V & VI SEMESTERS - Siddaganga Institute of · PDF fileV & VI SEMESTERS 2017-18 ... Design...

Fifth and Sixth Semester of MCA May-2017-18

Department of Master of Computer Applications Page No. 1

SCHEME & SYLLABUS

OF

V & VI SEMESTERS

2017-18

Department of Master of Computer Applications

Siddaganga Institute of Technology B.H. Road, Tumakuru



Salient features of academic autonomy

Continuous learning centric system

Flexibility in selection of subjects

Provision for paced learning.

Industry relevant mandatory subjects.

Program designed for 150 credits.

Equal weightage given to Continuous Internal Evaluation (CIE)

CIE based on performance in tests, quizzes, and assignments.

The break up is as follows:

Two mid semester tests: 17x 2 = 34 marks

Four Quizzes : 3x 4 = 12 marks

Assignment(s) : 04 marks

Total : 50 marks

A student is required to secure a minimum of 40% in order to

become eligible for semester end examination (SEE).

SEE is conducted for 100 marks and then reduced to 50 marks.

Provision for summer semester to help the students who have

dropped or withdrawn or secured “F” grade in maximum of four

subjects.



VISION STATEMENT

To effectively mould quality and responsible Computer Professionals,

with a mind of service and spirituality for nurturing the technological

competence.

MISSION STATEMENT

Imparting Quality Education to Students to make them professionals

in their domain replete with IT and Computational Skills par

Excellence

Program Outcomes:

The graduates of MCA will:

a. Computational Knowledge: Apply knowledge of computing fundamentals, computing specialization, mathematics, and domain knowledge appropriate for the computing specialization to the abstraction and conceptualization of computing models from defined problems and requirements.

b. Problem Analysis: Identify, formulate, research literature, and

solve complex computing problems reaching substantiated conclusions using fundamental principles of mathematics, computing sciences, and relevant domain disciplines.

c. Design /Development of Solutions: Design and evaluate

solutions for complex computing problems, and design and evaluate systems, components, or processes that meet specified needs with appropriate consideration for public health and safety, cultural, societal, and environmental considerations.

d. Conduct Investigations of Complex Computing Problems: Use

research-based knowledge and research methods including design of experiments, analysis and interpretation of data, and synthesis of the information to provide valid conclusions.



e. Modern Tool Usage: Create, select, adapt and apply appropriate

techniques, resources, and modern computing tools to complex computing activities, with an understanding of the limitations.

f. Professional Ethics: Understand and commit to professional

ethics and cyber regulations, responsibilities, and norms of professional computing practice.

g. Life-long Learning: Recognize the need, and have the ability, to

engage in independent learning for continual development as a computing professional.

h. Project management and finance: Demonstrate knowledge and

understanding of t h e c o mp u t i n g and management principles and apply these to one’s own work, as a member and leader in a team, to 16 manage projects and in multidisciplinary environments.

i. Communication Efficacy: Communicate effectively with the

computing community, and with society at large, about complex computing activities by being able to comprehend and write effective reports, design documentation, make effective presentations, and give and understand clear instructions.

j. Societal and Environmental Concern: Understand and assess

societal, environmental, health, safety, legal, and cultural issues within local and global contexts, and the consequential responsibilities relevant to professional computing practice.

k. Individual and Team Work: Function effectively as an

individual and as a member or leader in diverse teams and in multidisciplinary environments.

l. Innovation and Entrepreneurship: Identify a timely opportunity

and using innovation to pursue that opportunity to create value and wealth for the betterment of the individual and society at large.



Mapping of PEOs with POs

PEOs

POs

a b c d e f g h i j

I X X X X X X X

II X X X X X X

III X X X X X

IV X X X X X

V X X X

Distribution of subjects Total Credits: 150

Mandatory Subjects

Sl No. Title of the Subject Semester

1. Communicative English I

2. Soft Skills III

3. Aptitude Related Analytical Skills IV

Course Type Credits Percentage of Total Credits

Mathematics 12 8.0

Professional Core

( including practical)

83

55.3

Professional Electives 20 13.3

Humanity subjects 04 2.6

Seminars(2) 02 1.3

Projects (Major & Minor) 29 19.5



Board of Studies Committee, MCA: 2017-18

Sl. No

Category Nomination of the

Committee

Name of the Person

1. Director Dept. of M C A

Chairperson Dr.M.A.Jayaram

2. Faculty members at different levels veering different specializations

Members

1.Dr. B.G.Premasudha, professor

2. Dr..Ashagowda Karegowda, Associate Professor

3. Mr. H.S.Vijayakumar, Assistant Professor

4. Mr. T.M.Kirankumar, Assistant Professor

5. Mr. C.Bhanuprakash, Assistant Professor

3. Subject experts from outside the college nominated by Academic Council

Member

Dr.S.Natarajan, Professor, Dept. of Info Sc.& Engg., Bangalore

4. Expert from outside college, nominated by VTU.

Member

Dr.Kavya.N.P., Professor and Head, Dept.of MCA, RNSIT, Banaglore

5. Representative from Industry/Corporate sector.

Member

Dr.Gopal Krishna Sharma Director FISERV India Pvt. Ltd., Bangalore

6. Postgraduate Meritorious alumnus nominated by Principal/Chairman

Member

Mr. N.V.Kumar Technical Evangelist INFOSYS LTD, Mysore.

7. Co-opted members and also distinguished aluminii.

1.Mr. Chandrashekar Senior Project Manager HP Ltd, Bangalore

2. B. Shesha Pani Senior Project Manager Capegemini India Private Ltd., Banagalore



SCHEME OF TEACHING AND SYLLABI

V-VI SEMESTER MCA PROGRAMME

V Semester MCA

Sl.

No

Subject Code Title Hours/week Credits

L T Lab

1. 5MCA01 Object-Oriented Modeling

and Design Patterns

4 -- -- 4

2. 5MCA03 Data Mining 4 --- -- 4

3. 5MCAEX Elective-3 4 --- -- 4

4. 5MCAEX Elective-4 4 --- --- 4

5. 5MCAEX Elective-5 4 --- --- 4

6. 5MCAL4 Data mining Lab --- 1 3 2

7. 5MCAL2 Software Design Laboratory --- --- 2 1

8. 5MCAL3 Mini Project --- --- 3 2

Total Credits 25

Total Contact Hours/week 29

VI Semester

Sl.

No

Subject Code

Title Hours/week Credits

L T Lab

1. 6MCA01 Major Project --- -- -- 25



List of Electives 1. Elective-3 (Research oriented/Thrust Areas)

5MCAE1: Fuzzy Logic and Applications.

5MCAE2: Soft Computing Techniques.

5MCAE3: Computational Intelligence.

5MCAE4: Pattern recognition.

5MCAE5: Digital Image Processing

5MCAE6: Wireless Sensor Networks

5MCAE7: Information & Network Security

5MCAE22: Storage Area Network

5MCAE23: Cloud Computing

2. Elective–4 (Software Engineering Stream)

5MCAE8: Software Quality Management.

5MCAE9: Software Agents.

5MCAE10: Software Testing.

5MCAE11: Supply Chain Management

5MCAE12. Software Project Management.

3. Elective–5 (Generic stream)

5MCAE13: System Simulation and Modeling.

5MCAE14: Web 2.0 & Rich Internet Applications

5MCAE15: Distributed Computing.

5MCAE16: Mobile Computing.

5MCAE17: Web Programming.

5MCAE18: Data Warehousing and Data Mining.

5MCAE19: Information Retrieval

5MCAE20: Ad Hoc Wireless Networks

5MCAE22: Topics in Enterprise Architectures–II 5MCAE23: Cloud Computing



Detailed Syllabi for V semester

5MCA01: Object-Oriented Modeling and Design



Patterns

Credits: 4 Total Hours: 52 Lecture Hours/week: 4 SEE marks: 50 CIE marks: 50

Course Learning Objectives (CLO):

The objectives of the course are to :

To become familiar with all phases of Object-Oriented Modeling and

Design (OOMD)

To master the main features of the Unified Modeling Language (UML)

To master the main concepts of Object Technologies and how to apply

them at work

To develop the ability to analyze and solve challenging Problem

Domains

To learn the Object Design Principles and understand how to apply

them toward implementation

Course outcomes:

On successful completion of this course, the student will be able to:

Structure computer programs using object-oriented methodologies.

Gain experience using object-oriented methods include inheritance and

polymorphism.

Learn how to apply design patterns to the solution of programming

problems.

Learn about ethics and effective communication.

Gain experience developing software using different design patterns.

UNIT-1 10 Hrs.

What is Object Orientation? What is OO development? OO themes;

Evidence for usefulness of OO development; OO modeling history.

Modeling as Design Technique: Modeling; abstraction; The three models.

Class Modeling: Object and class concepts; Link and associations concepts;

Generalization and inheritance; A sample class model; Navigation of class

models; Practical tips.

Advanced object and class concepts; Association ends; N-ary associations;

Aggregation;

Abstract classes; Multiple inheritance; Metadata; Reification; Constraints;

Derived data;

Packages; Practical tips.

State Modeling: Events, States, Transitions and Conditions; State diagrams;



State diagram behavior; Practical tips.

UNIT-2 10 Hrs

Advanced State Modeling: Nested state diagrams; Nested states; Signal

generalization;

Concurrency; A sample state model; Relation of class and state models;

Practical tips.

Interaction Modeling: Use case models; Sequence models; Activity models.

Use case relationships; Procedural sequence models; Special constructs for

activity models.

Process Overview: Development stages; Development life cycle.

System Conception: Devising a system concept; Elaborating a concept;

Preparing a problem statement.

Domain Analysis: Overview of analysis; Domain class model; Domain state

model; Domain interaction model; Iterating the analysis.

UNIT-3

10 Hrs

Application Analysis: Application interaction model; Application class

model; Application state model; Adding operations.

Overview of system design; Estimating performance; Making a reuse plan;

Breaking a system in to sub-systems; Identifying concurrency; Allocation of

sub-systems; Management of data storage; Handling global resources;

Choosing a software control strategy; Handling boundary conditions;

Setting the trade-off priorities; Common architectural styles; Architecture of

the ATM system as the example.

UNIT- 4

10 Hrs

Class Design: Overview of class design; Bridging the gap; Realizing use

cases; Designing algorithms; Recursing downwards, Refactoring; Design

optimization; Reification of behavior; Adjustment of inheritance;

Organizing a class design; ATM example. Implementation Modeling:

Overview of implementation; Fine-tuning classes; Fine-tuning

generalizations; Realizing associations; Testing. Legacy Systems: Reverse

engineering; Building the class models; Building the interaction model;

Building the state model; Reverse engineering tips; Wrapping;

Maintenance.

