Ktu s3 Mtech Cse Syllabus

Kerala Technological University
Master of Technology – Curriculum, Syllabus & Course Plan
SEMESTER 3
End Semester
Examination Slot
Course Number Examination
Internal Marks
Name L-T-P
Duration
Credits
(hours)
Marks
A Elective IV 3-0-0 40 60 3 3
B Elective V 3-0-0 40 60 3 3
T 01CS7191 Seminar II 0-0-2 100 2
W 01CS7193 Project (Phase 1) 0-0-12 50 6
TOTAL 6-0-14 230 120 - 14
TOTAL CONTACT HOURS : 20

TOTAL CREDITS : 14
Elective IV
01CS7151 Complexity Theory
01CS7153 Distributed Algorithms
01CS7155 Advanced Computer Graphics
01CS7157 Ad-hoc and Sensor Networks
Elective V
01CS7171 Principles of Network Security
01CS7173 Fuzzy Set Theory & Applications
01CS7175 Decision Support Systems
01CS7177 Advanced Software Project Management
Cluster: 1 Branch: Computer Science & Engineering Stream: Computer Science & Engineering
4
01CS6194 - Experiments
Experiment No
Description
XIV Varying the RTT experiment using NS3
XV Study of Software-defined networking (SDN)
SEMSTER 3
SYLLABUS & COURSE PLAN
65
66
Course No. Course Name L-T-P Credits Year of Introduction

01CS7151 Complexity Theory 3-0-0 3 2015
Course Objectives
1. To understand fundamental time and space related complexity classes.

2. To understand randomized computation and associated complexity classes.
3. To explore various NP complete problems.
4. To understand parallel computation and associated complexity classes.
5. To understand the importance of complexity theory in cryptography.
Syllabus
Review of time and space related complexity classes, class L, NL, Co-NL, NL completeness. NP
complete problems, NP and Co-NP, function problems, Randomized computation , RP, ZPP, PP,
BPP – branching program – random sources. Cryptography – randomized cryptography –
interactive proofs – zero-knowledge. Approximability – Approximation algorithms class
MAXSNP, MAXSNP completeness – non-approximability. Parallel computation, algorithms,
models of computation – class NC, P-completeness – RNC algorithms.
Expected Outcome
1. Ability to distinguish between various complexity classes.
2. Explain the significance of complexity classes and computation strategies.
References
1. Christos H. Papadimitriou, “Computational Complexity”, Addison-Wesley Publishing
Company Inc, 1994.
2. Michael Sipser, “Introduction to the Theory of Computation”, Thompson Course
Technology, 2/e, 2006.
3. Dexter C. Kozen, “Theory of Computation”, Springer, 2006.
4. Vazirani V., “Approximation Algorithms”, Springer, 1/e, 2004.
5. Rajeev Motwani, PrabhakarRaghavan, “Randomized Algorithms”, Cambridge University
Press, 2000.
6. JorgRothe, “Complexity Theory and Cryptology: An Introduction to Crypto-complexity”,
Springer-Verlag, 2005.
67
01CS7151 – COURSE PLAN
Hours Allotted
% of Marks in
End-Semester
Examination
Module
Contents
Review of time and space related complexity classes – hierarchy

I theorem – reachability method, Space complexity – class L, NL, Co-NL, 15
6
NL completeness.
NP complete problems – problems in NP – variants of satisfiability –
II graph theoretic problems – sets and numbers, NP and Co-NP – function 6 15
problems.
FIRST INTERNAL EXAM
Randomized computation – randomized algorithms – complexity
III 15
classes – RP, ZPP, PP, BPP – branching program – random sources. 8
Cryptography – one-way functions – trapdoor functions – cryptography

IV and complexity – randomized cryptography – interactive proofs – zero- 20
8
knowledge.
SECOND INTERNAL EXAM
Approximability – Approximation algorithms – Approximation and
V complexity – L-reductions – class MAXSNP, MAXSNP completeness – 15
6
non-approximability.
VI Parallel computation – parallel algorithms – parallel models of
8 20
computation – class NC, P-completeness – RNC algorithms.
END SEMESTER EXAM
68

01CS7153 Distributed Algorithms 3-0-0 3 2015
Course Objectives
1. Provide an introduction to the most important basic results in the area of distributed
algorithms.
2. Should be able to use basic distributed algorithms and impossibility results
3. Ability to apply distributed algorithms in large computer networks to multiprocessor
shared-memory systems.
Syllabus
Synchronous Network Algorithm: Network Model, Leader election, , Algorithms in General

Synchronous Networks, Distributed consensus with link failures, Distributed consensus with
process failures, Asynchronous Algorithms: System model, Properties and proof
methods.Asynchronous Shared Memory Algorithms: Shared Memory Model, Mutual Exclusion,
Resource allocation, Consensus. Asynchronous Network Algorithms: Network Model, Basic
asynchronous network algorithms, Synchronizers, Applications. Partially Synchronous Algorithms:
System model, Timed automata, Basic Definitions and operations
Expected Outcome
 Ability to discuss and apply various synchronous algorithms and consensus problems.
 Ability to discuss and apply various asynchronous shared memory algorithms and
asynchronous network algorithms.
 Ability to discuss and apply partially synchronous algorithms.
References
1. Nancy Lynch, “Distributed Algorithms”, Morgan Kaufmann, 1996.
2. Vijay K. Garg, “Elements of Distributed Computing”, John Wiley, 2006.
3. S. Mullender, “Distributed Systems”, Addison-Wesley, 1993.
4. Gerard Tel, “Introduction to Distributed Algorithms”, Cambridge Univ. Press, 2000.
69
01CS7153 - COURSE PLAN
Hours Allotted
% of Marks in
End-Semester
Examination
Module
Contents
Synchronous Network Algorithm: Synchronous Network Model,

I Leader election in a synchronous ring, Algorithms in General
7 15
Synchronous Networks – Flooding algorithm – Breadth First Search –
Shortest Paths – Minimum Spanning Tree – Maximal Independent Set.
Distributed consensus with link failures – Deterministic coordinated
attack problem, Distributed consensus with process failures – Algorithm
for Byzantine failure.
II Asynchronous Algorithms: Asynchronous System model – I/O 7 15
automata – Operations on automata – Fairness – Inputs and outputs for
problems – Properties and proof methods.
FIRST INTERNAL EXAM
Asynchronous Shared Memory Algorithms: Asynchronous Shared
III Memory Model, Mutual Exclusion – Dijkstra’s Mutual Exclusion
7 15
algorithm – Lock out free Mutual Exclusion algorithms, Mutual
Exclusion using Read – Modify – Write Variables – TicketME algorithm.
Resource allocation – The problem – Nonexistence of Symmetric Dining
IV Philosophers Algorithm – Left Dining Philosophers Algorithm,
7 15
Drinking Philosophers Problem, Consensus – Agreement using
Read/Write shared memory.
Asynchronous Network Algorithms: Asynchronous Network Model,
Basic asynchronous network algorithms – Leader election – Spanning
V Tree construction – BFS – Shortest path –Minimum Spanning Tree, 20
7
Synchronizers – The Local synchronizer – The safe synchronizer –
Implementations – Applications.
Partially Synchronous Algorithms: System model – MMT Timed
automata – General Timed automata – Basic Definitions and operations
VI – Transforming MMT automata into General Timed Automata, Mutual 20
7
Exclusion with partial synchrony – The problem – Single-Register
algorithm.
END SEMESTER EXAM
70

01CS7155 Advanced Computer Graphics 3-0-0 3 2015
Course Objectives
1. To introduce geometric modeling and modeling transformations

2. To learn different techniques for representing Solids
3. To learn visible surface determination algorithms
4. To learn concepts of global illumination modeling using advanced Ray tracing algorithms
and Radiosity methods
Syllabus
Geometric modelling :Hierarchy in Geometric models, Defining and Displaying structures,

Modelling Transformations, Interaction, Optimizing display of hierarchical models, Limitations of
SPHIGS. User Interface Software, User Interface Management systems, Solid Modelling, Visible
surface determination algorithms, Image manipulation and storage, Advanced geometric and
raster transforms, Animation: Conventional and computer assisted animation, Methods of
controlling animation, Multiprocessor Graphics System.
Expected Outcome
1. Be able to apply appropriate mathematical models to solve computer graphics problems
References
1. James D. Foley, Andries van Dam, Steven K. Feiner and F. Hughes John, “Computer
Graphics, principles and Practice in C”, 2/e, Pearson Education.
2. Donald Hearn and M. Pauline Baker, “ Computer Graphics”, Prentice Hall India
3. Alan Watt , “ 3D Computer Graphics”, Addison Wesley
71
Hours Allotted
% of Marks in
End-Semester
Examination
Module
Contents
Geometric modelling :Hierarchy in Geometric models, relationship

between model, application program and Graphical System, Defining
I and Displaying structures, Modelling Transformations, Hierarchical 8 15
structure networks, Appearance attribute handling in hierarchy, Screen
updating and rendering modes,
Interaction, Output features, Implementation issues, Optimizing display
of hierarchical models, Limitations of SPHIGS. User Interface Software:
II Basic interaction handling models, Window management systems,
7 15
Output handling in window systems, Input handling in window
systems, User Interface Management systems.
FIRST INTERNAL EXAM
Solid Modelling: Regularized Boolean set of operations, Sweep
representations, Boundary representations, Winged –Edged
III representations, Boolean Set Operations, Spatial Partitioning 7 15
representations, Octrees, Constructive Solid Geometry, Comparisons of
representations.
Visible surface determination algorithms: Scan line algorithm, Area
subdivision algorithm, visible surface ray tracing. Illumination and
IV shading: Illumination models, diffuse reflection and Specular reflection,
8 20
illumination models, Shading models for polygons. Global illumination
algorithms. Recursive ray tracing and distributed ray tracing. Radiosity
methods, Combining radiosity and ray tracing.
Image manipulation and storage : Geometric transformation of images,
Filtering, Multipass transforms, Generation of transformed image with
V filtering, Image Compositing, Mechanism for image storage. Advanced 7 20
geometric and raster transforms: Clipping- clipping polygon against
rectangles and other polygons.
Animation: Conventional and computer assisted animation, Methods of
VI controlling animation. Advanced Raster graphics architecture. Display
5 15
processor system, Standard graphics pipeline, Multiprocessor Graphics
System.
END SEMESTER EXAM
72
01CS7157 Adhoc and Sensor Networks 300 3 2015
Course Objectives
1. To introduce wireless sensor networks and learn the concepts and principles behind WSN
2. To learn WSN network design, sensor node embedded system design and implementation
3. To understand issues involved in wireless network security
Syllabus
Fundamentals of wireless communication, characteristics of wireless channels, multiple access
techniques, wireless LANs, PANs, WANs, and MANs, Wireless Internet. Introduction to
adhoc/sensor networks, advantages of adhoc/sensor network, issues in adhoc wireless networks,
sensor network architecture, data dissemination and gathering.
MAC Protocols, issues, design goals, classification, SMAC. Routing Protocols : Issues,
classification, QoS and Energy Management, Issues and, classifications, QoS frameworks, need for
energy management, classification, Security in Adhoc wireless Networks.
Expected Outcome
1. The student is familiar with the main standards and specifications of WSNs and identifies
the key building blocks for them.
2. The student can define and explain the essential challenges of resourceconstrained WSN
design and implementation, including applications, interfaces, energyefficient protocols and
platform functionalities.
3. The student can apply both theoretical and practical tools for WSN design and utilization
and design potential application scenarios for WSNs.
References
1. C. Siva Ram Murthy, B. S. Manoj, "AdHoc Wireless Networks ", Pearson Education, 2008.
2. Feng Zhao, LeonidesGuibas, "Wireless Sensor Networks ", Elsevier, 2004.
3. Jochen Schiller, "Mobile Communications ", 2/e, Pearson Education, 2003.
4. William Stallings, "Wireless Communications and Networks ", Pearson Education, 2004.
% of Marks in
Hours Allotted
EndSemester
Examination
Module
Contents
I Introduction: Fundamentals of wireless communication technology, the 15
electromagnetic spectrum, radio propagation mechanisms, 3
characteristics of wireless channels.
Multiple access techniques, Wireless LANsFundamentals of WLANS, 6
73
IEEE 802.11 Standard, PANsBluetooth, WANs cellular concept,

cellular architecture and MANsIEEE 802.16 Standard, Wireless
Internet Introduction, Mobile IP.
Introduction to adhoc/sensor networks: Key definitions of adhoc/
sensor networks, unique constraints and challenges, advantages of
II adhoc/sensor network, driving applications, issues in adhoc wireless
5 15
networks, issues in design of sensor network, sensor network
architecture, data dissemination and gathering.
FIRST INTERNAL EXAM
MAC Protocols: Issues in designing MAC protocols for adhoc wireless
III networks, design goals, classification of MAC protocols. 4 15
MAC protocols for sensor network, location discovery, SMAC. 4
Routing Protocols: Issues in designing a routing protocol. 2
IV Classification of routing protocols, Destination Sequenced Distance 15
Vector routing protocol, Dynamic Source Routing Protocol. 4
QoS: Concept, Issues and challenges in providing QoS,
4
V QoS –Classifications. 20
MAC layer solutions, QoS frameworks for Adhoc Wireless networks
5
QoS Models ,INSIGNIA , INORA .
Energy Management need for energy management, classification. 2
VI Security in Adhoc wireless networksNetwork security Requirements, 20
Issues and challenges in security provisioning, Network Security 3
Attacks.
END SEMESTER EXAM
74

01CS7171 Principles of Network Security 3-1-0 4 2015
Course Objectives
1. To impart understanding of the main issues related to security in modern networked

computer systems
2. The student should gain extensive, detailed and critical understanding of the concepts,
issues, principles and theories of computer network security
Syllabus
Cryptographic Algorithms, DES, RSA, Hash function, Secure Hash Algorithm (SHA), Digital
Signature schemes, Key Management, distribution and authentication, Wireless Security, Wireless
LAN IEEE 802.11i, WAP, Security in Application layer, Transport layer and Network layer,
Intrusion detection and firewalls.
Expected Outcome
3. Students should attain the ability to identify security vulnerabilities in a networked
systems
4. Students should attain the ability apply network security algorithms and principles at
different layers in typical networked environment
References
1. William Stallings, “Cryptography and Network Security Principles and Practice”, 5/e,
Pearson Education Asia, 2011.
2. Behrous A. Forouzan, “Cryptography and Network Security”, TMH, 2007.
3. William Stallings, “Network Security Essentials”, 4e, Pearson Education, 2011.
4. Roberta Bragg et. al., “Network Security: The Complete Reference”, TMH, 2008.
75
Hours Allotted
% of Marks in
End-Semester
Examination
Module
Contents
DES, Strength of DES, Principles of public key crypto systems, The RSA
algorithm, Cryptographic Hash functions- Applications, Requirements,
4
I Secure Hash Algorithm (SHA ) 15
Digital signatures- Elgamal Digital Signature Scheme, Schnorr Digital

4
Signature Scheme, Digital Signature Standard.
Wireless LAN protocol architecture, Wireless LAN security,
2
II IEEE 802.11i Phases of operation- Discovery, Authentication, Key
15
management, Protected data transfer. Wireless Application Protocol 3
(WAP).
FIRST INTERNAL EXAM
IP Security, Modes of operation, Protocols -Authentication Header
(AH), Encapsulating Security Payload(ESP), Security Associations, 3
III Security policy, 15
Internet Key Exchange – Diffie-Hellman key exchange, Attacks, IKE
3
phases- Main mode, Aggressive and Quick mode
Email Architecture, Security, PGP-authentication, confidentiality, PGP
Certificates and public keys, Trust model in PGP, Key Revocation, PGP
4
packets, S/MIME- MIME, S/MIME data content types
IV 15
Secure Socket Layer, SSL Architecture, key exchange algorithms ,
Sessions and connections, Protocols –Handshake protocol, Change
4
cipherSpec protocol, Record protocol, Alert protocol, Transport layer
security, HTTPS, SSH
Symmetric Key Agreement- Diffie-Hellman Key exchange, Station to

Station Key exchange, Distribution of public keys, X.509 certificates,
4
Public Key Infrastructure, Remote user authentication, Remote user
V authentication using symmetric key encryption 20
Kerberos- version 4 message exchanges, improvements in version 5,
Zero Knowledge Protocols – Fiat-Shamir protocol, Feige-Fiat Shamir 3
Protocol.
VI Statistical anomaly detection, Rule based Intrusion detection, 4 20
76
Hours Allotted
% of Marks in
End-Semester
Examination
Module
Contents
distributed intrusion detection, Password Management- password

protection, password selection strategies
Malicious software- types, virus, worms, distributed denial of service,

Firewalls -types of firewalls 4
END SEMESTER EXAM
77

Fuzzy Set Theory&
01CS7173 3-0-0 3 2015
Applications
Course Objectives
1. To understand Fuzzy Set Theory and the basis of fuzyy logic and fuzzy logic applications
such as fuzzy control and fuzzy decision making
Syllabus
Introduction – crisp sets an overview – the notion of fuzzy sets – Basic concepts of fuzzy sets –
classical logic an overview – Fuzzy logic. Operations on fuzzy sets - fuzzy complement – fuzzy
union – fuzzy intersection – combinations of operations – general aggregation operations. Crisp
and fuzzy relations – binary relations – binary relations on a single set–equivalence and similarity
relations. Compatibility or tolerance relations– orderings – Membership functions – methods of
generation – defuzzification methods. General discussion – belief and plausibility measures –
probability measures– possibility and necessity measures – relationship among classes of fuzzy
measures. Classical logic: An overview – fuzzy logic – fuzzy rule based systems – fuzzy decision
making Fuzzy logic in database and information systems – Fuzzy pattern recognition – Fuzzy
contriol systems.
Expected Outcome
The students who succeeded in this course should be
1. able to examine the Set Theory problems.

2. able to interpret the systems which include fuzzines within the scope of fuzzy set theory.
3. able to combine the information of decision theory and the information of fuzzy set theory.
4. able to improve the proof techniques of Fuzzy Set Theory.
5. able to solve problems that include uncertainty with using Fuzzy Set Theory.
References
1. George J Klir and Tina A Folger, “Fuzzy Sets, Uncertainty and Information”, Prentice Hall
of India, 1998.
2. H.J. Zimmerman, “Fuzzy Set Theory and its Applications”, 4/e, Kluwer Academic
Publishers, 2001.
3. George Klir and Bo Yuan, “Fuzzy Sets and Fuzzy Logic: Theory and Applications”, Prentice
Hall of India, 1997.
4. Timothy J Ross, “Fuzzy Logic with Engineering Applications”, McGraw Hill International
Editions, 1997.
5. Hung Nguyen and Elbert Walker, “A First Course in Fuzzy Logic, 2/e,, Chapman and
Hall/CRC, 1999.
78
6. Jerry M Mendel, “Uncertain Rule-based Fuzzy Logic Systems: Introduction and New
Directions, PH PTR, 2000.
7. John Yen and Reza Lengari, “Fuzzy Logic: Intelligence, Control and Information”, Pearson
Education, 1999.
79
Hours Allotted
% of Marks in
End-Semester
Examination
Module
Contents
Introduction – crisp sets an overview – the notion of fuzzy sets – Basic

concepts of fuzzy sets – classical logic an overview – Fuzzy logic.
I Operations on fuzzy sets - fuzzy complement – fuzzy union – fuzzy
8 15
intersection – combinations of operations – general aggregation
operations
Crisp and fuzzy relations – binary relations – binary relations on a

II single set–equivalence and similarity relations. 7 15
FIRST INTERNAL EXAM

Compatibility or tolerance relations– orderings – Membership functions
III
– methods of generation – defuzzification methods. 7 15
General discussion – belief and plausibility measures – probability

IV measures– possibility and necessity measures – relationship among
8 20
classes of fuzzy measures.

