Download JNTUK M.Tech R19 CSE M.Tech Computer Science Course Structure And Syllabus

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DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING

COURSE STRUCTURE & SYLLABUS M.Tech CSE for COMPUTER SCIENCE PROGRAMME (Applicable for batches admitted from 2019-2020)

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JAWAHARLAL NEHRU TECHNOLOGICAL UNIVERSITY KAKINADA

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M. Tech. (CS) I SEMESTER

*Student has to choose any one audit course listed below.

II SEMESTER

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*Student has to choose any one audit course listed below.

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Audit Course 1 & 2:

1. English for Research Paper Writing
2. Disaster Management

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3. Sanskrit for Technical Knowledge
4. Value Education
5. Constitution of India
6. Pedagogy Studies
7. Stress Management by Yoga

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8. Personality Development through Life Enlightenment Skills

III SEMESTER

#Students going for Industrial Project/Thesis will complete these courses through MOOCs

IV SEMESTER

Open Electives offered by the Department of Computer Science and Engineering for other Departments students

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1. Python Programming
2. Data Science
3. Bioinformatics
4. Digital Forensics
5. Web Security

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6. Machine Learning

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I Year - I Semester

Mathematical Foundations of Computer Science (MTCSE1101)

Course Objectives:

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• To understand the mathematical fundamentals that are vital many courses in the field of Computer Science.
• To develop the understanding of the mathematical and logical basis to many modern techniques in information technology like machine learning, programming language design, and concurrency.
• To study various sampling and classification problems.

Course Outcomes: After completion of course, students would be able to

• Demonstrate skills in solving mathematical problems.

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• Comprehend mathematical principles and logic.
• Demonstrate knowledge of mathematical modeling and proficiency in using mathematical software
• Manipulate and analyze data numerically and/or graphically using appropriate Software.
• Communicate effectively mathematical ideas/results verbally or in writing.

UNIT I: Mathematical Logic-Propositional Calculus: Statements and Notations, Connectives, Well Formed Formulas, Truth Tables, Tautologies, Equivalence of Formulas, Duality Law, Tautological Implications, Normal Forms, Theory of Inference for Statement Calculus, Consistency of Premises, Indirect Method of Proof. Predicate Calculus: Predicative Logic, Statement Functions, Variables and Quantifiers, Free and Bound Variables, Inference Theory for Predicate Calculus.

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UNIT II: Set Theory-Introduction, Operations on Binary Sets, Principle of Inclusion and Exclusion, Relations: Properties of Binary Relations, Relation Matrix and Digraph, Operations on Relations, Partition and Covering, Transitive Closure, Equivalence, Compatibility and Partial Ordering Relations, Hasse Diagrams, Functions: Bijective Functions, Composition of Functions, Inverse Functions, Permutation Functions, Recursive Functions, Lattice and its Properties.

UNIT III: Algebraic Structures and Number Theory- Algebraic Structures: Algebraic Systems, Examples, General Properties, Semi Groups and Monoids, Homomorphism of Semi Groups and Monoids, Group, Subgroup, Abelian Group, Homomorphism, Isomorphism, Number Theory: Properties of Integers, Division Theorem, The Greatest Common Divisor, Euclidean Algorithm, Least Common Multiple, Testing for Prime Numbers, The Fundamental Theorem of Arithmetic, Modular Arithmetic (Fermat's Theorem and Euler's Theorem)

UNIT IV: Combinatorics- Basic of Counting, Permutations, Permutations with Repetitions, Circular Permutations, Restricted Permutations, Combinations, Restricted Combinations, Generating Functions of Permutations and Combinations, Binomial and Multinomial Coefficients, Binomial and Multinomial Theorems, The Principles of Inclusion–Exclusion, Pigeonhole Principle and its Application.

UNIT V: Recurrence Relations-Generating Functions, Function of Sequences, Partial Fractions, Calculating Coefficient of Generating Functions, Recurrence Relations, Formulation as Recurrence Relations, Solving Recurrence Relations by Substitution and Generating Functions, Method of Characteristic Roots, Solving Inhomogeneous Recurrence Relations, Graph Theory: Basic Concepts of Graphs, Sub graphs, Matrix Representation of Graphs: Adjacency Matrices, Incidence Matrices, