels and deployment templates -six levels

Module:3 Domain Specific IoTs 5 hours SLO:2

Smart home- smart city- Environment- Energy-Retail- Logistics- Industry- Agriculture- Health

and Lifestyle

Module:4 IoT platforms design methodology 6 hours SLO:2

Process Specification- Domain model specification- Information model specification- Service

specification- IoT level specification- Functional view specification- Operational view

specification- Device and component integration-Application development - Case Studies

Module:5 Physical Devices and End points 6 hours SLO: 6 Basic building blocks of IoT device- Examples – Raspberry PI interfaces – Arduino interfaces – programming Raspberry Pi with Python –Other IoT devices

Module:6 IoT physical servers and cloud offerings 7 hours SLO: 6

Introduction to cloud storage models and communication APIs- Xively cloud for IoT – Python

web application framework – Django- Designing RESTful web API- Amazon web services for

Iota

Module:7 IoT Analytics 7 hours SLO: 6

Batch Data Analysis-Real-time Data Analysis-Case Studies: Object Tracking , Anomaly

Detection, Mobility Pattern Analytics, Crowd Analytics, Behavior Learning and Prediction



Text Book

1. Arshdeep Bahga, Vijay Madisetti “Internet of Things - A Hands-on Approach”, Universities

Press, First Edition, 2015.

Reference Books

1. Dieter Uckelmann, Mark Harrison Florian, Michahelles “Architecting the Internet of things”,

Springer-Verlag Berlin Heidelberg, First Edition, 2011.


Course code Enterprise Operating systems L T P J C

ITE6005 3 0 0 0 3


1.0

Course Objectives:

To learn the features of advanced operating systems

To gain knowledge on mainframe OS, z /OS and virtualization concepts

To gain insight on to the IBM System x3950 Server & Memory features

To know about General Parallel File System(GPFS)


Upon Completion of the course, the students should be able to:

Acquire a complete overview of mainframe operating systems

work with virtualization products like vmware, xen and so on

work on various file system and memory management


Module:1 Introduction to Mainframe Environment

7 hours SLO: 2

Mainframe OS – An evolving architecture -Uses of mainframe computers-Typical mainframe

workloads- Mainframe hardware systems-System design -Processing - Disk devices -Clustering -

Basic shared DASD- sysplex.

Module:2 z/OS Overview 8 hours SLO: 2 z/OS-Overview of z/OS facilities-Virtual storage and other mainframe concepts - Workload management-I/O and data management-Supervising the execution of work in the system –Cross memory services-Defining characteristics of z/OS- comparison of z/OS and UNIX-Data sets Access Methods -Data set Record Format - DASD-Types of data sets -Virtual Storage Access Method - Role of DFSMS.

Module:3 Virtualization

8 hours SLO: 5

Virtualization-Virtualization concepts -Emulation versus virtualization-Hosted solutions versus

hypervisor solutions -OS virtualization -Full virtualization versus para virtualization-32-bit versus

64-bit support-Dual core CPUs-Virtualization futures.

Module:4 Virtual Storage Management (VSM) 5 hours SLO: 5

z/OS Memory/Storage Types- z/OS Memory Managers-31-Bit VSM-64-Bit VSM/RSM –End to-

End scheduling

Module:5 Scheduler

6 hours SLO: 5

Overview of Tivoli Workload Scheduler -Tivoli Workload Scheduler network-Tivoli Workload Scheduler architecture-Tivoli Workload Scheduler network -Tivoli Workload Scheduler workstation -End-to-End scheduling

Module:6 General Parallel File System(GPFS)

6 hours SLO: 5

GPFS Overview and features- Operating system and file systems with multiplatform GPFS –

Security

Module:7 Tivoli Storage Manager 3 hours SLO: 5

Network Shared Disk (NSD) creation considerations- GPFS considerations- Tivoli Storage

Manager for GPFS

Module:8 Contemporary issues 2 hours SLO: 5


Text Book(s)

1. “Introduction to the New Mainframe: z/OS Basics”, IBM Redbooks, March 2011.

Reference Books

1. “Implementing the IBM General Parallel File System (GPFS) in a Cross -

platform Environment”, IBM Redbooks, June 2011.

2. “Getting Started with IBM Tivoli Workload Scheduler” , IBM Redbooks,

2006.

3. “Virtualization on the IBM System x3950 Server”, June 2006.


Course code Wireless Networks L T P J C

ITE6006 3 0 2 4 5


1.0

Course Objectives:

To learn about different types of wireless and mobile systems

To understand the various layers in wireless network

To have in-depth knowledge in routing in a secured network


Design, implement and evaluate a wireless network, process, component, or program to meet desired

needs.

An ability to choose different MAC, routing protocols for the desired need.

An ability to use techniques, skills and simulation tools.


Module:1 Fundamentals of wireless communication 6 hours SLO: 6 Electromagnetic spectrum; Characteristics of wireless channel; Modulation techniques; Multiple access

techniques, Antennas, Radio Propagation Mechanisms-Spread Spectrum

Module:2 Fundamentals of wireless LANs, PANs, WANs,

MANs 7 hours SLO: 6

IEEE 802.11, HIPER-LAN standards; Bluetooth; HomeRF; Cellular concept and architecture, WLL, UMTS, 2G/3G Versus LTE, Next Generation Mobile Networks

Module:3 Wireless Internet 5 hours SLO: 17 Mobile IP; TCP over wireless; Wireless application protocol; Optimizing Web over wireless. Wireless

devices service technologies- SMS, USSD and VXML.

Module:4 Ad hoc wireless networks 7 hours SLO: 6 Issues and challenges in infrastructure-less networks; MAC protocols; Routing protocols; Multicast routing

protocols; Transport and security protocols; Quality of service provisioning; Energy management.

Module:5 Hybrid wireless networks 6 hours SLO: 6 Architectures and routing protocols for hybrid wireless networks; Load balancing schemes; Pricing schemes for multihop wireless networks

Module:6 Sensor Networks 7 hours SLO: 6 Issues and challenges in wireless sensor networks: Architectures and routing protocols; MAC protocols;

Data dissemination, data gathering, and data fusion; Quality of a sensor network; Real-time traffic support

and security protocols.

Module:7 Application Layer 4 hours SLO: 17 Mobile computing platforms -Energy efficiency of apps



Text Book(s)

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

Pearson Education, 2010.

Reference Books

1.

2.

3.

Asoke K. Talukder, Roopa R.Yavagal, Mobile Computing-Technology, Applications and Service

Creation, Tata McGraw Hill, 2010

Waltenegus Dargie, Christian Poellabauer, “Fundamentals of wireless sensor Networks - theory and

practice”, John Wiley & Sons, 2010

Ian F. Akyildiz, Mehmet Can Vuran, “Wireless Sensor Networks”, John Wiley & Sons, 2010.

List of Challenging Experiments SLO: 17

1. Analyze the effects of mobility with 9 nodes in wireless transmissions on reliable transport protocol.

Design a scenario based on the following properties:

i. The first 4 nodes are in subnet 1 and other 4 nodes belong to subnet 2 and one node

should be in both subnets

ii. Source is in subnet 1 and the destination is in subnet 2

iii. Give mobility to both source and destination.

2. Scenario for Cellular Network consists of 4 MSs , 1 BS,1 SC,1 gateway, 1 aggregated node. All MS

communicate with BS via radio interface. BS connects to SC, SC connects to gateway and gateway

connects to aggregated nodes. Use Cellular Abstract APP, Abstract Cellular MAC and Abstract

Physical Model. Analyze the statistical results.

3. To test how Dot11e (MAC 802.11e) protocol operates in following ad hoc network scenario. Node 1

2, 3, 4, 5,& 6 are all QSTAs. Node 2 is sending CBR packet to 5

6 1

2 5

3 4

4. To test how Dot11e (MAC 802.11e) protocol operates in Multichannel and QIBSS mode(QoS

enabled) for the following scenario. Node 1 3, 4 are in one Qos enable Wireless Subnet. Node 2 5,& 6

are in other Qos enable Wireless Subnet. Node 1 and 2 are QAP. and they are in a separate wired

subnet.Node 4 is sending CBR packet to 6

3 5

1 -------- 2

4 6

5. Illustrate a mesh network as a wireless inter-connects between non-wireless sub networks for the

following scenario. The mesh has two points of inter-connectivity with wired subnets and forms a

wireless link between them. Besides the two portals, the mesh consists of 10 MPs that are mobile

using random way-point movement. Application traffic is a mix of CBR and FTP/Generic between

wired nodes. Routing protocol is Bellman Ford.

102 ( ) 202

| ( ) |

| ( Mesh network ) |

101 ---- 100 with 10 mobile 200 ---- 201

| ( nodes ) |

| ( ) |

103 ( ) 203

6 To demonstrate how to create and run a simple wireless/wired combined scenario in 2D/3D GUI, and

analyze the performance for the following scenario.

7-------------------------HUB-----------------------8

| |

| |

1 (BaseStation1) (BaseStation2) 2

/ \ / \

3(MS1) 4(MS2) 5(MS3) 6(MS4)

7 In this scenario, 2 WiFi access points and 4 WiFi mobile terminals are deployed. Mobile terminal

(MS1) moves from the area covered by access point 1 (BaseStation1) to the area covered by access

point 2 (BaseStation2) and then return to the area covered by access point 1(BaseStation1). There is

One CBR traffic from MS1 to MS3. When MS1 moves, association/reassociation and handover are

happened between the two APs.

8 To show how to configure multiple wireless channels and specify channels for individual subnets

using listening and listenable channel masks for the following scenario. Node 1, 2, 3 are in one subnet

using wireless channel 0. Node 4, 5, 6 are in one subnet using wireless channel 1 Node 3 and 4 are in

the third subnet using wireless channel 2. Here, node 3 and node 4 have 2 dual interfaces and connect

subnet 1 and subnet 2.

--------- ---------

| 1, 2, 3-|----|-4, 5, 6 |

--------- ---------

9 Normal AODV test for 5 nodes in the following wireless scenario. CBR is used to send 10 data

segments of 1460B from node 1 to node 4.

1

/ \

/ \

/ \

2-------3

| |

4-------5

10 Tests destination sequence number update when new path is found to the same destination for the

following scenario.

simulation starts with the following topology:

1-----2-----3

mobility results in the following topology:

3-----1-----2

Node 1 sends a packet to Node 3 before mobility and another one is after mobility. The packet initially

goes to Node 3 via Node 2, but after mobility, a route error is generated by node 2.

11 To Test 802.11 Power Saving mode implementation in ad hoc mode for the following scenario. Node

1 thru 6 are connected through a wireless subnet and forms an IBSS. Here, IBSS supports PS Mode.

Node 2 is sending CBR packets to Node 5. Node 3 is sending CBR packets to Node 6.

6 1

| |

| |

| |

2-----[wireless-subnet]-----5

| |

| |

| |

6 4

12 Design the following network scenario with the following. Transfer CBR packets from 1 to 15 and

analyze and check your results with routing information. Use static routing and follow the routes

given

i. Route 1: 15 101215

ii. Route 2: 12481315

13 Design the following network scenario with the following. Transfer CBR packets from 1 to 15. Use

DSR routing protocol and analyze and check your results with routing information.

14 Analyze the performance of AODV and DSR routing protocols with 25 nodes and 50 nodes. Use

FTP/GEN application to transfer 200 packets of size 2000 bytes. Which protocol performs better in

the above scenario?

15 To test the functionality of IEEE 802.16 when running with multicast and unicast applications for the

following scenario. 1 wireless subnets (192.0.0.0) has 5 nodes (3 to 7) with node 3 as base station

(BS) and rests as MS. Node 13 is a switch. A MCBR flow is from node 1 to multicast group 225.0.0.1.

The multicast group includes nodes {7 9 10 12 14}- MCBR 1 225.0.0.1 0 512 1S 50S 3M. A CBR

flow is from node 9 to node 1 - CBR 9 1 0 512 1S 50S 3M PRECEDENCE 5. A CBR flow is from

node 10 to node 15 - CBR 10 15 0 512 1S 50S 3M PRECEDENCE 7. OSPFv2 and MOSPF are

unicast routing and multicast routing protocols respectively. The unicast and multicast packets should

be successfully received by their destinations.

1 (MCBR src)

|

|

2

|

|

3 (BS)

4 5 6 7

| | |

| | |

9-----8 11 13(switch)

| | |\

| | | \

10 12 14 15



Course code Advanced Database Systems L T P J C

ITE6007 3 0 0 4 4


1.00

Course Objectives:

To familiarize the relational database concepts.

Know the need for parallel and distributed.

Understand the usage of object, XML and spatial databases.



Analyze the collected data and Design Schemas.

Work with parallel and distributed databases.

Develop applications with complex data types.


Module:1 Relational Database Design 9 hours SLO: 7

Basics, Entity Types, Relationship Types, ER Model, ER-to-Relational Mapping algorithm.

Normalization: Functional Dependency, 1NF,2NF,3NF,BCNF,4NF and 5NF.

Module:2 Parallel Database Design 6 hours SLO: 2 Architecture , I/O Parallelism, Interquery Parallelism, Intraquery Parallelism, Intraoperation Parallelism, Interoperation Parallelism.

Module:3 Distributed Databases 6 hours SLO: 2

Architecture, Distributed data storage, Distributed transactions, Commit protocols, Concurrency

control, Query Processing.

Module:4 Object-Based Databases 5 hours SLO: 5

Complex Data Types, Structured Types and Inheritance, Table Inheritance, array and Multiset,

Object Identity and Reference Types, Object Oriented versus Object Relational.

Module:5 Spatial Database 5 hours SLO: 2 TYPES OF Spatial Data , Representation of Geometric Information, Design Databases, Geographic data, Spatial queries, Indexing of spatial data.

Module:6 XML Databases 5 hours SLO: 2

XML Hierarchical data model, XML Documents, DTD, XML Schema, XML Querying.

Module:7 Multimedia Databases 6 hours SLO: 2

Multimedia data format, Continuous media data, Similarity based retrieval. Mobility and personal

databases: A model of mobile computing, Routing and query processing, Broadcast data.

Module:8 Applications of Database in Industry-Case Studies

3 hours SLO:2



videotaped],Use of physical and computer

models to lecture, Visit to Industry, min of 2

45 hours

lectures by industry experts.

Text Book(s)

1. Abraham Silberschatz, Henry F Korth , S Sudarshan, “Database System Comcepts”, 6th

edition , McGraw-Hill International Edition , 2011.

Reference Books

1. Ramez Elmasri, Shamkant B Navathe, “Fundamental of Database Systems”, Pearson, 7th

edition , 2016.

2. Thomas Connolly, Carolyn Begg., “Database Systems a practical approach to Design ,

Inmplementation and Management “, Pearson Education, 2014..


1. Creation of Tables, Views, Synonyms, Sequence, Indexes, Save point

2. Query Processing – Implementation of an efficient query optimizer

3. Parallel queries

4. Creating Database Link, executing distributed queries

5. Creating type, varray, nested table and querying it

6. Designing Spatial Databases

7. Designing XML Schema and querying it

8. Designing multimedia database

1. a. Creating an Airline database to set various constraints and writing SQL queries to retrieve

information from the database.

b. Performing Insertion, Deletion, Modifying, Altering, Updating and Viewing records based

on conditions.

c. Creation of Views, Synonyms, Sequence, Indexes, Save point .

2. Consider the application for VIT University Counselling. The campus, department and

vacancy details are maintained in 4 sites. Students are allocated campus in these 4 sites

simultaneously. Implement this application using parallel database [State any assumptions

you have made].

3. There are 5 processors working in a parallel environment and producing output. The output

record contains campus details and students mark information. Implement parallel join and

parallel sort algorithms to get the marks from different campus of the university and publish

10 ranks for each discipline.

4. A University wants to track persons associated with them. A person can be an Employee or

Student. Employees are Faculty, Technicians and Project associates. Students are Full time

students, Part time students and Teaching Assistants. Design object based model for

university database. Write OQL for the following

a. Insert details in each object.

b. Display the Employee details.

c. Display Student Details.

d. Modify person details.

e. Delete person details.

5. Extend the design of university database by incorporating the following information.

Students are registering for courses which are handled by instructor researchers (graduate

students). Faculties are advisors to graduate students. Instructor researchers’ class is a

category with super class of faculty and graduate students. Faculty are having sponsored

research projects with a grant supporting instruction researchers. Grants are sanctioned by

different agencies. Faculty belongs to different departments. Department is chaired by a

faculty. Implement for the Insert ion and Display of details in each class

6. Design XML Schema for the given company database

Department (deptName, deptNo, deptManagerSSN, deptManagerStartDate, deptLocation )

Employee (empName, empSSN, empSex, empSalary, empBirthDate, empDeptNo,

empSupervisorSSN, empAddress, empWorksOn)

Project ( projName, projNo, projLocation, projDeptNo, projWorker )

Implement the following queries using XQuery and XPath

a. Retrieve the department name, manager name, and manager salary for every department

b. Retrieve the employee name, supervisor name and employee salary for each employee

who works in the Research Department.

c. Retrieve the project name, controlling department name, number of employees and total

hours worked per week on the project for each project.

d. Retrieve the project name, controlling department name, number of employees and total

hours worked per week on the project for each project with more than one employee working

on it

7. Implement a storage structure for storing XML database and test with the above schema




Course code Advanced Computer Architecture L T P J C

ITE6008 3 0 0 0 3


1.0

Course Objectives:

To learn the concept of 64-bit architecture, memory management, interfaces and

connectivity.

To understand Virtualization and Logical Partition (LPAR) concepts.



Design a scalable and parallel 64-bit architecture.

Develop Mainframe architecture to solve user problem.


Module:1 Introduction to 64 bit Architecture 7 hours SLO: 2 Architecture concepts - System components - Processing units – Virtual address space map - Addressing

modes - Dynamic address translation - Registers - Processor mode - Prefix saved area - Instruction

formats - Microcode concepts - Interrupts - Interrupt processing - Types of interrupts - Supervisor call

interrupt - Storage Protection - CP timer - I/O Configuration - Channel subsystem (CSS) elements -

Multiple CSS structure.

Module:2 Memory Management 7 hours SLO: 17

Module content Overview of z10 - System nomenclature - Processor Unit Instances - Book topology comparison - NUMA

topology - Multi-chip module(MCM) - Interconnection architecture of PU cores - Pipeline in z10 EC -

Techniques for instruction pipeline - Pipeline branch prediction - HDFU - Storage controller chip - Three

Levels of Cache - Software/hardware cache optimization - Central storage design - Infiband interconnect

technology.

Module:3 Interface with Enterprise System 5 hours SLO: 17 zEnterprise overview - zEnterprise parts - zBX hardware rack components - Blades types and functions -

Blades data warehouse roles - Power7 blades - WebSphere datapower appliance blades - Nodes and

ensembles - zBX networking and connectivity - IEDN.

Module:4 z/Enterprise Unified Resource Manager 4 hours SLO: 2 zManager location in zEnterprise - zManager Major roles - Energy Management - Operations Control -

zenterprise platform performance manager - PPM Virtual Servers.

Module:5 System z Connectivity 7 hours SLO: 5 Connectivity overview - Channel subsystem connectivity - CSS configuration management - ESCON architecture - Concepts - ESCD Switch functions - FICON channels - Ficon native topologies - Fiber Channel Protocol mode(FCP) FICON Switches - OSA-Express - QDIO architecture - HiperSockets Connectivity - Hardware Configuration Definition.

Module:6 Virtualization and Logical Partition (LPAR)

concepts

7 hours SLO: 5

Definitions - Concepts - Physical Resources - Hypervisor Types - Technologies - z/Virtual machine -

Power VM virtual servers - LPAR CPC Management - Types of capping - LPAR capped versus

Uncapped - Softcapping - Intelligent Resource Director (IRD) - WLM LPAR CPU Management -

Dynamic Channel Path Management(DCM) - Hardware Configuration Definition - Functions- Adding

Switches - DASD Controller capabilities.

Module:7 Overview of z13 5 hours SLO: 2 z13 highlights - z13 technical overview - Hardware Management Consoles (HMCs) and Support Elements

(SEs) - IBM z BladeCenter Extension (zBX) - IBM z Unified Resource Manager - Operating systems and

software.



Text Book(s)

1. “ABCs of z/OS System Programming”, Redbooks, Volume 10, 2012.

Reference Books

1.

2.

3.

4.

1.

“IBM z13 Technical Guide”, Redbooks, April 2015.

“IBM z13 Technical Introduction”, Redbooks, March 2015.

“IBM System z Connectivity Handbook”, Redbooks, April 2015.

“z/OS Intelligent Resource Director”, Redbooks, August 2001.



Course code Network Programming L T P J C

ITE6009 3 0 0 0 3


1.0

Course Objectives:

To understand the basics of network programming.

To establish connection and data transfer between sockets using TCP and UDP protocols

To introduce the principles and practices of secured socket programming.

Expected Course Outcome: On completion of this course, student should be able

To accomplish network programming tasks.

Implement socket programming using TCP and UDP protocols


Module:1 Network Programming 4 hours SLO: 2 Streams – InetAddresses – HTTP - Examples.

Module:2 URL 4 hours SLO: 7 URLs and URIs – URL Connection

Module:3 Sockets for Clients 7 hours SLO: 2

Using Sockets – Constructing and connecting sockets – Getting information about a socket – Setting socket options

Module:4 Sockets for Servers 7 hours SLO: 7 Using Server sockets – Constructing Server sockets – Server socket options – Examples

Module:5 Secured Sockets – I 7 hours SLO: 7

Secure Communications - Creating Secure Client Sockets - Choosing the Cipher Suites - Event Handlers - Session Management - Client Mode - Creating Secure Server Sockets.

Module:6 Secured Sockets – II 7 hours SLO: 7 Event Handlers - Session Management - Client Mode - Creating Secure Server Sockets.

Module:7 UDP 7 hours SLO: 7 UDP Protocol-UDP clients and Servers- Datagram Packet Class – Datagram Socket class – Socket options – Examples



Text Book(s)

1. Elliotte Rusty Harold “JAVA Network Programming” Fourth Edition, O’Reilly, 2014.

Reference Books

1 Jan Craba, "An Introduction to Network Programming with Java", Springer, 2013

2 Esmond Pitt, "Fundamental Networking in Java", Springer, 2010

3 David Reilly, “Java Network Programming and Distributed Computing”, Addison-Wesley, 2002.



Course code Machine Learning L T P J C

ITE6010 3 0 0 4 4


1.0

Course Objectives:

To enable students to understand different techniques related to Machine Learning.

To make students become acquainted with sequential decision-making methods in ML.

To gain basic knowledge about the key algorithms and theory that forms the foundation of machine learning


To analyze the principles, advantages, limitations and possible applications of machine learning.

Decide the suitable machine learning methods/algorithms for various type of learning problems

Apply the algorithms to a real-world problem, optimize the models learned and report on the expected accuracy that can be achieved by applying the models.

