MEWAR UNIVERSITY, CHITTORGARH (RAJ.)

Faculty of Engineering & Technology SYLLABI OF M.TECH. ( Computer Engineering ) SUBJECTS

Semester I

S. No. Code Subject L T P Credit

1 CS 611 Foundation of Computer Science 3 1 0 4

2 CS 612 Algorithem Design and Analysis 3 1 0 4

3 CS 613 Wireless and Mobile Communications 3 1 0 4

4 Open Elective I 3 1 0 4

5 Elective I 3 1 0 4

6 CS 651 Computer Lab-I 0 0 4 2

Total 22

Semester II

S. No. Code Subject L T P Credit

1 CS 621 Internet Protocols 1 0 4

1 0 4

1 0 4

1 0 4

1 0 4

0 4 2

Total 22

Semester III

S. No. Code Subject L T P Credit

1 CS 632 High Performance computer Architective 3 1 0 4

2 Open Elective II 3 1 0 4

3 CS 662 Seminar 0 0 2 6

4 CS 671 Minor Project 0 0 4 8

Total 22

Semester IV

S. No. Code Subject L T P Credit

1 CS 681 Dissertation work 0 0 4 22

Total 22

3 CS 623 Real Time Operating Systems 3

2 CS 622 Parallel and Distributed Algorithems 3

4 Elective II 3

5 Elective III 3

6 CS 661 Computer Lab-II 0

3

MEWAR UNIVERSITY, CHITTORGARH (RAJ.)

CS 611 Foundations of Computing Science L-T-P: 3-1-0, Credit: 4

Discrete Structures -- Sets, Relations and Functions; Proof Techniques, Algebraic

Structures, Morphisms, Posets, Lattices and Boolean Algebras.

Logic -- Propositional calculus and Predicate Calculus, Satisfiabiliy and validity,

Notions of soundness and completeness

Languages & Automata Theory -- Chomsky Hierarchy of Grammars and the

corresponding acceptors, Turing Machines, Recursive and Recursively Enumerable

Languages; Operations on Languages, closures with respect to the operations.

Computability -- Church-Turing Thesis, Decision Problems, Decidability and

Undecidability, Halting Problem of Turing Machines; Problem reduction (Turing and

mapping reduction).

Computational Complexity -- Time Complexity -- Measuring Complexity, The class

P, The class NP, NP-Completeness, Reduction, co-NP, Polynomial Hierarchy. Space

Complexity -- Savich's Theorem, The class PSPACE.

CS 612 Algorithm Design and Analysis L-T-P: 3-1-0, Credit: 4

Algorithmic paradigms: Dynamic Programming, Greedy, Branch-and-bound;

Asymptotic complexity, Amortized analysis; Graph Algorithms: Shortest paths, Flow

networks; NP-completeness; Approximation algorithms; Randomized algorithms;

Linear programming; Special topics: Geometric algorithms (range searching, convex

hulls, segment intersections, closest pairs), Numerical algorithms (integer, matrix and

polynomial multiplication, FFT, extended Euclid's algorithm, modular exponentiation,

primality testing, cryptographic computations), Internet algorithms (text pattern

matching, tries, information retrieval, data compression, Web caching).

CS 613 Wireless and Mobile Communications L-T-P: 3-1-0, Credit: 4

Introduction to mobile communication. Cellular mobile telephone architecture

overview.

Cellular radio system design-- Frequency assignments, frequency reuse channels.

Concept of cell splitting. Handover in cellular systems. Handoff algorithms.

Multiple access schemes in mobile communications--TDMA, FDMA, CDMA. Random

Multiple Access Schemes. Performance analysis issues. MAC layer scheduling and

connection admission in mobile communication. Interference suppression and Power

control. Teletraffic modelling and Queeuing theoretic analysis of cellular mobile

networks. Resource allocation and mobility management.Practical Cellular mobile

systems-- AMPS and GSM system architecture overview. Call management and system

operation. CDMA based cellular system. Wireless in Local Loop--DECT and CDMA WLL.