Classical logic: An overview – fuzzy logic – fuzzy rule based systems –
V
fuzzy decision making 7 20
Fuzzy logic in database and information systems – Fuzzy pattern

VI
recognition – Fuzzy control systems. 5 15
END SEMESTER EXAM
80

01CS7175 Decision Support Systems 3-0-0 3 2015
Course Objectives
1. To understand the theory and applications of various types of DSS
Syllabus
Introduction, Concepts of Data, Information, Information Systems & End Users. Systems Concepts,
Building Information System, Prototyping Evolution of Information Systems, Decision Making,
Characteristics and Capabilities. Components of DSS, Certainty, Uncertainty, and Risk, Sensitivity
Analysis, Making Decisions in Groups, Group Decision Support System(GDSS), Supporting Group
work with Computerized Systems, Knowledge Management System, Introduction to Business
Intelligence: Origins and Drivers of Business Intelligence, General Process of Intelligence Creation
and Use, Characteristics of Business Intelligence, Towards Competitive Intelligence, Successful BI
Implementation, Structure and Components of BI ,Future trends.Data Warehousing Definitions
and Concepts, Analytical Processing (OLAP). Knowledge Discovery in Databases (KDD, Data
Mining Concepts and Applications
Expected Outcome
1. The student should have conceptual strength in DSS and should be able apply it identify the
most apt DSS in a practical scenario.
References
1. Turban, Efrain, “Decision Support & Business Intelligent Systems”, 8/e, Pearson Education
2. Marakas, George.M, “Decision Support Systems in the 21st Century”, Pearson Education
3. Mallach, Efrem G., “ Decision Support & Data Warehouse Systems”, Tata McGraw-Hill
4. Keen,Peter G.W, “Decision Support System and Organizational Perspective”, Addison-
Wesley
5. Theierauff, Robert J., “Decision Support System for Effective Planning”, Prentice Hall, 1982.
6. Krober,Donald W., and Hugh J. Watson, “Computer Based Information System”, New
York,1984.
7. Andrew P. Sage, “Decision Support System Engineering”, John Wiley & Sons, New
York,1991.
8. Leod. Raymond Me JR, “Management Information Systems”, 5/e, Macmillian Publishing
Company, 1993.
81
Hours Allotted
% of Marks in
End-Semester
Examination
Module
Contents
Introduction, Concepts of Data, Information, Information Systems &

End Users. Systems Concepts: Open System, Closed System;
Information Systems and Systems Concept. Building Information
I 15
System: System Analysis and Design – Systems Development Cycle 7
(Identification of Requirements, Feasibility Study, System Analysis,
Design And Implementation), Prototyping Evolution of Information
Systems: PS,OAS,MIS,DSS,EIS,ES
Decision Making: Introduction and Definitions, Simons Decision
Making Model, How Decisions are Supported, DSS Configurations, DSS
II Characteristics and Capabilities. Components of DSS, DSS 7 15
Classifications DSS Modeling-Static and Dynamic Models, Certainty,
Uncertainty, and Risk, Sensitivity Analysis, What-IF, and Goal Seeking
FIRST INTERNAL EXAM
Making Decisions in Groups: Group Decision Support
System(GDSS),Characteristics, Process, Benefits, and Dysfunctions,
Supporting Group work with Computerized Systems, Tools for Indirect
III 20
and Indirect Support of DecisionMaking, From GDSS to GSS 8
Knowledge Management System: Definition and types of Knowledge,
Frame work for Knowledge Management Knowledge Representation
Techniques: Rules, Frames, Semantic Networks
Introduction to Business Intelligence: Origins and Drivers of Business
Intelligence, General Process of Intelligence Creation and Use,
IV 15
Characteristics of Business Intelligence, Towards Competitive 7
Intelligence, Successful BI Implementation, Structure and Components
of BI, Future trends.
Data Warehousing Definitions and Concepts, Types of Data warehouse.
V 15
Business Analytics-Online Analytical Processing (OLAP), Reporting and 6
Queries, Multidimensionality.
Knowledge Discovery in Databases (KDD), framework of KDD. Data
VI 20
Mining Concepts and Applications, Framework of data mining, Text 7
Mining, Web Mining Usage, Benefits, and Success of Business Analytics.
END SEMESTER EXAM
82