Student Learning Outcomes (SLO): 1, 2, 7

Module:1 Basics 6 hours SLO: 1

Introduction to machine learning - different forms of learning; Basics of probability theory, linear

algebra and optimization

Module:2 Regression Analysis 6 hours SLO:1 Linear regression, Ridge regression, Lasso, Bayesian regression, Regression with Basis functions

Module:3 Classification Methods 8 hours SLO: 2

Linear Discriminant Analysis, Logistic regression, Perceptrons, Large margin classification,

Kernel methods, Support Vector Machines. Classification and Regression Trees, Multi-layer

Perceptrons and Back propagation

Module:4 Graphical Models 6 hours SLO: 7

Bayesian Belief Networks, Markov Random Fields, Hidden Markov Models, Exact inference

methods, Approximate inference methods.

Module:5 Ensemble Methods 6 hours SLO: 7 Boosting - Adaboost, Gradient Boosting; Bagging - Simple methods, Random Forest.

Module:6 Computational Learning Theory 5 hours SLO: 2

PAC Learning, VC Dimension, Bias/Variance Tradeoff.

Module:7 Unsupervised Learning 5 hours SLO: 7

Clustering - k-means, EM-Mixture of Gaussians, Factor Analysis, PCA, ICA, LDA



Text Book(s)

1. Christopher M. Bishop, Pattern Recognition and Machine Learning, Springer, 2013

Reference Books

1. T. Hastie, R. Tibshirani, and J. H. Friedman. The Elements of Statistical Learning: Data Mining,

Inference and Prediction.2nd Edition, Springer, 2016.

2 Mitchell, Tom. Machine Learning. McGraw-Hill, 2013.


Course code System Modelling and Simulation L T P J C

ITE6011 3 0 0 4 4


1.00

Course Objectives:

To understand how computer simulation can be used to model complex systems and solve

related decision problems.

To understand and apply statistical methods used in simulation analysis.

To be able to run a simulation project from start to finish.


Identify different types of simulation models (e.g., stochastic-dynamic, Monte Carlo) and

give examples of situations or problems where they are appropriate.

Identify the basic steps that are used in a simulation project.

Implement and verify the model in a computer system.

Evaluate and analyze the model output, compare alternatives and make appropriate

suggestions for the real system.

Student Learning Outcomes (SLO): 1, 2,14

Module:1 Introduction 7 hours SLO: 1

Simulation Terminologies, Application areas, Discrete and Continuous Systems, Components of a

system, Model -Types of Simulation, Steps in a Simulation study, Concepts in Discrete Event

Simulation

Mathematical models:

Statistical Model, Concepts, Discrete Distribution, Continuous Distribution, Poisson Process,

Empirical Distributions

Module:2 Queueing Models and Random Numbers 6 hours SLO: 1 Characteristics, Notation, Queueing Systems, Markovian Models, Properties of random numbers, Generation of Pseudo Random numbers, Techniques for generating random numbers, Testing random number generators, Generating Random-Variates, Inverse Transform technique, Acceptance- Rejection technique, Composition & Convolution Method.

Module:3 Input Modeling 6 hours SLO: 1

Data collection, Assessing sample independence, Hypothesizing distribution family with data,

Parameter Estimation, Goodness-of-fit tests, Selecting input models in absence of data

Module:4 Verification and validation 6 hours SLO: 1

Building, Verification of Simulation Models, Calibration and Validation of Models, Validation of

Model Assumptions, Validating Input, Output Transformations.

Module:5 Output analysis for a Single system 6 hours SLO: 14 Types of Simulations with Respect to Output Analysis, Stochastic Nature of Output Data, Measures of Performance and Their Estimation, Terminating Simulations, Steady state simulations, Comparing Alternative System Configurations.

Module:6 Simulation of computer systems and case

studies

6 hours SLO: 14

Simulation Tools, Model Input, High level computer system simulation, CPU – Memory

Simulation, Comparison of systems via simulation, Simulation Programming techniques,

Development of Simulation models, Using tools.

Module:7 Simulation of Computer Networks 6 hours SLO: 14

Introduction, Traffic Modeling, Media Access Control, Token Passing Protocols, Ethernet, Data

Link Layer, TCP, Model Construction, Example.



Text Book(s)

1. Jerry Banks, John S. Carson, Barry L. Nelson and David M. Nicol, “Discrete Event System

Simulation”, Fifth Edition, PHI, 2013.

Reference Books

1. Sheldon M.Ross, “Simulation”, Fifth Edition, Academic Press Elsevier, 2012.

2. Averill M. Law, “Simulation Modeling and Analysis”, Fourth Edition, McGraw Hill, 2007.

Course code Advanced Data Mining Techniques L T P J C

ITE6012 3 0 0 0 3


1.0

Course Objectives:

To understand the guidelines and principles influences of Data Mining.

To learn the methodologies and technologies supporting advances in Data Mining



Analyze huge databases by applying various data mining techniques.