UNIT-5 12 Hrs.



What is a pattern and what makes a pattern? Pattern categories;

Relationships between patterns; Pattern description; Communication

Patterns: Forwarder-Receiver; Client- Dispatcher-Server; Publisher-

Subscriber; Management Patterns: Command processor; View Handler;

Idioms: Introduction; What can idioms provide? Idioms and style; Where to

find Idioms; Counted Pointer example.

Text Books:

1. Michael Blaha, James Rumbaugh: Object-Oriented Modeling and Design

with UML, 2nd Edition, Pearson Education, 2005. (Chapters 1 to 17, 23)

2. Frank Buschmann, Regine Meunier, Hans Rohnert, Peter Sommerlad,

Michael Stal: Pattern-Oriented Software Architecture, A System of

Patterns, Volume 1, John Wiley and Sons, 2006.(Chapters 1, 3.5, 3.6, 4)



5MCA03: Data Mining

Credits: 4 Total Hours: 52 Lecture Hours/week: 4 SEE marks: 50 CIE marks: 50 Course Learning Objective (CLO):

To realize the need of Data Warehousing, Data Mart and Data mining.

To understand the architecture of Data warehousing and OLAP operations

To realize the significance of data preprocessing for data warehouse and data mining

To learn the data mining algorithms mainly classification, association rule mining and clustering to discover the hidden patterns

To learn any one data mining tool.

Course outcomes:

Apply data mining algorithms for real world applications

Carry out final year major project using data mining and data warehouse concepts

Publish papers applying data mining concepts

Apply data prepossessing steps and data mining algorithm using R Unit I : Data Warehouse : 10 Hrs What is Data warehouse?, Differences between operational database systems, A multidimensional data model: data cubes, starts, snowflakes and fact constellations, Concept hierarchies, OLAP operations in multidimensional data model, Data warehouse architecture – steps for the design and construction of data warehouses, a three tier data warehouse architecture, types of OLAP servers, Data warehouse implementation – efficient computational of data cubes, Indexing OLAP data. What motivated data mining? What is data mining? Unit II: Data Preprocessing 12 Hrs Why preprocess data, Descriptive data summarization – measuring the central tendency, dispersion of data, graphic displays of basic descriptive data summaries, Data cleaning - missing values, noisy data, data cleaning as process, Data integration and Transformation , data reduction – data cube aggregation, attribute subset selection, dimensionality reduction, numerosity reduction , Data discretization and concept hierarchy generations .



Unit III : Classification and Prediction 12 Hrs What is classification and prediction?, issues regarding classification and prediction, classification by decision tree induction – attribute selection method – information gain, gain ratio, Gini index, Tree pruning, Lazy learners- k-nearest-neighbor classifiers, case based reasoning, Prediction Accuracy and error measures- classifier accuracy measure, predictor error measures, Evaluating the accuracy of a classifier or predictor – holdout method and random sub sampling, cross validation, bootstrap. Unit IV: Association Rule mining 09 Hrs Market basket analysis, frequent itemsets, closed itemsets, and association rules , Association Rule mining: Association Rule Mining Basic concepts, frequent item sets, The Apriory Algorithm, Generating association rules from frequent item sets. Association Rule Mining without candidate generation -using FP-growth algorithm, Mining multilevel association rules, mining multidimensional association rules. Unit V. Clustering 09 Hrs. Clustering: What is Cluster analysis? Types of data in cluster analysis- interval-scaled variables, binary variables, categorical, ordinal, ratio-scaled variables, variables of mixed types, vector objects, A categorization of major clustering methods, Partitioning Methods: The K-means method and k-mediods method Hierarchical methods: Agglomerative and Divisive hierarchical clustering, Dendrogram, Measures for distance between clusters: Minimum distance, maximum distance, average distance (Clusters Problems using these measures). Text Books: 1. Data Mining Concepts and Techniques- Jiawei Han & Micheline Kamber

Morgan Kaufmann Publishers – Second Edition ) Unit I- Chapter 1 and 3 – (1.1, 1.2, 3.1.1, 3.1.2, 3.2.1, 3.2.2, 3.2.3, 3.2.5, 3.2.6, 3.3.1, 3.3.2, 3.3.5, 3.4.1, 3.4.2, 3.4.3) Unit II – Chapter 2: (2,1, 2,2, 2,3, 2,4, 2,5, 2,6) Unit III – Chapter 6: (6.1, 6.2, 6.3.1, 6.3.2, 6.3,3, 6.9.1, 6.9.2, 6.11.1-6.11.36.12, 6.13) Unit IV Chapter 5: (5.1.1, 5.1.2, 5.1.3, 5.2.1, 5.2.2, 5.2.4, 5.3.1, 5.3.2) Unit V - Chapter 7: (7.1, 7.2.1-7.2.5, 7.3, 7.4.1, 7.5.1)

References: 1. Introduction to Data mining – Pang-Ning Tan, Michael Steinbach, Vipin

Kumar, Pearson Education.



Elective-3 (Research oriented/Thrust Areas) 5MCAE1: Fuzzy Logic and Applications


UNIT-1 12 Hrs

INTRODUCTION: Historical perspective, utility of fuzzy systems, limitations of fuzzy systems,statistics and random processes, uncertainty in information, fuzzy sets and membership, chance versus fuzzyness, sets as points in Hypercube. CLASSICAL SETS AND FUZZY SETS: classical sets, operations on them, mapping of classical sets to functions, fuzzy sets, fuzzy set operations, properties of fuzzy sets, non interactive fuzzy sets. CLASSICAL RELATIONS AND FUZZY RELATIONS: Cartesian Product, Crisp Relations - Cardinality of Crisp Relations, Operations on Crisp Relations, and Properties of Crisp Relations, Composition. Fuzzy Relations - Cardinality of Fuzzy Relations, Operations on Fuzzy Relations, Properties of Fuzzy Relations, Fuzzy Cartesian Product and Composition, Noninteractive Fuzzy Sets. Tolerance and Equivalence Relations – Crisp Equivalence Relation, Crisp Tolerance Relation, Fuzzy Tolerance and Equivalence Relations. Value Assignments - Cosine Amplitude, Max-min Method, Other Similarity methods. UNIT-2 12 Hrs

MEMBERSHIP FUNCTIONS: Features of the Membership Function, Standard Forms and Boundaries, Fuzzification, defuzzification to crisp sets, Lambda-Cuts for Fuzzy Sets, Lambda-Cuts for Fuzzy Relations, Defuzzification Methods. Development of membership Functions: Membership value assignments, intuition, inference, rank ordering, neural networks, genetic algorithms, inductive reasoning. UNIT-3 12Hrs

FUZZY ARITHMETIC AND THE EXTENSION PRINCIPLE - Crisp Functions, Mapping and Relations, Functions of fuzzy Sets – Extension Principle, Fuzzy Transform (Mapping), Practical Considerations. Fuzzy Numbers Interval Analysis in Arithmetic, Approximate Methods of



Extension - Vertex method, DSW Algorithm, Restricted DSW Algorithm, Comparisons. Fuzzy Vectors. LOGIC AND FUZZY LOGIC: Classical Predicate Logic –Tautologies, Contradictions, Equivalence, Exclusive Or Exclusive Nor, Logical Proofs, Deductive Inferences. Fuzzy Logic, Approximate Reasoning, Fuzzy Tautologies, Contradictions, Equivalence and Logical Proofs, Other forms of the Implication Operation, Other forms of the Composition Operation. UNIT- 4 8 Hrs

FUZZY RULE BASED SYSTEMS: Natural Language, Linguistic Hedges, Rule-Based Systems - Canonical Rule Forms, Decomposition of Compound Rules, Likelihood and Truth Qualification, Aggregation of Fuzzy Rules. Graphical Techniques of Inference. UNIT-5 8 Hrs

FUZZY CLASSIFICATION: Classification by equivalence relations, fuzzy relations, cluster analysis, cluster validity, C-means clustering, hard-c means(HCM), fuzzy c-means(FCM), fuzzy c-means algorithm, classification metric, hardening the fuzzy partition and similarity relations from clustering.

Text Book:

1. Timothy J. Ross, Fuzzy Logic with Engineering Applications, Wiley India, II Edition, 2010 reprint.

Chapters 1,2,3,4,5,6,Chapter 11 (Part I only), 12, Reference Books:

1. John Yen, Reza Langari, Fuzzy Logic- Intelligence, Control, and information, Pearson Education, 2004.

2. George J.Klir , Bo Yuan, Fuzzy Sets and Fuzzy Logic-Theory and Applications, Prentice Hall of India, 2000.



5MCAE2: Soft Computing Techniques

Credits: 4 Total Hours: 52 Lecture Hours/week: 4 SEE marks: 50 CIE marks: 50 UNIT-1 10 Hrs

Introduction- Intelligent systems-machine intelligence, meaning of intelligence, dynamics of intelligence, intelligent machines, knowledge-based systems-architecture of knowledge based systems, development of expert systems, processing, soft computing UNIT-2 10 Hrs

Fundamentals of fuzzy logic systems, fuzzy sets, fuzzy logic operations, generalized fuzzy operations, implications, some definitions, fuzziness and fuzzy resolution, fuzzy relations, composition and inference, extension principle. UNIT-3 12 Hrs

Connectionist modeling and neural networks, learning and acquisition knowledge, features of artificial neural networks, neural network activation functions, learning algorithms, fundamentals of connectionist modeling. UNIT- 4 10 Hrs

Major classes of neural networks, the multiplayer perceptron, radial basis function networks, Kohonen’s self-organizing network, Industrial and commercial applications of neural networks. UNIT-5 10 Hrs

Evolutionary computing, overview, genetic algorithms and optimization, the schema theorem, genetic algorithm operators, selection, crossover, mutation, mode of operations in GA, steps for implementing Gas. Text Book: 1. Karry F.O and Silva C.D., Soft Computing and Intelligent Systems, Pearson Education. (Chapters: 1, 2, 4, 5, 8) Reference Book: 1.Shivanandam, Deepa, Principles of Soft Computing, Wiley India Ltd.



5MCAE3: Computational Intelligence


UNIT-1 08Hrs

Introduction, Definitions, biological basis for neural nets, biological versus artificial neural nets, chromosomes, biological versus artificial chromosomes, behavioural motivations for fuzzy logic, Myths about computational intelligence, neural networks, evolutionary computation, fuzzy logic.

UNIT-2 08 Hrs

Computational intelligence, adaptation, adaptation versus learning, three space adaptation, self-organization and evolution, evolution beyond Darwin, Historical views, Computational intelligence as adaptation and self organization, ability to generalize. Soft computing versus hard computing

UNIT-3 12Hrs

Evolutionary computation concepts and paradigms, History of evolutionary computation, genetic algorithms, evolutionary programming, genetic programming, particle swarm optimization, towards unification, evolutionary computation overview, overview of genetic algorithms, GA problem, GA operations, schemata and schema. Particle swarm optimization.

UNIT- 4 12 Hrs

Neural network paradigms and concepts, Neural network history, components and terminology, neural network topologies, neural network adaptation, comparing neural networks and other information processing models, Kalman filters, correlation, radial basis functions. Preprocessing and post processing.

UNIT-5 12 Hrs

Neural network implementation, topology, back-propagation network initialization, leraning vector quantization, BPN supervised adaptation, LVQ adaptation, issues in evolving neural networks, BPN implementation, Kohonen feature maps , implementation, Text Book: 1. Eberhart, Computational Intelligence, Elsevier India publications.

Reference Book: 1. David poole, Allan Macworth, Randey Goebal, Computational Intelligence

– A Logical Approach, Oxford University Press, New York.



5MCAE4: Pattern recognition


UNIT-1 08 Hrs

Introduction: Applications of pattern recognition, statistical decision theory, image processing and analysis. Probability: Introduction, probability of events, random variables, Joint distributions and densities, moments of random variables, estimation of parameters from samples, minimum risk estimators UNIT-2 08 Hrs

Statistical Decision Making: Introduction, Baye’s Theorem, multiple features, conditionally independent features, decision boundaries, unequal costs of error, estimation of error rates, the leaving-one—out technique. Characteristic curves, estimating the composition of populations.

UNIT-3 10Hrs

Nonparametric Decision Making: Introduction, histograms, Kernel and window estimators, nearest neighbor classification techniques, adaptive decision boundaries, adaptive discriminate Functions, minimum squared error discriminate functions, choosing a decision making technique. UNIT- 4 14 Hrs

Clustering: Introduction, hierarchical clustering, partitioned clustering UNIT-5 12 Hrs

Processing of Waveforms and Images: Introduction, gray level sealing transfoniiations, equalization, geometric image and interpolation, Smoothing, transformations, edge detection, Laplacian and sharpening operators, line detection and template matching, logarithmic gray level sealing, the statistical significance of image features.

Text Book: 1. Eart Gose, Richard Johnsonburg and Steve Joust, “Pattern Recognition and Image Analysis”, Prentice-Hall of India-2003.

Reference Book: 1. Duda and Hart, “Pattern recognition (Pattern recognition a scene analysis)”,PHI Learning private Limited, 2009



5MCAE5: Digital Image Processing

Credits: 4 Total Hours: 52 Lecture Hours/week: 4 SEE marks: 50 Lab session 1hr/week CIE marks: 50 Course Learning Objectives (CLO): The objectives of the course are to :

Provide the student with the fundamentals of digital image processing.

Give the students a taste of the applications of the theories taught in the subject.

Give the students a useful skill base that would allow them to carry out further study should they be interested and to work in the field.

Course outcomes: On successful completion of this course, the student will be able to: Demonstrate understanding of the basic concepts of two-dimensional signal

acquisition, sampling, and quantization.

Explain of spatial filtering techniques, including linear and nonlinear methods.

Understanding of the Human Visual System (HVS) and its affect on image perception and understanding.

Apply image enhancement algorithms such as histogram modification, contrast manipulation, and edge detection.

Apply image processing skills in related problems /project works. Contribute to teamwork and show communication skills through course

projects.

UNIT-1 10 Hrs.

Introduction, digital image processing, fundamental steps in digital image processing, components of digital image processing system. Elements of visual perception, image sensing and acquisition, image sampling and quantization, some basic relationships between pixels. Intensity transformation and spatial filtering, Background, some basic intensity transformation functions

UNIT-2

10 Hrs.

Histogram processing, fundamentals of spatial filtering, smoothing spatial filters sharpening of spatial filters. UNIT-3 10 Hrs.

Filtering in the frequency domain, background, preliminary concepts,



sampling and the Fourier transform of sampled functions. Image restoration and reconstruction, noise models, restoration in the presence of noise only spatial filtering, estimating the degradation, inverse filtering.

UNIT- 4 10 Hrs.

Color Image Processing, color fundamentals, color models, pseudo color image processing, basics of full color image processing color transformations, formulation and color complements, smoothing and sharpening. Image compression, fundamentals, coding redundancy, come basic compression methods. UNIT-5 12 Hrs.

Morphological Image processing, preliminaries, erosion and dilation, opening and closing, hit-or-miss transformation. Image Segmentation, fundamentals, point, line and edge detection.

Text Book:

1. Rafael C. Gonzaliz and Richard E.Woods, Digital Image Processing, III edition, Pearson education, 2008. 1.1, 1.4, 1.5, 2.1,2.3,2.4, 2.5, 3.1-3.6, 4.1-4.3, 5.1-5.3, 5.6.1,5.7, 6.1-6.4, 6.5.1, 6.5.2, 6.6, 8.1-8.2.4, 9.1-9.4, 10.1-10.2.3

Reference Books:

1. W.K.Pratt, Digital Image Processing, McGraw Hill, New Delhi. 2. Malay K. Pakhira, Digital Image Processing and Pattern

Recognition,Prentice Hall of India, 2011.

Self Study Component:

Students have to learn MatLab and prepare a report of analysis of an image of their choise. This report shall be considered as assignment component and shall be valued for 4 marks.



5MCAE6: Wireless Sensor Networks Credits: 4 Total Hours: 52 Lecture Hours/week: 4 SEE marks: 50

CIE marks: 50 Prerequisites: 1. Good knowledge in physical, networking and application layer and

making major design tradeoffs across the layers. 2. This course require some rudimentary knowledge of linear algebra,

elementary probability and estimation theory, graph theory, networking protocols, databases and distributed systems.



This course will provide students with a comprehensive introduction of wireless sensor network area.

It creates awareness in new set of research challenges – involving design and analysis of self-configuration protocols and distributed algorithms that are energy-efficient, fault tolerant and scalable.

This course also aims to train students in the craft of academic research . Course outcomes: On successful completion of this course, the student will be able to:

Understanding of the Integration of the simple processing, storage, sensing, and communication capabilities into small-scale, low-cost devices and joining them into so-called wireless sensor networks.

Understanding this new type of networks is a formidable challenge. A key characteristic is the need to understand issues from many diverse areas, ranging from low-level aspects of hardware and radio communication to high-level concepts like databases or middleware and to the applications.

Students are able to understand the design of the routing technique for exploiting the various sources of information to find destination of a packet.

The explicit construction of the routing tables with implicit topology/ neighborhood information via positions will enable the students to take up some interesting projects or writing a paper.

Efforts can be made to prepare a paper in a team to inculcate the research culture.

UNIT I 10 Hrs. Introduction: The vision of Ambient Intelligence, Application examples, Types of applications, Challenges for WSNs, Why are sensor networks different, Enabling technologies. Single node architecture, Hardware components, Energy consumption of sensor nodes. Some examples of sensor nodes. (1.1 to 1.6,2.1,2.2,2.4,)



UNIT II 12 Hrs. Network architecture, Sensor network scenarios, Optimization goals & figures of merit. Design principles for WSNs. MAC Protocols: Fundamentals of (wireless) MAC protocols, Contention-based protocols, Schedule-based protocols, The IEEE 802.15.4 MAC protocol. How about IEEE 802.11 and Blue tooth? Link Layer Protocols. Fundamentals: Tasks and requirements, Error control, Framing. (3.1,3.2, 3.3,5.1 to 5.8) UNIT III 12 Hrs. Naming and Addressing: Fundamentals, Address and name management in wireless sensor networks, Content-based and geographic addressing. Localization and Positioning: Properties of positioning, Possible approaches, and Single-hop localization, Positioning in multi-hop environments, Impact of anchor placement. (7.1,7.2,7.5,7.6,9.1,9.2,9.4,9.5,9.6) UNIT IV 9 Hrs. Routing protocols: The many faces of forwarding and routing, Gossiping and agent-based unicast forwarding , Energy-efficient unicast. Broadcast and multicast. Geographic routing. Introduction: Data-centric routing, (11.1 to11.5,12.1, 12.2) UNIT V 9 Hrs. Data aggregation, Data-centric storage. Transport Layer and Quality of Service, The transport layer and QoS in wireless sensor networks, Coverage and deployment , Reliable data transport, Block delivery, Congestion control and rate control (12.3,12.4,13.1to 13.3,13.5,13.6) Text books: 1. Holger Karl, Andreas Willig “Protocols and Architectures for Wireless

Sensor Networks” John Wiley & Sons, Ltd References: 1. Feng Zhao, Leonidas Guibas: “Wireless Sensor Networks – An

Information Processing Approach”, Elsevier, 2004. 2. Edgar H. Callaway Wireless Sensor Networks Architectures and

Protocols, Auerbach Publications 2004 Self Study Component: Students have to submit a paper on recent research work taking place in the area of wireless sensor network shall be considered as assignment component and shall be valued for 4 marks.



5MCA E7: Information & Network Security

Credits: 4 Total Hours: 52 Lecture Hours/week: 4 SEE marks: 50

CIE marks: 50

Unit-1 6 Hrs Planning for Security Introduction; Information Security Policy, Standards, and Practices; The Information Security Blue Print; Contingency plan and a model for contingency plan. Unit-2 12 Hrs Security Technology Introduction; Physical design; Firewalls; Protecting Remote Connections Introduction; Intrusion Detection Systems (IDS); Honey Pots, Honey Nets, and Padded cell systems; Scanning and Analysis Tools Unit-3 8 Hrs Cryptography Introduction; A short History of Cryptography; Principles of Cryptography; Cryptography Tools; Attacks on Cryptosystems. Unit-4 14 Hrs Introduction to Network Security, Authentication Applications Attacks, services, and Mechanisms; Security Attacks; Security Services; A model for Internetwork Security; Internet Standards and RFCs

Kerberos, X.509 Directory Authentication Service. Electronic Mail Security Pretty Good Privacy (PGP); S/MIME Unit-5 IP Security 12 Hrs IP Security Overview; IP Security Architecture; Authentication Header; Encapsulating Security Payload; Combining Security Associations; Key Management. Web Security Web security requirements; Secure Socket layer (SSL) and Transport layer Security (TLS); Secure Electronic Transaction (SET)



Text Books:

1. Michael E. Whitman and Herbert J. Mattord: Principles of Information Security, 2nd Edition, Thomson, 2005. (Chapters 5, 6, 7, 8; Exclude the topics not mentioned in the syllabus)

2. William Stallings: Network Security Essentials: Applications and Standards, Pearson Education, 2000. (Chapters: 1, 4, 5, 6, 7, 8)

Reference Book:

1. Behrouz A. Forouzan: Cryptography and Network Security, Special Indian Edition, Tata McGraw-Hill, 2007.



5MCA22: Storage Area Network


Objectives of the course:

Compare Server Centric IT architecture and Storage Centric architecture and study Intelligent Disk Systems.

Understand the Fibre channel Technology.

Compare SAN and NAS architectures.

Understand Storage virtualisation at various levels.

Analyse the various fault situations to maintain Data availability

Analyse the performance bottleneck of Network back-up

Gain knowledge to plan and implement the SAN infrastructure.

Outcomes of the course:

Upon completion of this course the student will be able to:

Explain the advantages of Storage Centric IT Architecture over Server Centric IT Architecture.

Describe various FC and IP Storage protocols.

Explain the working of Network attached storage and storage area networks.

Iluustrte how different RAID levels can provide storage virtualisation

Demonstrate the knowledge of Storage virtualization at various levels of SAN

Develop solutions for data availability.

Work on Storge Networks in industry with prior hands on training.

UNIT 1 11Hrs.

1.INTRODUCTION: Server Centric IT Architecture and its Limitations; Storage – Centric IT Architecture and its advantages; Case study: Replacing a server with Storage Networks; The Data Storage and Data Access problem; The Battle for size and access. 2.INTELLIGENT DISK SUBSYSTEMS - 1:

Architecture of Intelligent Disk Subsystems; Hard disks and Internal I/O

Channels, JBOD, Storage virtualization using RAID and different RAID

levels – RAID0, RAID 1, RAID 10, RAID 2 and RAID 3, RAID 4 and RAID 5.

A comparison of RAID levels



UNIT 2 12 Hrs.

3. INTELLIGENT DISK SUBSYSTEMS & I/O TECHNIQUES

Intelligent Disk subsystems - Caching - Acceleration of Hard Disk Access,

Intelligent disk subsystems, Availability of disk subsystems.

I/O TECHNIQUES – The Physical I/O path from the CPU to the Storage System; SCSI basics, and storage networks, Fibre Channel Protocol Stack; Fibre Channel SAN; IP Storage. UNIT 3 09 Hrs.

5. FILE SYSTEM AND NAS: Local File Systems; Network file Systems and file servers; Shared Disk file systems; Comparison of Fibre Channel and NAS. UNIT 4 09 Hrs.

6. STORAGE VIRTUALIZATION: Definition of Storage virtualization; Implementation Considerations; Storage virtualization on Block or file level; Storage virtualization on various levels of the storage Network; Symmetric & Asymmetric storage virtualization in the Networks. UNIT 5 11 Hrs 7. Applications of Storage Networks: Storage Sharing- disk storage pooling, dynamic tape library sharing, data sharing. Availability of data – failure of I/O bus, Failure of server, Failure of disk subsystem, failure of virtualization in the storage network, Failure of a data center based upon the case study. Adaptability and scalability of IT system’s – clustering for load distribution, web architecture- case study. TEXT BOOKS: 1. Storage Networks Explained – Ulf Troppens, Rainer Erkens and

Wolfgang Muller, John Wiley & Sons, 2009. UNIT 1- Chapter 1: 1.1, 1.2, 1.3 Chapter 2: 2.1, 2.2, 2.3, 2.4, 2.5 -2.5.1- 2.5.7 UNIT 2- Chapter 2.6,2.7 Chapter 3- 3.1, 3.2, 3.3,3.4, 3.5 UNIT 3- Chapter 4,1, 4,2, 4.3, 4.4 UNIT 4- Chapter 5 – 5.3, 5.4, 5.5.,5.6, 5.7 UNIT 5- Chapter 6- 6.2, 6.3, 6.4

REFERENCE BOOKS: 1. Storage Area Network Essentials: A Complete Guide to understanding

and Implementing SANs – Richard Barker and Paul Massiglia, John Wiley India, 2002.

2. Storage Networking Fundamentals Marc Farley, Cisco Press, 2005.



Elective–4 (Software Engineering Stream)

5MCAE8: Software Quality Management


UNIT-1 10 Hrs

Introduction To Software Quality

Software Quality – Hierarchical models of Boehm and McCall – Quality measurement – Metrics measurement and analysis – Gilb’s approach – GQM Model UNIT-2 10 Hrs

Software Quality Assurance Quality tasks – SQA plan – Teams – Characteristics – Implementation – Documentation – Reviews and Audits UNIT-3 11 Hrs

Quality Control And Reliability

Tools for Quality – Ishikawa’s basic tools – CASE tools – Defect prevention and removal – Reliability models – Rayleigh model – Reliability growth models for quality assessment

UNIT- 4 10 Hrs

Quality Management System Elements of QMS – Rayleigh model framework – Reliability Growth models for QMS – Complexity metrics and models – Customer satisfaction analysis.

UNIT-5

11 Hrs

Quality Standards Need for standards – ISO 9000 Series – ISO 9000-3 for software

development – CMM and CMMI – Six Sigma concepts.



Text Books:

1. Allan C. Gillies, “Software Quality: Theory and Management”, Thomson

Learning, 2003. (UI : Ch 1-4 ; UV : Ch 7-8)

2. Stephen H. Kan, “Metrics and Models in Software Quality Engineering”,

Pearson Education (Singapore) Pte Ltd., 2002. (UI : Ch 3-4; UIII : Ch 5-8 ;

UIV : Ch 9-11)

Reference Books:

1. Norman E. Fenton and Shari Lawrence Pfleeger, “Software Metrics” Thomson, 2003

2. Mordechai Ben – Menachem and Garry S.Marliss, “Software Quality”, Thomson Asia Pte Ltd, 2003.

3. Mary Beth Chrissis, Mike Konrad and Sandy Shrum, “CMMI”, Pearson Education (Singapore) Pte Ltd, 2003.

4. ISO 9000-3 “Notes for the application of the ISO 9001 Standard to software development.



5MCAE9: Software Agents


UNIT-1 11 Hrs

Agent and User Experience: Interacting agents, agents from direct manipulation to deligation-interface agent metaphor with character designing agents- direct manipulation versus agent path to predictable. UNIT-2 11 Hrs

Agents for learning in intelligent assistance Agents for information sharing and coordination-agents that reduce work information overhead-agents without programming language-life like computer character-S/W agents for cooperative learning-architecture of intelligent agents.

UNIT-3 10 Hrs

Agent Communication and collaboration Overview of agent oriented programming-agent communication language-agent based framework of interoperability.

UNIT- 4 10 Hrs

Agent Architecture Agents for information gathering-open agent architecture-communicative action for artificial agent. UNIT-5

10 Hrs

Mobile Agents Mobile agent paradigm-mobile agent concepts-mobile agent technology-case study: Tele script, Agent Tel Text Books: 1. Jeffrey M.Bradshaw, Software agents, MIT Press, 2000 ( Units 1,2,3 & 4) 2. William R.Cockayne, Michael Zyda, Mobile agents, Prentice Hall, 1998

( Unit 5). Reference Book: 1 Russel and Norvig, Artificial Intelligence: A Modern Approach, prentice Hall, 2nd Edition, 2002.



5MCAE10: Software Testing


Course Learning Objectives (CLO): The objectives of the course are to:

1. To understand the principles of software testing. 2. To identify the need for testing. 3. Identify Testing Process. 4. Identify the types of tests to be conducted on applications. 5. Describe various types of Test and their objectives.

Course outcomes: On successful completion of this course, the student will be able to:

1. Explain importance of testing 2. Explain overview of Testing process 3. Explain types of testing in various phases of software development 4. Recall content of a test plan 5. Explain test execution in detail

UNIT-1 10 Hrs Introduction to testing as an engineering activity The evolving profession of software engineering, the role of process in software quality, testing as a process. Testing fundamentals: Initiating a study of testing, basic definitions, why testing is necessary? What is testing? The psychology of testing? Software quality assurance group, software-testing principles, The Tester’s Role in a Software Development Organization. UNIT II 12 Hrs The test development life cycle (TDLC), when should testing stop?; Verification strategies; review, walkthrough, inspection Testing types and techniques; white box testing: basis path testing, flow graph notation, cyclomatic complexity, graph matrices, loop testing Black box testing: boundary value analysis, equivalence partitioning, graph based testing methods, error guessing.



UNIT III 14 Hrs Levels of testing; The Need for Levels of Testing, Unit Test, Unit Test Planning, Designing the Unit Tests. The Class as a Testable Unit, Running the Unit tests and Recording results, Integration tests, Designing Integration Tests, Integration Test Planning, System Test – The Different Types, Regression Testing, Alpha, Beta and Acceptance Tests, Web testing: Introduction to web testing, web testing process and techniques, cross browser testing, web browser error messages, Performance testing UNIT IV 10 Hrs Test planning: what is test plan; why to plan test? Template for test plan; guidelines for creating the test plan; risk analysis Test design: importance; test design essentials; good test case; test case mistakes; test case template; test design stages. UNIT V 06 Hrs Test execution: Objectives; execution considerations; execution activities Defect management: what is defect; defect life cycle; defect management process. TEXT BOOK:

1. Ilene Burnstein, “Practical software testing”, Springer international edition.

2. Foundations of software testing ISTQB certification (Level I) by Dorothy graham, Erik van veenendaal, Rex black.

REFERENCE

1. Boris Beizer, “software system testing and quality assurance” , vannostrand reinhold ,newyork

2. Gordon schulmeyer , , “zero defect software” , McGraw –hill book co 3. Watts Humphrey, Managing the software process, Addison

weselypub.co.inc.



5MCAE11: Supply Chain Management Credits: 4 Total Hours: 52 Lecture Hours/week: 4 SEE marks: 50 CIE marks: 50

Unit-1 12 Hrs Introduction to Supply Chain, Performance of Supply Chain What is a Supply Chain; Decision phases in a supply Chain; Process view of a Supply Chain; The importance of Supply Chain Flows; Examples of Supply Chains. Competitive and Supply Chain strategies; Achieving strategic fit; Expanding strategic scope.

Supply Cain drivers and Obstacles, Designing Distribution Network Drivers of Supply Chain Performance; A framework for structuring drivers; Facilities, Inventory, Transportation, and Information; Obstacles to achieve strategic fit The role of distribution in the Supply Chain; factors influencing distribution network design; Design options for a distribution network; the value of distributors in the Supply Chain; Distribution Networks in practice.

Unit-2 14 Hrs Network Design The role of network design in the Supply Chain; Factors influencing Network design Decisions; A framework for Network Design Decisions; Models for facility Location and Capacity Allocation; making Network Design decisions in practice.

The impact of uncertainty on Network design; Discounted cash flow analysis; Representations of uncertainty; Evaluating Network Design decisions using Decision Trees; Making Supply Chain decisions under uncertainty in practice.

Demand Forecasting, Aggregate Planning The role of forecasting in a Supply Chain; Characteristics of forecast; Components of a forecast and forecasting methods; Basic approach of Demand forecasting; Time series forecasting methods; Measures of forecast errors; The role of aggregate planning in a supply Chain; The aggregate planning problem; Aggregate planning strategies.

Unit-3 Inventory Management 13 Hrs The role of cycle inventory in a supply Chain; Economies of scale to exploit fixed costs, quantity discounts; Short-term discounting; Managing multi-echelon cycle inventory; Estimating cycle inventory related costs in practice.



Transportation The role of transportation in the Supply Chain; Factors affecting transportation decisions; Modes of transportation and their performance characteristics; Design options for a transportation network; Trade-offs in transportation design; Tailored transportation; Routing and scheduling in transportation; Making transportation decisions in practice.

Unit-4 7 Hrs Pricing and Revenue Management, Coordination The role of revenue management in Supply Chain; revenue management for multiple customer segments, perishable assets, seasonal demand, and bulk and spot contracts; Using revenue management in practice Lack of Supply Chain coordination and Bullwhip effect; Effect of lack of coordination on performance; Obstacles to coordination in the Supply Chain; managerial levers to achieve coordination; Building strategic partnerships and trust within a supply Chain; Achieving coordination in practice.

Unit-5 6 Hrs IT, Internet and Supply Chain The role of IT in the Supply Chain; The Supply Chain IT framework; CRM; Internal SCM; Supplier Relationship Management; The transaction management foundation; The future if IT in SCM; Supply Chain It in practice. The role of E-Business in Supply Chain; The E-Business framework; The B2B addition to the E-Business framework; E-Business in practice

Text Book:

1. Sunil Chopra, Pter Meindl: Supply Chain Management Strategy, Planning, and Operation, 2nd Edition, Prentice-Hall of India, 2004. (Chapters 1, 2, 4, 4, 5, 6, 7, 8.1 to 8.3, 10, 14, 15, 16, 17, 18)

Reference Books:

1. David Simchi-Levi, Philp Kaminky, Edith Simchi-Levi: Designing and Managing The Supply Chain Concepts, Strategies & Case Studies, 3rd Edition, Tata McGraw Hill, 2003.

2. R.P. Mohanty, S.G. Deshmukh: Supply Chain Management Theories & Practices, Bizmantra, 2005.

3. Rahul V. Altekar: Supply Chain Management Concepts and Cases, PHI, 2005.

4. M Martin Christopher: Logistics and Supply Chain Management, 2nd Edition, Pearson Education, 1998.



5MCAE12: Software Project Management Credits: 4 Total Hours: 52 Lecture Hours/week: 4 SEE marks: 50

CIE marks: 50


Deliver successful software projects that support organization's strategic goals

Match organizational needs to the most effective software development model

Plan and manage projects at each stage of the software development life cycle (SDLC)

Create project plans that address real-world management challenges

Develop the skills for tracking and controlling software deliverables

Course outcomes: On successful completion of this course, the student will be able to: Evaluate and select the most desirable projects.

Identify desirable characteristics of effective project managers.

Apply appropriate approaches to plan a new project.

Apply appropriate methodologies to develop a project schedule.

Develop a suitable budget for a new project.

Identify important risks facing a new project.

Apply appropriate techniques to assess ongoing project performance.

UNIT-1 12Hrs

Introduction to Project Management Importance of software project management: What is a project? Problems with Software Projects What are Project Management? Stages of Project. The Feasibility Study. The Cost-benefit Analysis. Planning. Project Execution. Project and Product Life Cycles. The Stakeholder of Project. All parties of project. The Role of Project Manager. Project Management Framework.

Project Planning Integration Management. what is Integration Management. Project Plan Development. Plan Execution.Scope Management. what is Scope Management?. Methods for Selecting Projects. Project Charter. Scope Statement. Work Breakdown Structure. Stepwise Project Planning Overview. Main Steps in Project Planning. UNIT-2 15Hrs

Project Scheduling Time Management. Importance of Project Schedules. Schedules and Activities. Sequencing and Scheduling Activity. Project Network Diagrams.



Network Planning Models. Duration Estimating and Schedule Development. Critical Path Analysis. Program Evaluation and Review Technique (PERT).

Project Cost Management Importance and Principles of Project Cost Management. Resource Planning. Cost Estimating. Types of Cost Estimates. Expert Judgment. Estimating by Analogy. COCOMO Model. Cost Budgeting. Cost Control. UNIT-3 12Hrs

Project Quality Management Quality of Information Technology Projects. Stages of Software Quality Management Quality Planning. Quality Assurance. Quality Control. Quality Standards. Tools and Techniques For Quality Control. Project Human Resources Management What is Project Human Resources Management?. Keys to Managing People. Organizational Planning. Issues in Project Staff Acquisition and Team Development. UNIT- 4 04Hrs

Project Communication Management Communications Planning. Information Distribution. Performance Reporting. Administrative Closure. Suggestions for Improving Project Communications.

UNIT-5 09Hrs

Project Risk Management The Importance of Project Risk Management. Common Sources of Risk in IT projects. Risk Identification. Risk Quantification. Risk Response Development and Control. Project Procurement Management Importance of Project Procurement Management. Procurement Planning. Solicitation. Source Selection. Contract Administration. Contract Close-out.

Text Books: 1: Kathy Schwalbe, “Information Technology Project Management”, International Student Edition, THOMSON Course Technology, 2003 2: Bob Hughes and Mike Cotterell, “Software Project Management”, Third Edition, Tata McGraw-Hill.

Reference Books: 1: Basics of Software Project Management, NIIT, Prentice-Hall India, 2004. 2: Pankaj Jalote, Software Project Management in Practice, Pearson Ed., 2002. 3: S.A. Kelkar, Software Project Management, a Concise Study, Revised

Edition, Prentice-Hall India, 2003



Elective–5 (Generic stream) 5MCAE13: System Simulation and Modeling

Credits: 4 Total Hours: 52 Lecture Hours/week: 4 SEE marks: 50

CIE marks: 50 Course Learning Objectives (CLO): The objectives of the course are to :

To judge whether simulation can be a useful both an analysis tool for predicting the effects of changes to existing systems.

To Identify the major capabilities and limitations of discrete-event simulation for modeling types of systems

To define a simulation model for a practical business scenario.

To describe the generation of random number, input modeling, output analysis and comparison of alternative system

To determine the appropriate simulation model to solve any real-world problems.

Course outcomes: On successful completion of this course, the student, will be able to:

Define basic concepts in modeling and simulation

Classify various simulation models and give practical examples for each category.

Explore the effects of randomness on system behavior and performance.

Generate and test random numbers and variates and apply them to develop simulation models

Fit statistical distributions to input data.

UNIT-1 10 Hrs

Introduction to Simulation When simulation is the appropriate tool and when it is not appropriate, Advantages and disadvantages of Simulation, Areas of application, Systems and system environment, Components of a system, Discrete and continuous systems, Model of a system, Types of Models, Discrete-Event System Simulation, Steps in a Simulation Study. Queueing Models: Characteristics of queuing systems, Queuing notation.

UNIT-2 10 Hrs

Simulation Examples Simulation examples: Simulation of queuing systems, Simulation of inventory



systems. Other Examples of Simulation.

General Principles Concepts in Discrete-Event Simulation: The Event-Scheduling / Time-Advance Algorithm, World Views, Manual simulation Using Event Scheduling.

UNIT-3 12 Hrs

Random-Number Generation Properties of random numbers, Generation of pseudo-random numbers, Techniques for generating random numbers, Tests for Random Numbers. Random-Variate Generation : Inverse transform technique, Acceptance-Rejection technique. UNIT- 4 08 Hrs

Input Modeling Data Collection, Identifying the distribution with data, Parameter estimation, Goodness of Fit Tests. UNIT-5 12 Hrs

Verification and Validation of Simulation Models Model building, verification and validation, Verification of simulation models, Calibration and validation of models Output Analysis for a Single Model Types of simulations with respect to output analysis, Stochastic nature of output data, Measures of performance and their estimation, Output analysis for terminating simulations.

Text Book: 1. Jerry Banks, John S. Carson II, Barry L. Nelson, David M. Nicol: Discrete-Event System Simulation, 4th Edition, Pearson Education / PHI, 2007. (Chapters1, 2, 3, 4.4, 4.5, 5, 6.1 to 6.3, 6.4.1, 6.6, 7, 8, 9, 10, 11, 12.4) Reference Books: 1. Lawrence M. Leemis, Stephen K. Park: Discrete – Event Simulation: A First Course, Pearson Prentice-Hall, 2006. 2. Averill M. Law: Simulation Modeling and Analysis,4th Edition, TMH, 2007.



5MCAE14: Web 2.0 & Rich Internet Applications Credits: 4 Total Hours: 52 Lecture Hours/week: 4 SEE marks: 50

CIE marks: 50 Unit-1 6 Hrs Introduction, Ajax - 1 Web 2.0 and Rich Internet Applications, Overview of Ajax, Examples of usage of Ajax: Updating web page text, Chatting in real time, Dragging and dropping, Downloading images. Creating Ajax Applications: An example, Analysis of example ajax.html, Creating the JavaScript, Creating and opening the XMLHttpRequest object, Data download, Displaying the fetched data, Connecting to the server, Adding Server-side programming, Sending data to the server using GET and POST, Using Ajax together with XML. Unit-2 7 Hrs Ajax – 2 Handling multiple XMLHttpRequest objects in the same page, Using two XMLHttpRequest objects, Using an array of XMLHttpRequest objects, Using inner functions, Downloading JavaScript, connecting to Google Suggest, Creating google.php, Downloading from other domains with Ajax, HTML header request and Ajax, Defeating caching, Examples. Building XML and working with XML in JavaScript, Getting the document element, Accessing any XML element, Handling whitespace in Firefox, Handling cross-browser whitespace, Accessing XML data directly, Validating XML, Further examples of Rich Internet Applications with Ajax. Unit-3 13 Hrs Ajax – 3 Drawing user’s attention to downloaded text, Styling text, colors and background using CSS, Setting element location in the web pages, Setting the stacking order of web page elements, Further examples of using Ajax. Displaying all the data in an HTML form, Working with PHP server variables, Getting the data in to array format, Wrapping applications in to a single PHP page, Validating input from the user, Validating integers and text, DOM, Appending new elements to a web page using the DOM and Ajax, Replacing elements using the DOM, Handling timeouts in Ajax, Downloading images with Ajax, Example programs.