CS 621 Internet Protocols L-T-P: 3-1-0, Credit: 4

Overview Of Essentials : Physical Connectivity ,Protocols And Addressing , The OSI

Seven Layer Model, An Architecture For The Network , Packaging Data, Data Link

Protocols; The Internet Protocol : Choosing To Use IP, IPv4, IPv4 Addressing, IP In

Use, IP Options And Advanced Functions, Internet Control Message Protocol (ICMP);

Multicast: Choosing Unicast Or Multicast, Multicast Addressing And Forwarding,

Internet Group Management Protocol (IGMP); IP Version Six : IPv6 Addresses, Packet

Formats, Options, Choosing Between IPv4 And IPv6; Routing: Routing And

Forwarding, Distributing Routing Information, Computing Paths, Routing Information

Protocol (RIP), Open Shortest Path First (OSPF), IS-IS, Choosing Between IS-IS And

OSPF, Border Gateway Protocol 4 (BGP-4), Multicast Routing, Other Routing

Protocols; IP Service Management: Choosing How To Manage Services,

Differentiated Services, Integrated Services , Reserving Resources Using RSVP;

Transport Over IP: What Is A Transport Protocol , User Datagram Protocol

(UDP),Transmission Control Protocol (TCP) ,Stream Control Transmission Protocol

(SCTP), The Real-Time Transport Protocol (RTP), Multiprotocol Label Switching :

Label Switching, MPLS Fundamentals, Signaling Protocols, Label Distribution Protocol

(LDP) , Traffic Engineering In MPLS, CR-LDP, RSVP-TE, Choosing Between CR-

LDP And RSVP-TE, Prioritizing Traffic In MPLS, BGP-4 AND MPLS; Application

Protocols: What Is An Application, Choosing A Transport, Domain Name System,

Telnet, File Transfer Protocol, Hyper-Text Transfer Protocol, Choosing An Application

Protocol; Concepts In IP Security: The Need For Security, Choosing Where To Apply

Security, Components Of Security Models, Transport Layer Security, Securing The

Hypertext Transfer Protocol, Hashing And Encryption: Algorithms And Keys,

Exchanging Keys, Internet Key Exchange; Advanced Applications :IP Encapsulation,

Virtual Private Networks (VPN), Mobile IP, Header Compression, Voice Over IP, IP

Telephony, IP And ATM, IP Over Dial-Up Links.

CS 622 Parallel and Distributed Algorithms L-T-P: 3-1-0, Credit: 4

Fundamentals: Models of parallel and distributed computation, complexity measures;

The PRAM Model: balancing, divide and conquer, parallel prefix computation, pointer jumping, symmetry breaking, list ranking, sorting and searching, graph

algorithms, parallel complexity and complexity classes, lower bounds;

Interconnection Networks: topologies (arrays and mesh networks, trees, systolic

networks, hypercubes, butterfly) and fundamental algorithms, matrix algorithms,

sorting, graph algorithms, routing, relationship with PRAM models; Asynchronous

Parallel Computation; Distributed Algorithms: models and complexity measures,

safety, liveness, termination, logical time and event ordering, global state and

snapshot algorithms, mutual exclusion, clock synchronization, election, termination

detection, routing, Distributed graph algorithms; Applications of Distributed

algorithms.

CS 623 Real Time Operating Systems L-T-P: 3-1-0, Credit: 4

Basic Real-Time Concepts: Terminology, Real-Time System Design Issues, Example Real-

Time Systems, Brief History

Real-Time Operating Systems: Real-Time Kernels, Theoretical Foundations of Real-Time

Operating Systems, Intertask Communication and Synchronization, Memory

Management

Software Requirements Engineering: Requirements-Engineering process, Types of

Requirements, Requirements Specification for Real-Time Systems, Formal Methods in

Software Specification, Structured Analysis and Design, Object-Oriented Analysis and the

Unified Modeling Language, Organizing the Requirements Document , Organizing and

Writing Requirements, Requirements Validation and Review

Software System Design: Properties of Software, Basic Software Engineering Principles,

the Design Activity, Procedural-Oriented Design, Object-Oriented Design, Brief Survey of

Languages

Performance Analysis and Optimization: Theoretical Preliminaries, Performance Analysis,

Application of Queuing Theory, I/O Performance, Performance Optimization, Results

from Compiler Optimization, Analysis of Memory Requirements, Reducing Memory

Utilization

Engineering Considerations: Metrics, Faults, Failures and Bugs, Fault-Tolerance, Systems

Integration, Refactoring Real-Time Code, Cost Estimation Using COCOMO

CS 632 High Performance Computer Architecture L-T-P: 3-1-0, Credit: 4

Introduction: review of basic computer architecture, quantitative techniques in

computer design, measuring and reporting performance. CISC and RISC processors.

Pipelining: Basic concepts, instruction and arithmetic pipeline, data hazards, control

hazards, and structural hazards, techniques for handling hazards. Exception handling.

Pipeline optimization techniques. Compiler techniques for improving performance.

Hierarchical memory technology: Inclusion, Coherence and locality properties; Cache

memory organizations, Techniques for reducing cache misses; Virtual memory

organization, mapping and management techniques, memory replacement policies.

Instruction-level parallelism: basic concepts, techniques for increasing ILP,

superscalar, superpipelined and VLIW processor architectures. Array and vector

processors. Multiprocessor architecture: taxonomy of parallel architectures.

Centralized shared-memory architecture: synchronization, memory consistency,

interconnection networks. Distributed shared-memory architecture. Cluster

computers. Non von Neumann architectures: data flow computers, reduction

computer architectures, systolic architectures.

Electives

CS 001 Computational Geometry L-T-P: 3-1-0, Credit: 4

Convex hulls: construction in 2d and 3d, lower bounds; Triangulations: polygon

triangulations, representations, point-set triangulations, planar graphs; Voronoi

diagrams: construction and applications, variants; Delayney triangulations: divideand-

conquer, flip and incremental algorithms, duality of Voronoi diagrams, min-max

angle properties; Geometric searching: pointlocation, fractional cascading, linear

programming with prune and search, finger trees, concatenable queues, segment trees,

interval trees; Visibility: algorithms for weak and strong visibility, visibility with

reflections, art-gallery problems; Arrangements of lines: arrangements of hyperplanes,

zone theorems, many-faces complexity and algorithms; Combinatorial geometry:

Ham-sandwich cuts, Helly's theorems, k-sets, polytopes and hierarchies, polytopes

and linear progarmming in d-dimensions, complexity of the union of convex sets,

simply connected sets and visible regions; Sweep techniques: plane sweep for

segment intersections, Fortune's sweep for Voronoi diagrams, topological sweep for

line arrangements; Randomization in computational geometry: algorithms, techniques

for counting; Robust geometric computing; Applications of computational geometry.

CS 002 Computational Complexity L-T-P: 3-1-0, Credit: 4

Models of Computation, resources (time and space), algorithms, computability,

complexity; Complexity classes, P/NP/PSPACE, reductions, hardness, completeness,

hierarchy, relationships between complexity classes; Randomized computation and

complexity; Logical characterizations, incompleteness; Approximability; Circuit

complexity, lower bounds; Parallel computation and complexity; Counting problems;

Interactive proofs; Probabilistically checkable proofs; Communication complexity;

Quantum computation.

CS 003 Advances in Compiler Construction L-T-P: 3-1-0, Credit: 4

Review of compiler fundamentals - lexical analysis, parsing, semantic analysis, error

recovery and intermediate code generation; Runtime storage management; Code

generation; Code improvement - peephole optimization, dependence analysis and

redundancy elimination, loop optimization, procedural and inter-procedural

optimization, instruction scheduling, optimization for memory hierarchy; Compilation

for high performance architecture; Portability and retargetability; Selected topics from

compilers for imperative, object-oriented and mark-up languages, parallel and

distributed programming and concurrency.

CS 004 Algorithms for Bioinformatics L-T-P: 3-1-0, Credit: 4

Sequence similarity, homology, and alignment. Pairwise alignment: scoring model,

dynamic programming algorithms, heuristic alignment, and pairwise alignment using

Hidden Markov Models. Multiple alignment: scoring model, local alignment gapped

and ungapped global alignment. Motif finding: motif models, finding occurrence of

known sites, discovering new sites. Gene Finding: predicting reading frames,

maximal dependence decomposition. Analysis of DNA microarray data using

hierarchical clustering, model-based clustering, expectation-maximization clustering,

Bayesian model selection.

CS 005 Performance Evaluation and Reliability of Information Systems

L-T-P: 3-1-0, Credit: 4

Review of probability and statistics, stochastic processes, Markov Models, Parameter

estimation and hypothesis testing. Models of information systems, introduction to

reliability measures. Estimation of MTF and other reliability parameters. Software

metrics and software reliability models. Queuing network models, Workload design,

Benchmarks, Estimations of performance metrics, case studies.

CS 006 Advanced Graph Theory L-T-P: 3-1-0, Credit: 4

Basic Concepts: Graphs and digraphs, incidence and adjacency matrices,

isomorphism, the automorphism group; Trees: Equivalent definitions of trees and

forests, Cayley's formula, the Matrix-Tree theorem, minimum spanning trees;

Connectivity: Cut vertices, cut edges, bonds, the cycle space and the bond space,

blocks, Menger s theorem; Paths and Cycles: Euler tours, Hamilton paths and cycles,

theorems of Dirac, Ore, Bondy and Chvatal, girth, circumference, the Chinese

Postman Problem, the Travelling Salesman problem, diameter and maximum degree,

shortest paths; Matchings: Berge's Theorem, perfect matchings, Hall's theorem,

Tutte's theorem, Konig's theorem, Petersen's theorem, algorithms for matching and

weighted matching (in both bipartitie and general graphs), factors of graphs

(decompositions of the complete graph), Tutte's f-factor theorem; Extremal problems:

Independent sets and covering numbers, Turan's theorem, Ramsey theorems;

Colorings: Brooks theorem, the greedy algorithm, the Welsh-Powell bound, critical

graphs, chromatic polynomials, girth and chromatic number, Vizing's theorem;

Graphs on surfaces: Planar graphs, duality, Euler's formula, Kuratowski's theorem,

toroidal graphs, 2-cell embeddings, graphs on other surfaces; Directed graphs:

Tournaments, directed paths and cycles, connectivity and strongly connected

digraphs, branchings; Networks and flows: Flow cuts, Max flow min cut theorems,

perfect square; Selected topics: Dominating sets, the reconstruction problem,

intersection graphs, perfect graphs, random graphs.

CS 007 Speech and Natural Language Processing L-T-P: 3-1-0, Credit: 4

Speech and Natural Language Processing: Introduction; Brief Review of Regular

Expressions and Automata; Finite State Transducers; Word level Morphology and

Computational Phonology; Basic Text to Speech; Introduction to HMMs and Speech

Recognition. Indian language case studies; Part of Speech Tagging; Parsing with

CFGs; Probabilistic Parsing. Representation of Meaning; Semantic Analysis; Lexical

Semantics; Word Sense; Disambiguation; Discourse understanding; Natural Language

Generation; Techniques of Machine Translation; Indian Language case studies.

CS 008 Machine Learning L-T-P: 3-1-0, Credit: 4

The concept learning task. General-to-specific ordering of hypotheses. Version

spaces. Inductive bias. Decision Tree Learning. Rule Learning: Propositional and

First-Order, Over-fitting, Cross-Validation. Experimental Evaluation of Learning

Algorithms Instance-Based Learning: k-Nearest neighbor algorithm, Radial basis

functions. Case-based learning. Computational Learning Theory: probably

approximately correct (PAC) learning. Sample complexity. Computational

complexity of training. Vapnik-Chervonenkis dimension. Artificial Neural Networks :

Linear threshold units, Perceptrons, Multilayer networks and backpropagation,

recurrent networks. Probabilistic Machine Learning Maximum Likelihood Estimation,

MAP, Bayes Classifiers Naive Bayes. Bayes optimal classifers. Minimum description

length principle. Bayesian Networks, Inference in Bayesian Networks, Bayes Net

Structure Learning Unlabelled data: EM, preventing overfitting, cotraining Gaussian

Mixture Models, K-means and Hierarchical Clustering, Clustering and Unsupervised

Learning, Hidden Markov Models, Reinforcement Learning Support Vector Machines

Ensemble learning: boosting, bagging.

CS 009 Cryptography & Network Security L-T-P: 3-1-0, Credit: 4

Multi level model of security, Cryptography, Secret Key Cryptography, Modes of

Operation, Hashes and Message Digest, Public Key Algorithm, Security Handshake Pitfall,

Strong Password Protocol; Case study of real time communication security; Introduction

to the Concepts of Security, Security Approaches, Principles of security, Types of attacks;

Cryptographic Techniques: Plain text and Cipher text , Substitution Techniques,

Transposition Techniques Encryption and Decryption, Symmetric and Asymmetric Key

Cryptography. Computer-based symmetric Key Cryptographic; Algorithms: Algorithm

Types and Modes, An Overview of Symmetric Key Cryptography, Data Encryption

Standard (DES), International Data Encryption Algorithm (IDEA), Advanced Encryption

Standard (AES); Computer-based Asymmetric Key Cryptographic Algorithms;

Cryptography, An Overview of Asymmetric Key Cryptography, The RSA algorithm,

Symmetric and Asymmetric Key Cryptography Together, Digital Signatures, Knapsack

Algorithm; Public Key Infrastructure (PKI) Digital Certificates, Private Key Management ,

The PKI Model, Public Key Cryptography Standards (PKCS); Internet Security Protocols

Secure Socket Layer (SSL) , Secure Hyper Text Transfer Protocol (SHTTP) , Time Stamping

Protocol (TSP), Secure Electronic Transaction (SET), SSL versus SET

CS 010 Quantum Computing and Quantum Information Pr

4

Mathematical foundations; quantum mechanical principles; quantum entanglement;

reversible computation, qubits, quantum gates and registers; universal gates for

quantum computing; quantum parallelism and simple quantum algorithms; quantum

Fourier transforms and its applications, quantum search algorithms; elements of

quantum automata and quantum complexity theory; introduction to quantum error

correcting codes; entanglement assisted communication; elements of quantum

information theory and quantum cryptography.

ocessing L-T-P: 3-1-0, Credit:

CS 011 Intelligent Systems L-T-P: 3-1-0, Credit: 4

Data, information and knowledge. Model of an intelligent system. Models of

knowledge representations: Representation and reasoning in logic. Semantic

representations: semantic networks, frames; Frame/script systems; Conceptual

dependency and conceptual graphs. Ontologies. Knowledge based systems: Software

architecture of a knowledge-based system, Rulebased programming and production

systems, Rule chaining and inference control, Inference: reasoning about knowledge,

Temporal reasoning, Inference under uncertainty: Bayesian techniques, Fuzzy

reasoning, Casebased reasoning. Intelligent agents, The agent metaphor and attributes

of agenthood, Agent theory and languages, Inter-agent communication, Ontological

issues. Alternatives to the symbolic approach: Foundations of connectionist networks;

their history. Applications of AI: Example application domains, e.g. Configuration,

Diagnosis, Planning, intelligent interfaces, usermodelling, Practical implications of

choosing and applying AI solutions. Knowledge representation and the Web,

Semantic Web.

Sequential Languages (Imperative and Applicative): Operational Semantics, Vienna

Definition Methods, Denotational Semantics: Scott-Strachy Theory, Axiomatic Semantics:

Floyd- Hoare Approach, Temporal Logic, Algebraic Semantics and Data Types.

CS 012 Theory of Programming Languages L-T-P: 3-1-0, Credit: 4

Syntax of Programming Languages, Formal Language and Automata Theory: Finite

Automata, Regular Languages, Pushdown Automata, Context Free Languages, Linear

Bounded Automata, Context Sensitive Languages, Turing machines and Recursively

Enumerable Sets. Theory of LR(k) Parsing, Attribute Grammars. Semantics of

Programming Languages: Basic Mathematical Introduction: Propositional and

Predicate Calculus, Lambda Calculus, Algebraic Structures.

CS 013 Simulation And Modeling L-T-P: 3-1-0, Credit: 4

Introduction to Discrete-Event System Simulation: Definitions of Modeling and

Simulation the Nature of Simulation Systems Advantage and Disadvantages of

Simulation Area of Application Components of a system Discrete and Continuous

System Model of System Type of Models Discrete-Event System Simulation

Simulation Examples: Simulation of Queuing System Communication System Other

Example of Simulation

General Principles: Event-driven Simulation Word Views List Processing

Simulation Software: History of Simulation Selection Process Simulation in High Level

Language (C, C++

, Pascal Fortran) Simulation Packages (Matlab/ Simulink)

Mathematical and statistical Models: Terminology and Concept Useful Statistical

Models

Psuedo random numbers: Methods of Generation and testing. Methods for generating

continuous and discrete distributions. Methods for generating Poisson Process.

Queuing Models: Characteristics Performance Steady-State Behavior Network of

Queues

Random Number Generation: Properties Of Random Numbers Generation of Pseudo-

Random NumbersTesting of Randomness Pitfalls

Random Variate Generation: Invers Transform Direct Transform Convolution

Acceptance-Reject

Input Modeling: Collecting Data Identifying Distribution Histograms Parameter

Estimation Selecting Input Model without Data

Verification and Validation of Simulation Models: Model Building Verification and

Validation verification of Simulation

Output Analysis: Types of Simulation with respect to Output Analysis Stochastic Nature

of Output Data Measures of Performance Output Analysis for Termination Simulation

CS 014 Design of Embedded System L-T-P: 3-1-0, Credit: 4

CS 015 Research Methodology L-T-P: 3-1-0, Credit: 4

1. Embedded Computing Requirements: Characteristics and applications of

embedded systems;Components of Embedded Systems; challenges in Embedded

System Design and design process; Formalism for system design.

2. Embedded Processor Architecture/Microcontrollers: Role of processor selection

in embedded system, RISC vs. CISC architectures; overviews of 8-bits/16-bits/32-bits

microcontrollers, 8051 microcontroller: Architecture, basic assembly language

programming concepts, instruction sets, addressing modes, logical operations,

arithmetic operations, branching instructions, Boolean instructions, subroutines,

timing subroutine, serial data communication & interrupt process, assembly language

programming examples [8]

3. Interfacing, programming & real-time applications: Memory & I/O interfacing,

Timer & counter operation & Programming, Serial communication,& interrupt

handling, LCD & keyboard interfacing, DS 12887 RTC interfacing, interfacing

ADC/DAC, real world interfacing & applications.

4. [12]Embedded Software Analysis and Design: Concepts of concurrency, processes,

threads, mutual exclusion and inter-process communication, Models and languages

for embedded software, Synchronous approach to embedded system design,

Scheduling paradigms, Scheduling algorithms, Introduction to RTOS, Basic design

using RTOS Analysis and optimization of execution time, energy, power and

program size.

5. Embedded C Language: Real time methods, Mixing C and Assembly, Standard I/O

functions, Preprocessor directives, Study of C compilers and IDE, Programming the

target

Open Electives

OE 001 Random Variables and Stochastic Process L-T-P: 3-1-0, Credit: 4

OE 002 Advanced Microprocessor Based Systems L-T-P: 3-1-0, Credit: 4

Introduction: Basics of Von Neumann Architecture and the early Microprocessors,

CISC and RISC concepts; Parallelism in Processor Architecture: Pipelining, Superscalar,

Super-pipeline and VLIW Architectures, Low-power Architecture; Built-in

Multiprocessing support; Co-processors; Processor Architecture with hierarchical

memory organization: Cache memory, Virtual memory; Built-in Multi-user and

multitasking support in 16-bit and 32 bit microprocessors, Built-in memory mapping

and management support; Evolution of platform architecture; Special-purpose

processor Architectures: Signal processing Microprocessors; Communication

processors; Case studies with contemporary Microprocessors.

OE 003 Nano Electronics L-T-P: 3-1-0, Credit: 4

Shrink-down approaches: Introduction, CMOS Scaling, The nanoscale MOSFET, Finfets,

Vertical MOSFETs, limits to scaling, system integration limits (interconnect issues etc.),

Resonant Tunneling Transistors, Single electron

transistors, new storage, optoelectronic, and spintronics devices.

Atoms-up approaches: Molecular electronics involving single molecules as electronic

devices, transport in molecular structures, molecular systems as alternatives to

conventional electronics, molecular interconnects; Carbon

nanotube electronics, bandstructure & transport, devices, applications.

OE 004 Digital Message Transmission L-T-P: 3-1-0, Credit: 4

Examples of analog pulse and digital transmission systems. Performance analysis of

analog and pulse modulation systems. Role and review of probability theory and

stochastic processes in digital message transmission. Principles of detection theory:

Binary and m-ary hypothesis testing. Bayes' likelihood ratio test. Performance analysis of

digital communication systems. Spectrum of digital signals: Spectral efficiency of digital

communication systems; Nyquist pulse shaping.Correlative coding schemes. Equalization

techniques. Synchronization techniques. Carrier, bit and frame synchronization schemes.

OE 005 Telematics L-T-P: 3-1-0, Credit: 4

Basics of Telephony: Telephone Network overview; Subscriber Loop; Signalling in the

Telephone Network; Overview of ISDN, BISDN and ATM Technologies

Circuit Switching in Telephone Networks: Crossbar switch; Clos networks; Clos and

Slepian-Duguid theorems; Recursive construction of Clos Networks; Time switching,

TMS and TST switches; Lee and Jacobeus blocking analysis; Routing in R-NB network;

Switch processor, Call processing and overload control; Example telephone switches.

Cell Switching: Generic Switch; Input and output queued switches; Shared memory

and Shared medium switches, Crossbar switch, Complexity and scaling disdvantage of

output queued switches, Knockout principle; Interconnections for large switches, Self

routing architectures, Batcher-banyan networks; Unbufferred banyan switches,

Buffered banyan, Tandem banyan, Speedup, Parallelism and Channel grouping

toenhance input queued switches; Concentrators superconcentrators and Copy

networks, Examples of ATM switches, IP Switching from VC based fixed length packet

switches.

Multiplexing and Routing in Circuit Switched Networks: Abstract System Models

Erlang Blocking Models; Overflow Models, Equivalent Random Theory, Haywards

Approxmn and Introductory Non Poisson Arrival Processes; Product form solution;

Erlang Fixed Point Solution; Techniques to choose good routes; Alternate Routing;

Dynamic Routing, Least Busy Alternate Routing;

OE 006 Computational Number Theory L-T-P: 3-1-0, Credit: 4

Algorithms for integer arithmetic: Divisibility, gcd, modular arithmetic, modular

exponentiation, Montgomery arithmetic, congruence, Chinese remainder theorem,

Hensel lifting, orders and primitive roots, quadratic residues, integer and modular

square roots, prime number theorem, continued fractions and rational approximations.

Representation of finite fields: Prime and extension fields, representation of

extension fields, polynomial basis, primitive elements, normal basis, optimal normal

basis, irreducible polynomials. Algorithms for polynomials: Root-finding and factorization,

Lenstra-Lenstra-Lovasz algorithm, polynomials over finite fields. Elliptic curves: The elliptic

curve group, elliptic curves over finite fields, Schoof's

point counting algorithm. Primality testing algorithms: Fermat test, Miller-Rabin test,

Solovay-Strassen test, AKS test. Integer factoring algorithms: Trial division, Pollard rho

method, p-1 method, CFRAC method, quadratic sieve method, elliptic curve method.

Computing discrete logarithms over finite fields: Baby-step-giant-step method,

Pollard rho method, Pohlig-Hellman method, index calculus methods, linear sieve

method, Coppersmith's algorithm.

Applications: Algebraic coding theory, cryptography.

OE 007 Advances in Operating Systems Design L-T-P: 3-1-0, Credit: 4

Theory and implementation aspects of distributed operating systems. Process

synchronization in multiprocessing/multiprogramming systems. Inter-process

communication and co-ordination in large distributed systems. Distributed resource

management. Fundamentals of real time operating systems. Case studies. Information

management in distributed systems: security, integrity and concurrency problems.

Fault tolerance issues. OS issues related to the Internet, intranets, pervasive

computing, embedded systems, mobile systems and wireless networks. Case studies

of contemporary operating systems.

Linear control of manipulators: Introduction, feedback and closed loop control, second

order linear systems, control of second-order systems, Trajectory following control,

modeling and control of a single joint.

Robot Programming languages & systems: Introduction, the three level of robot

programming, requirements of a robot programming language, problems peculiar to

robot programming languages.

Off-line programming systems: Introduction, central issues in OLP system, cimstation,

automating subtasks in OLP systems.

OE 008 Robotics L-T-P: 3-1-0, Credit: 4

Matrix algebra, Inversion of Matrices, Rotational groups, matrix representation of co-

ordinate transformation.

Manipulator kinematics: kinematics: Introduction, solvability, algebraic solution by

reduction to polynomial, standard frames, repeatability and accuracy, computational

considerations.

Manipulator dynamics: introduction, acceleration of rigid body, mass distribution,

Newton’s equation, Euler’s equation, Iterative Newton-Euler dynamic formulation, closed

dynamic equation, Lagrangian formulation of manipulator dynamics, dynamic simulation,

computational consideration.

Trajectory Generation: Introduction, general considerations in path description and

generation, joint space schemes, Cartesian space schemes, Path generation in runtime,

Planning path using dynamic model.

OE 009 Matrix computations L-T-P: 3-1-0, Credit: 4

Basic iterative methods for solutions of linear systems and their rates of convergence.

Generalized conjugate gradient, Krylov space and Lanczos methods. Iterative methods for

symmetric, non-symmetric and generalized eigenvalue problems. Singular value

decompositions. Fast computations for structured matrices. Polynomial matrix

computations. Perturbation bounds for eigenvalues.

OE 010 Advance Mathematics L-T-P: 3-1-0, Credit: 4

Transform Methods – Laplace transform methods for one-dimensional wave equation –

Displacements in a String – Longitudinal vibrations of an elastic bar – Fourier transform

methods for one-dimensional heat conduction problems in infinite and semi-infinite rod.

Elliptic equations – Laplace equation – Fourier transform methods for Laplace equation –

Solution of Poisson equation by Fourier transform method.

Calculus of variations – Variation and its properties – Euler’s equation – Functionals

dependent on first and higher order derivatives – Functionals dependent on functions of

several independent variables – Some applications – Direct methods – Ritz methods.

Numerical solution of partial differential equations – Numerical Solution of Partial

Differential Equations – Solution of Laplace’s and Poisson equation on a rectangular

region by Liebmann’s Method – Diffusion equation by explicit and Crank Nicholson

implicit methods – Solution of wave equation by explicit scheme.