Apply data mining techniques to provide efficient solutions

Design data mining solutions to analyze real-world Data sets


Module:1 Introduction 6 hours SLO: 2

A multidimensional Data Model – Data preprocessing- Data cleaning – Data integration and

Transformation- Correlation analysis- Data Reduction

Module:2 Data Visualization and Measuring Data

Similarity

6 hours SLO: 2

Data Objects and Attribute Types, Basic Statistical Descriptions of Data, Data Visualization, Data Matrix versus Dissimilarity Matrix, Proximity Measures for Nominal Attributes ,Binary Attributes, ,Numeric Data, Ordinal Attributes ,Dissimilarity for Attributes of Mixed Types.

Module:3 Pattern Mining 6 hours SLO: 7

Mining Frequent Patterns-basic concepts-apriori principle, Pattern Mining in Multilevel,

Multidimensional Space, Constraint-Based Frequent Pattern Mining, Mining High-Dimensional

Data and Colossal Patterns

Module:4 Classification Methods 7 hours SLO: 7

Bayesian Belief Networks, Classification by Backpropagation, Support Vector Machines, k-

Nearest-Neighbour Classifiers, Genetic Algorithms, Rough Set Approach, Fuzzy Set, Model

Evaluation and Selection, Approaches, Techniques to Improve Classification Accuracy

Module:5 Cluster Analysis 7 hours SLO: 7 k-Means: A Centroid-Based Technique, k-Medoids, probabilistic Model-Based Clustering, Clustering High-Dimensional Data, Clustering Graph and Network Data, Evaluation of Clustering.

Module:6 Outlier Detection 5 hours SLO: 7

Proximity-Based Methods, and Clustering-Based Methods, Outlier Detection in High-

Dimensional Data.

Module:7 Complex Data Mining 6 hours SLO: 17

Mining Sequence Data: Time-Series, Symbolic Sequences, and Biological Sequences, Mining

Graphs and Networks, Statistical Data Mining, Visual and Audio Data Mining



Text Book(s)

1. Han J. & Kamber, M, “Data Mining: Concepts and Techniques”, Third Edition, Morgan

Kaufmann, 2012.

Reference Books

1. Pang-Ning Tan, Michael Steinbach, Vipin Kumar, “Introduction to Data Mining” Pearson,

First Edition, 2014.

2. Mohammed J.Zaki, Wagneer meira, “Data Mining and Analysis: Fundamental concepts and

algorithms”, First Edition, Cambridge University Press India, 2015

3. Ian H. Witten, & Eibe Frank, “Data Mining –Practical Machine Learning Tools and

Techniques”, 3rd Edition, Elesvier, 2011.


Course code Big Data Analytics L T P J C

ITE6013 3 0 0 4 4


1.00

Course Objectives:

Use the Hadoop Distributed File System for storing large datasets and run distributed

computations over those datasets with MapReduce.

Become familiar with Hadoop's data and I/O building blocks for compression, data

integrity, serialization and persistence.

Discover common pitfalls and advanced features for writing real-world MapReduce

programs.


Design, build and administer a dedicated Hadoop cluster, or run Hadoop in the cloud.

Apply best practices to extend data warehousing with Hadoop and other big data

technologies across business operations and industries to enable big data analytics.

Implement algorithms for analyzing and mining data streams and social network graphs.

Student Learning Outcomes (SLO): 2,7, 14

Module:1 Overview of Big Data and Data Analytics 6 hours SLO: 7

Overview of Big Data: Characteristics of Big Data-Big Data Sources- Challenges in Big Data

processing-Scalability issues; Business Intelligence v/s Data Analytics-Need of Data Analytics-

Data Analytics in Industries-Role of the Data Scientist.

Module:2 Hadoop and HDFS 6 hours SLO: 7

The Design of HDFS- HDFS Concepts- Blocks - Namenodes and Datanodes; The Command-Line Interface: Basic File system Operations; Hadoop File systems: Interfaces-The Java Interface-Data Flow; Hadoop I/O: Data Integrity-Compression-Serialization-File-based data structures.

Module:3 MapReduce 6 hours SLO: 7

Analyzing the Data with Unix Tools- Analyzing the Data with Hadoop- Map and Reduce- Java

MapReduce; Data Flow- Combiner Functions- Running a Distributed MapReduce Job; Hadoop

Streaming; Hadoop Pipes.

Module:4 Application development using MapReduce

framework

6 hours SLO: 7

The Configuration API- Configuring the Development Environment- Writing a Unit Test-

Running Locally on Test Data- Running on a Cluster- Tuning a Job- MapReduce Workflows.

Module:5 Working of MapReduce 6 hours SLO: 14 Mining Data Streams: The Stream Data Model- Sampling data in a stream- Filtering Streams- The Bloom filter; Counting distinct elements in a stream- The Flajolet-Martin Algorithm. How stream works-Streams Processing Language; Apache Spark - Introduction- Features of Apache Spark- Components of Spark- Resilient Distributed Datasets- Data Sharing using Spark RDD-Spark Streaming.