Advanced Software Project
01CS7177 3-0-0 3 2015
Management
Course Objectives
1. To impart comprehensive knowledge of software project management

2. To familiarise with the planning and implementing of complex software projects.
Syllabus
Planning a software project; Project evaluation; Selection of Process model; Software effort
estimation; Activity planning; Risk analysis and risk management; Resource allocation; Project
tracking and control; Contract management; People management; Software quality assurance;
Configuration management.
Expected Outcome
1. Ability to explain and exemplify to the different stages of planning a software project and
managing it.
2. Capability to plan a large software project, and to effectively monitor and control it.
References
5. Bob Hughes and Mike Cotterell, “Software Project Management”, 5/e, 2011,McGraw Hill
6. PankajJalote, “Software Project Management in Practice”, 2002, Pearson Education Asia.
7. Roger S. Pressman, “Software Engineering: A practitioner’s Approach”, 7/e, 2010,
McGraw Hill
8. Robert T. Futrell, Donald F. Shafer, and Linda I. Shafer, “Quality Software Project
Management”, 2002, Pearson Education Asia.
9. Ramesh Gopalaswamy, “Managing Global Software Projects”, 2003, Tata McGraw Hill.
83
Hours Allotted
% of Marks in
End-Semester
Examination
Module
Contents
Introduction to Software Project Management: Stakeholders; Software

product, process, resources, quality, and cost;Objectives, issues, and 3
I problems relating to software projects. 15
Project Planning: Defining scope and objectives; Work
3
breakdownstructure; Time, cost, and resource estimation. Case studies.
Project Evaluation: Strategic assessment; Technical assessment; Cost
benefit analysis; Risk evaluation. Choice of process model: Rapid
II
application development; Waterfallmodel; V-process model; Spiral 5 15
model; Prototyping; Incremental delivery, Agile methods. Case studies.
FIRST INTERNAL EXAM
Software Effort Estimation: Effort estimation techniques; Algorithmic
4
III methods; Function point analysis; COCOMO model. Case studies. 15
Activity Planning: Network planning model; Critical path; Slack and
3
float.
Risk Analysis and Management: Risk Identification; Risk assessment;
4
Risk mitigation, monitoring, and management.
IV Resource Allocation: project resources; Allocating and scheduling 15
resources; cost of resources; Cost variance; time-cost tradeoff. Case 4
studies.
Project Tracking and Control: Measurement of physical and financial
4
progress; Status reports; Change control.
Contract Management: Outsourcing; Types of contracts; Stages and
V Terms of contract; Contract monitoring; Managing People and 20
Organizing Teams: Recruitment; Motivation; Group behaviour; 6
LeadershipMini and leadership styles; forms of organizational
structures.
Software Quality Assurance: Planning for quality; Product versus
process quality; Defect analysis and prevention; Statistical process
4
VI control; Pareto analysis; Causal analysis; Quality standards and Models;
20
Quality audit.
Configuration Management: CM Process; Change control;
2
Configuration audit; Status reporting.
END SEMESTER EXAM
84

01CS7191 Seminar II 0-0-2 1 2015
Course Objectives
To make students
1. Identify the current topics in the specific stream.
2. Collect the recent publications related to the identified topics.
3. Do a detailed study of a selected topic based on current journals, published papers and
books.
4. Present a seminar on the selected topic on which a detailed study has been done.
5. Improve the writing and presentation skills.
Approach
Students shall make a presentation for 20-25 minutes based on the detailed study of the
topic and submit a report based on the study.
Expected Outcome
Upon successful completion of the seminar, the student should be able to

1. Get good exposure in the current topics in the specific stream.
2. Improve the writing and presentation skills.
3. Explore domains of interest so as to pursue the course project.
85

01CS7193 Project (Phase I) 0-0-12 6 2015
Course Objectives
To make students
1. Do an original and independent study on the area of specialization.