OE 011 Artificial Intelligence L-T-P: 3-1-0, Credit: 4

Machine Learning & AI - Introduction, hierarchical perspective and foundations. Rote

Learning, Learning by advice, learning in problem solving inductive learning, explanation

based learning, learning from observation and discovery, learning by analogy,

introduction to formal learning theory.

Biological neurons and brain, models of biological neurons, artificial neurons and neural

networks, Early adaptive nets Hopfield nets, back error propagation competitive learning

lateral inhibition and feature maps, Stability - Plasticity and noise saturation dilemma, ART

nets, cognition and recognition.

Neural nets as massively parallel, connectionist architecture, Application in solving

problems from various are as e.g., AI, Computer Hardware, networks, pattern recognition

sensing and control etc.

Reference:

Practical

CS 651 Computing Lab-I L-T-P: 0-0-6, Credit: 4

Object-oriented programming concepts and implementation of abstract data types.

Implementation of graph algorithms. Linear programming with applications. Basics of

OS programming: process creation and synchronization, shared memory and

semaphore, shell programming.

CS 661 Computing Lab-II L-T-P: 0-0-6, Credit: 4

Socket programming, database creation and update, building large client server applications. Basics of compiler writing using lex and yacc.

M.Tech. (CS) 1st Semester

List of Text/ Reference Books

Cryptography & Network Security

S.No. Title Author/Publishers

1. Cryptography & Network Security Atul Kahate, Tata McGraw Hill

2. Cryptography & Network Security William Stalling, Pearson

Education

Foundation of Computer Science:

1. Discrete Maths and Its Application Bhupinder Singh, Khanna Book

2. Elements of the Theory of Computation Harry R. Lewis, Pearson Education

3. Theory of computer Science K.L.P. Mishra, PHI India

Analysis and Design of Algorithms

1. Introduction of Algorithms H.Cormen & Rivest, PHI India

2. Fundamental of Algorithms Ellis Haro Witzand Satraj Sahni,

University Publishers

Wireless And Mobile Communication

1. Wireless Communications Rappaport Theadores, Pearson

Prentice Hall

2. Introduction Wireless and Mobile System Agarwal DP, Thomson

Artificial Intelligence

1. Artificial Intelligence and Intelligent

Systems

N.P. Padhy, Oxford University

Press

2. Introduction to Artificial Neural Systems Jacek M. Zurada, CBC

3. Artificial Intelligence Peter Norving

M.Tech. (CS) 2nd

Semester

List of Text/ Reference Books Parallel and Distributed Algorithms:

S.No. Title Author

1. Parallel and distributed computation : Numeric

elements Dimitrip Bert sekar, John N

2. An Introduction parallel algorithm J. Jaja

3. Algorithms: sequential, parallel and distributes Kenneth Berman, Jerome Paul

4. Designing efficient algorithm for parallel

computers M.J.Quinn

5. Introduction to distributed algorithms Gerard tel

6. Introduction to parallel computing Vipin kumar

7. Introduction to parallel algorithm architecture T. leightm

Internet Protocols

1.The Internet and Its Protocols, A comparative

Approach Andrian Farrel

2. TCP/IP Red Book from IBM Corporation

Real Time Operating Systems:

1. Real Time Systems Design and Analysis : An

Engineer’s HandbookPhillp A. Laplante, 2nd Edition, PHI

2. Real Time system Design Levi Shem Tov and Ashok K.

Agrawala (New York MGH)

3. Real Time Systems and their Programming

Language Burns

Alan and Andy

Welling (New York, Addison

Wesley)

4. Proceedings of IEEE Special Issue on Real Time

Systems (Jan 1994)

5. The design of Real time Applications M. Blackman (New York John

Wiley & Sons).

6. Real time systems C.M. Krishna, K.G. Shin

(TMGh)

Simulation and Modeling

S.No. Title Author

1. Simulation Modeling and Analysis, 3rdEdition, by Law Kelton,

McGraw-Hill, New

2. Discrete-Event System Simulation David M. Nicol, PHI

3. System Simulation with Digital Computer Narsingh Deo, PHI

4. Simulation Modeling and Analysis Averill M. Law McGraw-Hill

Design of Embedded System

1. Embedded System Design: A Unified

Hardware/Software Introduction

Frank Vahid, Tony Givargis,

John Wiley

2. Embedded Linux Craig Hollabaugh, Pearson

Education 3. Fundamentals of Embedded Software Daniel Lewis,Pearson Education 4. Embedded C Programming and the Atmel AVR Barnett, Cox, O’Cull,, Thomson

Learning 5. Programming and Customizing the 8051

Microcontroller Myke Predko