Module:6 Analytics for Big Data in motion 6 hours SLO: 14

Mining Data Streams: The Stream Data Model- Sampling data in a stream- Filtering Streams-

The Bloom filter; Counting distinct elements in a stream- The Flajolet-Martin Algorithm.

How stream works-Streams Processing Language; Apache Spark - Introduction- Features of

Apache Spark- Components of Spark- Resilient Distributed Datasets- Data Sharing using Spark

RDD-Spark Streaming.

Module:7 Analysis of Social Network Data 6 hours SLO: 14

Mining Social Network Graphs: Clustering of Social Network Graphs- Direct Discovery of

Communities- Partitioning of Graphs- Finding overlapping communities- Simrank; Sentiment

analysis- Document sentiment classification- Rules of Sentiment Composition- Sentiment

analysis using Twitter data.



Text Book(s)

1. Tom White, "Hadoop: The definitive guide",3rd Edition, O'Reilly Media, Inc., 2012.

Reference Books

1. Jure Leskovec, Anand Rajaraman, Jeff Ullman, "Mining of Massive Datasets", 2nd Edition,

Cambridge University Press, UK, 2011.

2. Paul C. Zikopoulos, Chris Eaton, Dirk deRoos, Thomas Deutsch, George Lapis,

“Understanding Big Data: Analytics for Enterprise Class Hadoop and Streaming Data,

McGraw-Hill, 2012.

3. Liu, Bing. "Sentiment analysis and opinion mining." Synthesis lectures on human language

technologies,Cambridge University Press, 2015.

4. Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia, " Learning

Spark:Lightning-Fast Big Data Analysis", O'Reilly Media, 2015.

5. David Loshin, Morgan, “Big Data Analytics: From Strategic Planning to Enterprise

Integration with Tools, Techniques, NoSQL and Graph”, Kaufman Publishers, 2013.



STUDENT LEARNING OUTCOMES (SLO)

1. Having an ability to apply mathematics and science in engineering applications

2. Having a clear understanding of the subject related concepts and of contemporary issues

3. Having an ability to be socially intelligent with good SIQ (Social Intelligence Quotient) and EQ

(Emotional Quotient)

4. Having Sense-Making Skills of creating unique insights in what is being seen or observed (Higher

level thinking skills which cannot be codified)

5. Having design thinking capability

6. Having an ability to design a component or a product applying all the relevant standards and with

realistic constraints

7. Having computational thinking (Ability to translate vast data in to abstract concepts and to

understand database reasoning)

8. Having Virtual Collaborating ability

9. Having problem solving ability- solving social issues and engineering problems

10. Having a clear understanding of professional and ethical responsibility

11. Having interest in lifelong learning

12. Having adaptive thinking and adaptability

13. Having cross cultural competency exhibited by working in teams

14. Having an ability to design and conduct experiments, as well as to analyze and interpret data

15. Having an ability to use the social media effectively for productive use

16. Having a good working knowledge of communicating in English

17. Having an ability to use techniques, skills and modern engineering tools necessary for engineering

practice

18. Having critical thinking and innovative skills

19. Having a good cognitive load management skills

20. Having a good digital footprint.

M.TECH - IT (Networking) - PROGRAMME SLO MAPPING

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y

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CODE

COURSE

TITLE

STUDENT LEARNING OUTCOMES

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0

1

1

1

2

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3

1

4

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5

1

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Mathematics for

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Engineering * * *

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of

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* *

ENG50

02

Professional and

Communication

Skills * *

FRE50

01

Foreign

Language * * * *

STS50

01 Soft skills * *

STS50

02 Soft skills * *

SET50

01

Science,

Engineering and

Technology

Project

* * *

SET50

02

Science,

Engineering and

Technology

Project

* * *

ITE609

9 Master Thesis * * * * * *

Program

me Core

ITE500

1

Advanced Data

Structures and

Algorithms * *

ITE570

2

Cloud

Computing and

Virtualization * *

ITE500

3

Computer

Networks * * *

ITE500

4

Cryptography

and Network

Security * *

ITE500

5

Open Source

Programming * * *

Program

me

Elective

ITE600

1

Network

Management * * *

ITE600

3

High Speed

Networks * * *

ITE600

4

Internet of

Things * *

ITE600

5

Enterprise

Operating

Systems * *

ITE600

6

Wireless

Networks * *

ITE600

7

Advanced

Database * * *

Systems

ITE600

8

Advanced

Computer

Architecture * * *

ITE600

9

Network

Programming * *

ITE601

0

Machine

Learning * * *

ITE601

1

System

Modeling and

Simulation * * *

ITE601

2

Advanced Data

Mining

Techniques * * *

ITE601

3

Big Data

Analytics * * *

ITE60

XX

Software

Defined

Networking *

* *