Flex - 1 Introduction: Understanding Flex Application Technologies, Using Flex Elements, Working with Data Services (Loading Data at Runtime), The Differences between Traditional and Flex Web Applications, Understanding How Flex Applications Work, Understanding Flex and Flash Authoring. Building Applications with the Flex Framework: Using Flex Tool Sets, Creating Projects, Building Applications, Deploying Applications Framework Fundamentals: Understanding How Flex Applications Are Structured, Loading and Initializing Flex Applications, Understanding the Component Life Cycles, Loading One Flex Application into Another Flex Application, Differentiating Between Flash Player and the Flex Framework, Caching the Framework, Understanding Application Domains, Localization, Managing Layout: Flex Layout Overview, Making Fluid Interfaces, Putting It All Together. Unit-4 13 Hrs Flex – 2 MXML: Understanding MXML Syntax and Structure, Making MXML Interactive Working with UI Components: Understanding UI Components, Buttons, Value Selectors, Text Components, List-Based Controls, Pop-Up Controls, Navigators, Control Bars. Customizing Application Appearance: Using Styles, Skinning components, Customizing the preloader, Themes, Runtime CSS Flex - 3 ActionScript: Using ActionScript, MXML and ActionScript Correlations, Understanding ActionScript Syntax, Variables and Properties, Inheritance, Interfaces, Handling Events, Error Handling, Using XML Unit-5 13 Hrs Flex - 4 Managing State: Creating States, Applying States, Defining States, Adding and Removing Components, Setting Properties, Setting Styles, Setting Event Handlers, Using Action Scripts to Define States, Managing Object Creation Policies, Handling State Events, Understanding State Life Cycles, When To Use States. Using Effects and Transitions: Using Effects, Creating Custom Effects, Using Transitions, Creating Custom Transitions.



Flex - 5 Working with Data: Using Data Models, Data Binding, Enabling Data Binding for Custom Classes, Data Binding Examples, Building data binding proxies. Validating and Formatting Data: Validating user input, Formatting Data. Text Books:

1. Steven Holzner: Ajax: A Beginner’s Guide, Tata McGraw Hill, 2009. (Listed topics from Chapters 3, 4, 6, 7, 11, 12)

2. Chafic Kazon and Joey Lott: Programming Flex 3, O’Reilly, 2009. (Listed topics from Chapters 1 to 8, 12 to 15)

Reference Books: 1. Getting Started with Flex 3, Jack Herrington and Emily Kim, O’Reilly,

1st Edition, 2008. 2. Flex 3: A Beginner’s Guide, Michele E. Davis and John A. Phillips,

Tata McGraw-Hill, 2008. 3. Essential Actionscript 3.0 – Colin Moock, O’Reilly Publications, 2007. 4. Professional Ajax, Nicholas C Zakas et al, Wrox Publications, 2006.



5MCAE15: Distributed Computing Credits: 4 Total Hours: 52 Lecture Hours/week: 4 SEE marks: 50

CIE marks: 50

UNIT-1 10 Hrs

Introduction: Characterization of Distributed Systems - Examples - Resource Sharing and the Web - Challenges - System Models - Architectural and Fundamental Models - Networking and Internetworking - Types of Networks - Network Principles - Internet Protocols - Case Studies. UNIT-2 12 Hrs

Processing and Distributed Objects Interprocess Communication - The API for the Internet Protocols - External Data Representation and Marshalling - Client-Server Communication - Group Communication - Case Study - Distributed Objects and Remote Invocation - Communication Between Distributed Objects - Remote Procedure Call - Events and Notifications - Java RMI - Case Study. UNIT-3

10 Hrs

Operating System Issues-I The OS Layer - Protection - Processes and Threads - Communication and Invocation – OS Architecture - Security - Overview - Cryptographic Algorithms - Digital Signatures - Cryptography Pragmatics - Case Studies - Distributed File Systems - File Service Architecture - Sun Network File System - The Andrew File System. UNIT- 4 10 Hrs

Operating System Issues-II Name Services -Domain Name System - Directory and Discovery Services - Global Name Service - X.500 Directory Service - Clocks, Events and Process States - Synchronizing Physical Clocks - Logical Time And Logical Clocks - Global States - Distributed Debugging - Distributed Mutual Exclusion – Elections – Multicast Communication Related Problems.

UNIT-5

10 Hrs

Distributed Transaction Processing Transactions - Nested Transactions - Locks - Optimistic Concurrency Control -



Timestamp Ordering - Comparison - Flat and Nested Distributed Transactions - Atomic Commit Protocols - Concurrency Control in Distributed Transactions - Distributed Deadlocks - Transaction Recovery - Overview of Replication And Distributed Multimedia Systems Text Book:

1. George Coulouris, Jean Dollimore and Tim Kindberg,Distributed Systems Concepts and Design, Pearson Education, 3rd Edition, 2002.

Reference Books:

1. M.L.Liu, Distributed Computing Principles and Applications, Pearson Education, 2004.

2. Andrew S Tanenbaum , Maartenvan Steen, Distibuted Systems –Principles and Pardigms,Pearson Education, 2002

3. Mugesh Singhal,Niranjan G Shivaratri, Advanced Concepts in Operating Systems,Tata McGraw Hill Edition, 2001.



5MCAE16: Mobile Computing Credits: 4 Total Hours: 52 Lecture Hours/week: 4 SEE marks: 50

CIE marks: 50

UNIT-1 10 Hrs

Introduction to Mobile Communications and Computing: Mobile Computing (MC): Introduction to MC, Mobility, novel applications, limitations, and architecture. GSM: Mobile services, System architecture, Radio interface, Protocols, Localization and calling, Handover, Security, and New data services. UNIT-2 10 Hrs

(Wireless) Medium Access Control : Motivation for a specialized MAC (Hidden and exposed terminals, Near and far terminals), SDMA, FDMA, TDMA, CDMA. Protocols and Tools: Wireless Application Protocol-WAP. (Introduction, protocol architecture) UNIT-3 12 Hrs

Mobile IP Network Goals, assumptions, entities and terminology, IP packet delivery, location management,agent advertisement and discovery, registration, tunneling and encapsulation, Route optimizations. Traditional TCP, Indirect TCP, Snooping TCP, Mobile TCP, Fast retransmit/fast recovery, Transmission /time-out freezing, Selective retransmission, Transaction oriented TCP,TCP over 3G Mobile Networks. UNIT- 4 10 Hrs

Data delivery mechanisms, push-based mechanisms, pull-based mechanisms, hybrid mechanisms, selective tuning (indexing) techniques. Properties of a MANET, spectrum of MANET applications, routing and various routing algorithms, security in MANETs. UNIT-5 10 Hrs

Wireless LAN (WiFi) Architecture and protocol layers. Bluetooth Enabled devices Network. Bluetooth (User scenarios, physical layer, MAC layer, networking, security, link management).

http://www.indiastudychannel.com/resources/31505-JNTU-IV-Year-B-Tech-CSE-I-Semester-syllabus-for-MOBILE-COMPUTING.aspx



Text Books:

1. Jochen Schiller,“Mobile Communications”,Addison-Wesley.

(Chapters 4,7,9,10,11), second edition,2004.

2. Stojmenovic and Cacute, “Handbook of Wireless Networks and Mobile Computing”, Wiley, 2002, ISBN 0471419028. (Chapters 11, 15, 17, 26 and 27)

Reference Books:

1. Reza Behravanfar, “Mobile Computing Principles: Designing and Developing Mobile Applications with UML and XML”, ISBN: 0521817331, Cambridge University Press, October 2004,

2. Adelstein, Frank, Gupta, Sandeep KS, Richard III, Golden , Schwiebert, Loren, “Fundamentals of Mobile and Pervasive Computing”, ISBN: 0071412379, McGraw-Hill Professional, 2005.

3. Hansmann, Merk, Nicklous, Stober, “Principles of Mobile Computing”, Springer, second edition, 2003.



5MCAE17: Web Programming


Unit-1 13 Hours Fundamentals of Web, XHTML, CSS Internet, WWW, Web Browsers and Web Servers, URLs, MIME, HTTP, Security, The Web Programmers Toolbox. XHTML: Basic syntax, Standard structure, Basic text markup, Images, Hypertext Links. Lists, Tables, Forms, Frames. CSS: Introduction, Levels of style sheets, Style specification formats, Selector forms, Property value forms, Font properties, List properties, Color, Alignment of text, The box model, Background images, The <span> and <div> tags, Conflict resolution. Unit-2 13 Hours Javascript Overview of Javascript, Object orientation and Javascript, Syntactic characteristics, Primitives, operations, and expressions, Screen output and keyboard input, Control statements, Object creation and modification, Arrays, Functions, Constructors, Pattern matching using regular expressions, Errors in scripts, Examples. Javascript and HTML Documents, Dynamic Documents with Javascript The Javascript execution environment, The Document Object Model, Element access in Javascript, Events and event handling, Handling events from the Body elements, Button elements, Text box and Password elements, The DOM 2 event model, The navigator object, DOM tree traversal and modification. Introduction to dynamic documents, Positioning elements, Moving elements, Element visibility, Changing colors and fonts, Dynamic content, Stacking elements, Locating the mouse cursor, Reacting to a mouse click, Slow movement of elements, Dragging and dropping elements.

Unit-3 13 Hours XML Introduction, Syntax, Document structure, Document type definitions, Namespaces, XML schemas, Displaying raw XML documents, Displaying XML documents with CSS, XSLT style sheets, XML processors, Web services.



Perl, CGI Programming Origins and uses of Perl, Scalars and their operations, Assignment statements and simple input and output, Control statements, Fundamentals of arrays, Hashes, References, Functions, Pattern matching, File input and output; Examples. The Common Gateway Interface; CGI linkage; Query string format; CGI.pm module; A survey example; Cookies. Database access with Perl and MySQL

Unit-4 6 Hours PHP Origins and uses of PHP, Overview of PHP, General syntactic characteristics, Primitives, operations and expressions, Output, Control statements, Arrays, Functions, Pattern matching, Form handling, Files, Cookies, Session tracking, Database access with PHP and MySQL. Unit-5 7 Hours Ruby, Rails Origins and uses of Ruby, Scalar types and their operations, Simple input and output, Control statements, Arrays, Hashes, Methods, Classes, Code blocks and iterators, Pattern matching. Overview of Rails, Document requests, Processing forms, Rails applications with Databases, Layouts.