2. Explore in depth a subject of his/her own choice.
3. Start the preliminary background studies towards the project by conducting
literature survey in the relevant field.
4. Broadly identify the area of the project work, familiarize with the tools required for
the design and analysis of the project.
5. Plan the experimental platform, if any, required for project work.
Approach
The student has to present two seminars and submit an interim Project report. The first
seminar would highlight the topic, objectives, methodology and expected results. The first
seminar shall be conducted in the first half of this semester. The second seminar is the
presentation of the interim project report of the work completed and scope of the work
which has to be accomplished in the fourth semester.
Expected Outcome
Upon successful completion of the project phase 1, the student should be able to
1. Identify the topic, objectives and methodology to carry out the project.
2. Finalize the project plan for their course project.
86

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Kerala Technological University

Master of Technology – Curriculum, Syllabus & Course Plan

Course Number Examination

TOTAL CONTACT HOURS : 20

XIV Varying the RTT experiment using NS3

XV Study of Software-defined networking (SDN)

Course No. Course Name L-T-P Credits Year of Introduction

1. To understand fundamental time and space related complexity classes.

01CS7151 – COURSE PLAN

Review of time and space related complexity classes – hierarchy

Cryptography – one-way functions – trapdoor functions – cryptography

Course No. Course Name L-T-P Credits Year of Introduction

Synchronous Network Algorithm: Network Model, Leader election, , Algorithms in General

01CS7153 - COURSE PLAN

Synchronous Network Algorithm: Synchronous Network Model,

Course No. Course Name L-T-P Credits Year of Introduction

1. To introduce geometric modeling and modeling transformations

Geometric modelling :Hierarchy in Geometric models, Defining and Displaying structures,

01CS7155 – COURSE PLAN

Geometric modelling :Hierarchy in Geometric models, relationship

01CS7157 Ad­hoc and Sensor Networks 3­0­0 3 2015

IEEE 802.11 Standard, PANs­Bluetooth, WANs­ cellular concept,

Course No. Course Name L-T-P Credits Year of Introduction

1. To impart understanding of the main issues related to security in modern networked

01CS7171 – COURSE PLAN

Digital signatures- Elgamal Digital Signature Scheme, Schnorr Digital

Symmetric Key Agreement- Diffie-Hellman Key exchange, Station to

01CS7171 – COURSE PLAN

distributed intrusion detection, Password Management- password

Malicious software- types, virus, worms, distributed denial of service,

END SEMESTER EXAM

Course No. Course Name L-T-P Credits Year of Introduction

1. able to examine the Set Theory problems.

01CS7173 – COURSE PLAN

Introduction – crisp sets an overview – the notion of fuzzy sets – Basic

Crisp and fuzzy relations – binary relations – binary relations on a

FIRST INTERNAL EXAM

General discussion – belief and plausibility measures – probability

SECOND INTERNAL EXAM

Fuzzy logic in database and information systems – Fuzzy pattern

END SEMESTER EXAM

Course No. Course Name L-T-P Credits Year of Introduction

1. To understand the theory and applications of various types of DSS

01CS7175 – COURSE PLAN

Introduction, Concepts of Data, Information, Information Systems &

Course No. Course Name L-T-P Credits Year of Introduction

1. To impart comprehensive knowledge of software project management

01CS7177 – COURSE PLAN

Introduction to Software Project Management: Stakeholders; Software

Course No. Course Name L-T-P Credits Year of Introduction

Upon successful completion of the seminar, the student should be able to

Course No. Course Name L-T-P Credits Year of Introduction

1. Do an original and independent study on the area of specialization.

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