Text Book: 1. Robert W. Sebesta: Programming the World Wide Web, 4th Edition,

Pearson education, 2008. (Listed topics only from Chapters 1 to 9, 11 to 15)

Reference Books: 1. M. Deitel, P.J. Deitel, A. B. Goldberg: Internet & World Wide Web How

to Program, 3rd Edition, Pearson education, 2004. 2. Chris Bates: Web Programming Building Internet Applications, 3rd

Edition, Wiley India, 2006. 3. Xue Bai et al: The web Warrior Guide to Web Programming, Thomson,

2003.



5MCAE18: Data Warehousing and Data Mining


Data Warehouse Unit I : Data Warehouse : The Building Blocks 10 Hrs Defining Features: subject oriented, integrated data, time-variant data, nonvolatile data and data granularity. Data Warehouses and Data Marts , Overview of the Components: source data component, data staging , data storage, information delivery component, metadata , management and control component. Metadata in the Data warehouse: types and significance of metadata. Unit II: Data Design and Data Preparation 12 Hrs Principles of Dimensional Modeling: Star Schema, Snowflake Schema Data Extraction, Transformation and Loading: ETL Overview: ETL Requirements and Steps. Data Extraction: Source identification, Data Extractions Techniques, Evaluation of the Techniques. Data Transformation: Basic tasks, major transformation types, data integration and consolidations, transformations for dimension attributes, how to implement transformation. Data Loading: Applying data Techniques and Processes, Data refresh versus update, Procedure for dimension tables, Fact Tables: history and incremental loads. Unit III : OLAP in the Data Warehouse 10 Hrs Demand for Online Analytical Processing: Need for multidimensional analysis, fast access and powerful calculations, limitations of other analysis methods, OLAP definitions, rules and characteristics. Major Features and Functions: General features, dimensional analysis, What are hyper cubes?, drilldown and roll-up, slice and dice or rotations and benefits of OLAP. OLAP Models: MOLAP, ROLPA, ROLAP vs. MOLAP. OLAP implementations Considerations: Data design and Preparations, Administrations and Performance. Data Mining Unit IV: Classfication & Association Rule mining 10 Hrs What is Data mining? Classfication what is classfication and prediction? Eager learners: Decision tree induction, attribute selection. Lazy learners: k-nearest-Neighbor classifiers. Prediction: Linear Regression, Nonlinear Regression.



Association Rule mining: Association Rule Mining Basic concepts, frequent item sets, The Apriory Algorithm, Generating association rules from frequent item sets. Unit V. Clustering and Association Rule mining 10 Hrs Association Rule Mining using FP-growth algorithm. Clustering: What is Cluster analysis? Types of data in cluster analysis. Clustering methods. Partitioning Methods: The K-means method. Hierarchical methods: Agglomerative and Divisive hierarchical clustering, Dendrogram, Measures for distance between clusters: Minimum distance, maximum distance, average distance (Clusters Problems using these measures) Text Books:

1. Paulraj Ponniah, “Data Warehousing Fundamentals”, John Wiley. Unit I - Chapter 2 Unit II - Chapter 10 (pp. 210- 219), Chapter 11 ( pp 235-238), Chapter 12 Unit III- Chapter 15.

2. Data Mining Concepts and Techniques - Jiawei Han & Micheline

Kamber Morgan Kaufmann Publishers – Second Edition ) Unit IV - Chapter 6.1, 6.3.1, 6.3.2, 6.9.1, 6.11.1, 6.11.2

Chapter 5: 5.1, 5.2.1,5.2.2 Unit V - Chapter 5 : 5.2.4 Chapter 7: 7.1, 7.2, 7.4.1,7.5.1

Reference Books:

1. W.H. Inmon, “Building the Data Warehouses”, Wiley Dreamtech. 2. R. Kimball, “The Data Warehouse Toolkit”, John Wiley. 3. E.G. Mallach, “Decision Support and Data Warehouse systems”,

TMH. 4. Introduction to Data mining – Pang-Ning Tan, Michael Steinbach,

Vipin Kumar, Pearson Education.



5MCAE19: Information Retrieval


Unit-1 13 Hrs. Introduction, Retrieval Strategies Introduction; Retrieval Strategies: Vector Space Model; Probabilistic Retrieval strategies, Some More Retrieval Strategies: Language Models; Inference Networks; Extended Boolean Retrieval; Latent Semantic Indexing; Neural Networks; Genetic Algorithms; Fuzzy Set Retrieval. Unit-2 13 Hrs. Retrieval Utilities Relevance feedback; Clustering; Passage-Based Retrieval; N-Grams; Regression Analysis; Thesauri; Semantic Networks; Parsing. Indexing and Searching Introduction; Inverted Files; Other indices for text; Boolean queries; Sequential searching; Pattern matching; Structural queries; Compression. Unit-3 12 Hrs. Cross-Language Information Retrieval and Efficiency Introduction; Crossing the language barrier; Cross-Language retrieval strategies; Cross language utilities. Duplicate Document Detection. Integrating Structured Data and Text Review of the relational model; A historical progression; Information retrieval as a relational application; Semi-structured search using a relational schema; Multi-dimensional data model. Unit-4 7 Hrs. Parallel Information Retrieval, Distributed Information Retrieval Parallel text scanning; Parallel indexing; Clustering and classification; Large parallel systems; A theoretic model of distributed information retrieval; Web search; Result fusion; Peer-to-Peer information systems; Other architectures. Unit-5 7 Hrs. Multimedia IR Introduction; data modeling; Query languages; Spatial access methods; A general multimedia indexing approach; One-dimensional time series; Two-dimensional color images; Automatic picture extraction.



Text Books: 1. David A. Grossman, Ophir Frieder: Information Retrieval Algorithms

and Heuristics, 2nd Edition, Springer, 2004. (Chapters 1, 2, 3, 4, 5, 6, 7, 8)

2. Ricardo Baeza-Yates, Berthier Ribeiro-Neto: Modern Information Retrieval, Pearson Education, 1999 (Chapters 8, 11, 12)

Reference Book: 1. William B. Frakes, Ricardo Baeza-Yates (Editors): Information

Retrieval Data Structures & Algorithms, Prentice Hall PTR, 1992.



5MCAE20: Ad Hoc Wireless Networks Credits: 4 Total Hours: 52 Lecture Hours/week: 4 SEE marks: 50 CIE marks: 50

UNIT-I 10 Hours. Introduction to Wireless Communication Technology: Fundamentals, the Electromagnetic Spectrum, Radio Propagation Mechanisms, Characteristics of the Wireless Channel. Wireless LANs : Fundamentals of WLANs, IEEE 802.11 standard, Bluetooth. Wireless WANs : The Cellular Concept, Cellular Architecture, The First-Generation cellular Systems, The Second-Generation cellular Systems, The Third-Generation cellular Systems. Wireless Internet : What is Wireless Internet? Mobile IP, TCP in Wireless Domain. UNIT-II 10 Hours. Ad hoc Networks: Introduction, Issues in Ad hoc wireless networks, Ad hoc wireless internet. MAC – 1: MAC Protocols for Ad hoc wireless Networks: Introduction, Issues in designing a MAC protocol for Ad hoc wireless Networks, Design goals of a MAC protocol for Ad hoc wireless Networks, Classification of MAC protocols, Contention based protocols with reservation mechanisms. UNIT-III 11 Hours. Routing protocols for Ad hoc wireless Networks: Introduction, Issues in designing a routing protocol for Ad hoc wireless Networks, Classification of routing protocols, Table drive routing protocol, On-demand routing protocol. UNIT-IV 12 Hours. Transport layer protocols for Ad hoc wireless Networks: Introduction, Issues in designing a transport layer protocol for Ad hoc wireless Networks, Design goals of a transport layer protocol for Ad hoc wireless Networks, Classification of transport layer solutions, TCP over Ad hoc wireless Networks, Other transport layer protocols for Ad hoc wireless Networks. Security: Security in Ad hoc wireless Networks, Network security requirements, Issues & challenges in security provisioning, Network security attacks, Key management, Secure routing in Ad hoc wireless Networks.



UNIT-V 09 Hours. QoS: Quality of service in Ad hoc wireless Networks: Introduction, Issues and challenges in providing QoS in Ad hoc wireless Networks, Classification of QoS solutions, MAC layer solutions, network layer solutions. Text Books:

1. C. Siva Ram Murthy & B. S. Manoj: Ad hoc Wireless Networks, 2nd Edition, Pearson Education, 2005 [ Chapter 1: 1.1, 1.2, 1.3, 1.4. Chapter 2: 2.1, 2.2, 2.3, 2.5. Chapter 3: 3.1, 3.2, 3.3, 3.4, 3.5, 3.6. Chapter 4: 4.1, 4.2, 4.3, 4.4. Chapter 5, Chapter 6: 6.1-6.6, Chapter 7, Chapter 9, Chapter 10. ]

Reference Books:

1. Ozan K. Tonguz and Gianguigi Ferrari: Ad hoc Wireless Networks, John Wiley, 2007.

2. Xiuzhen Cheng, Xiao Hung, Ding-Zhu Du: Ad hoc Wireless Networking, Kluwer Academic Publishers, 2004.

3. C.K. Toh: Adhoc Mobile Wireless Networks- Protocols and Systems, Pearson Education, 2002.



5MCAE22: Topics in Enterprise Architectures–II


Course Learning Objectives:


Microsoft.NET Framework is a computing platform for developing

distributed applications for the Internet. Following are the design goals of

Microsoft .NET Framework:

To provide a very high degree of language interoperability

To provide a runtime environment that completely manages code

execution

To provide a very simple software deployment and versioning model

To provide high-level code security through code access security and

strong type checking

To provide a consistent object-oriented programming model

To facilitate application communication by using industry standards

such as SOAP and XML.

To simplify Web application development

Course outcomes:

After the completion of the course, the students will be able to:

Understand, analyze and explain .NET Framework and C#.

Quickly learn how the basics are created in C#, such as variables,

loops, libraries, and objects.

Transfer the existing programming knowledge to the C# language.

Understand, analyze and use basic C# constructs, delegates, events,

language interfaces, and inheritance.

Display proficiency in C# by building stand-alone applications in the

.NET framework using C#.

.

Unit-1 11 Hrs

The philosophy of .NET

Introducing the Building Blocks of the .NET Platform (the CLR, CTS, and

CLS), Additional .NET-Aware Programming Languages, An Overview of

.NET Assemblies, Understanding the Common Type System,

Understanding the Common Language Specification, Understanding the

Common Language Runtime, The Assembly/Namespace/Type

http://www.academictutorials.com/microsoft.net/dotnet-aims-and-objectives.asp



Distinction, Exploring an Assembly Using ildasm.exe, Exploring an

Assembly Using Reflector, Deploying the .NET Runtime, The Platform-

Independent Nature of .NET

Building C# Applications

The Role of the .NET Framework 4.0 SDK, Building C# Applications using

csc.exe, Building .NET applications using Visual Studio 2010

Unit-2 9 Hrs

Core C# Programming Constructs

The Anatomy of a simple C# Program, An Interesting Aside: Some

Additional Members of the System.Environment Class, The System.Console

class, System Data Types & C# shorthand Notation, Working with String

Data, Narrowing & widening data type conversions, Understanding

implicitly typed local variables, C# iteration constructs, Decision constructs

& the relational/Equality operators, Methods & parameter modifiers,

Understanding C# arrays, Understanding the Enum type, Understanding

the Structure type, Understanding Value types & reference types,

Understanding C# Nullable types

Unit-3 10 Hrs

Defining encapsulated class types

Introducing the C# class type, understanding constructors, the role of the

this keyword, understanding the static keyword, C# access modifiers, The

first pillar: C#’s encapsulation services, understanding automatic

properties, understanding object initializer syntax, working with constant

field data, understanding partial types.

Inheritance

Inheritance Basics, Member Access and Inheritance, Using Protected

Access, Constructors and Inheritance, Calling Base Class Constructors,

Inheritance and Name Hiding, Using base to Access a Hidden Name,

Creating a Multilevel Hierarchy, When Are Constructors Called? Base Class

References and Derived Objects, Virtual Methods and Overriding, Why

Overridden Methods? Applying Virtual Methods, Using Abstract Classes,

Using sealed to Prevent Inheritance, The object Class, Boxing and

Unboxing, Is object a Universal Data Type?



Unit-4 11 Hrs

Exception Handling

The System.Exception Class, Exception-Handling Fundamentals, Using try

and catch, A Simple Exception Example, A Second Exception Example, The

Consequences of an Uncaught Exception, Exceptions Let You Handle

Errors Gracefully, Using Multiple catch Clauses, Catching All Exceptions,

Nesting try Blocks, Throwing an Exception, Rethrowing an Exception,

Using finally, A Closer Look at the Exception Class, Commonly Used

Exceptions, Deriving Exception Classes, Catching Derived Class

Exceptions, Using checked and unchecked,

Understanding Object Lifetime

Classes, Objects, & References, The basics of object lifetime, The role of

application roots, Understanding object generations, The System.GC type,

Building finalizable objects, Building disposable objects, Building

Finalizable & Disposable types

Interfaces

Interfaces, Implementing Interfaces, Using Interface References, Interface

Properties, Interface Indexers. Interfaces Can Be Inherited, Name Hiding

with Interface Inheritance, Explicit Implementations, Choosing Between an

Interface and an Abstract Class, The .NET Standard Interfaces,Building

Enumerable Types (IEnumerable & IEnumerator), Building cloneable

objects (ICloneable), Comparable objects (IComparable)

Unit-5 11 Hrs

Delegates, Events, & Lambda Expressions

Delegates, Delegate Method Group Conversion, Using Instance Methods as

Delegates, Multicasting, Covariance and Contravariance, System.Delegate,

Why Delegates? Anonymous Functions, Anonymous Methods, Pass

Arguments to an Anonymous Method, Return a Value from an Anonymous

Method, Use Outer Variables with Anonymous Methods, Lambda

Expressions, The Lambda Operator, Expression Lambdas, Statement

Lambdas, Events, A Multicast Event Example, Instance Methods vs. Static

Methods as Event Handlers.

Advanced C# Langauage Features

Understanding Indexer methods, Understanding Operator overloading,

Understanding Custom type conversions (up to The internal representation of

custom conversion routines)



Configuring .NET Assemblies

Defining custom Namespaces, The role of .NET assemblies, Understanding

the format of a .NET assembly, Building & consuming a single-file assembly,

Building & consuming a multifile assembly.

Text Books:

1. Andrew Troelsen: Pro C# 2010 and the .NET 4 Platform, Fifth Edition,

Apress, India, 2010. Chapters: 1 to 5, 8, 12, 14.

2. Herbert Schildt: The Complete Reference C# 4.0, TMH Edition 2010.

Chapters: 11, 12, 13, 15

Reference Books:

1. Ian Griffiths, Matthew Adams, and Jesse Liberty: Programming C# 4.0,

Sixth Edition, O’REILLY, 2010.

2. Andrew Stellman, Jennifer Greene: Head First C#, 2nd Edition,

O’REILLY 2010

5MCAE23: CLOUD COMPUTING

Contact Hours/ Week : 4 Credits : 4.0 Total Lecture Hours : 50 CIE Marks : 50 Total Tutorial Hours : 0 SEE Marks : 50 Sub. Code : 5MCA23

UNIT- I 10 Hrs

Defining Cloud Computing: Cloud Types, The NIST model, The Cloud

Cube Model, Deployment models, Service models, Examining the

Characteristics of Cloud Computing, Paradigm shift, Benefits of cloud

computing, Disadvantages of cloud computing; Assessing the value

proposition: Early adopters and new applications, the laws of

cloudonomics, cloud computing obstacles, behavioral factors relating to

cloud adoption, measuring cloud computing costs, specifying SLAs



UNIT- II 12 Hrs

Understanding Cloud Architecture: Exploring the Cloud Computing

Stack, Composability, Infrastructure, Platforms, Virtual Appliances,

Communication Protocols; Understanding Services and Applications by

Type: Defining IaaS, Defining PaaS, Defining SaaS, Defining IDaaS

UNIT- III 10 Hrs

Understanding Abstraction and Virtualization: Using Virtualization

Technologies, Load balancing and Virtualization, Understanding

Hypervisors; Capacity Planning: Defining Baseline and Metrics, Baseline

measurements, System metrics, Load testing, Resource ceilings, Server and

instance types, Network Capacity, Scaling

UNIT-IV 10 Hrs

Understanding Service Oriented Architecture: Introducing Service

Oriented Architecture, Event-driven SOA or SOA 2.0, The Enterprise

Service Bus, Service catalogs, Defining SOA Communications, Business

Process Execution Language, Business process modeling, Managing and

Monitoring SOA, SOA management tools , SOA security , The Open Cloud

Consortium, Relating SOA and Cloud Computing

UNIT-V 10 Hrs

Using Platforms: Defining Services, Salesforce.com versus Force.com:

SaaS versus PaaS, Application development , Exploring Google

Applications, Surveying the Google Application Portfolio, Understanding

Amazon Web Services, Amazon Web Service Components and Services,

Exploring Microsoft Cloud Services, Defining the Windows Azure Platform

Moving Applications to the Cloud : Applications in the Clouds ,

Functionality mapping, Application attributes, Cloud service attributes,

System abstraction, Cloud bursting, Applications and Cloud APIs



TEXT BOOK: 1. Barrie Sosinsky, “Cloud Computing Bible”, Wiley Publishing

Inc. 2011 .

REFERENCES: 1. David S. Linthicum, Cloud Computing and SOA Convergence in

Your Enterprise: A Step-by-Step Guide

2. Kai Hwang, Geoffrey C. Fox, and Jack J. Dongarra, “Distributed

and Cloud Computing – From Parallel Processing to the Internet of

Things”, Morgan Kaufman Publishers, 2012.

3. Gautam Shroff, Enterprise Cloud Computing Technology

Architecture Applications Toby Velte, Anthony Velte, Robert

Elsenpeter, Cloud Computing, A Practical Approach

V Semester Laboratory Program Details

5MCAL4: Data mining Lab

Credits: 2 SEE marks: 50 Lab Hours/week: 4 CIE marks: 50

1. Data Exploration and visualization with R 2. Regression with R 3. Classification with R 4. Data Clustering with R 5. Association Rule Mining with R



5MCAL2: Software Design Laboratory Credits: 1 SEE marks: 50 Lab Hours/week: 2 CIE marks: 50

Lab Programs

The student has to draw the necessary UML diagrams using any suitable UML Drawing Tool and implement in Java OR C++ OR C# a program to demonstrate the Design Pattern specified by the Examiner. The Design Pattern is allotted based on lots from the following list: 1) Expert 2) Controller 3) Publisher-Subscriber 4) Command 5) Forward-Receive 6) Client-Dispatcher 7) Proxy 8) Façade 9) Polymorphism

5MCAL3: Mini Project Credits: 2 SEE marks: 50 Lab Hours/week: 3 CIE marks: 50

Project Work for VI semester

6MCA01: MAJOR PROJECT

Sl. No Subject Code Title Credits

1. 6MCA01 Major Project 25

CIE 50 marks SEE 50 marks

a) Is spread over VI semester and evaluated at the end of VI semester

for the assigned credits.

Mini project which are oriented to topics not restricted to DBMS, Image processing, Wireless sensor network, data mining, data analytics is to be developed by each batch consisting of a maximum of two students.



b) The project may be based on;

Design of a system.

Theoretical/Analytical modeling.

Computer simulation.

Developing working software

Interdisciplinary computer application/modeling.

c) The project could be part of the research activity carried out in the

department.

d) The literature survey should be one of the components of the

project.

e) The project can be carried outside the institute in a recognized

industry/research lab.

f) All the project works should be approved by DAAC.

g) Director and DAAC assign guides for the major project.

h) The project is to be carried out by individual student.

CIE for the major project

Comprises of three seminars. Departmental Project Evluation Committee (DPEC) shall evaluate seminars along with the respective guides.

In the first seminar, students have to present about the area of the project, literature survey and preliminary requirements of the project and what they propose to do.

In the second seminar, the students have to present about the project development issues like, specifications, flow chart, design steps, data flow diagrams, data structures, entity relation ship diagrams pertaining to the chosen project.

In the third seminar, the students have to present a demo of the project.

CIE is done for a total of 100 marks, which shall be reduced to 50.

The breakup of marks for CIE is given in Table 1.

Table 1. Break up of CIE marks for major project



Seminar-1 20 marks

Seminar-2 40 marks

Seminar-3 40 marks

Total 100 marks

*Conducted in presence of external examiner

SEE for the major project

SEE is conducted by one external examiner and the respective guide. The breakup of marks is given in Table 2.

SEE is done for a total of 100 marks, which shall be reduced to 50.

Table 2. Break up of SEE marks for major project

Evaluation of the project report by external examiner and the guide (average of independent evaluations)

50 marks

Presentation, Demonstration and Quality of work, viva-voce

50 marks

Total 100 marks

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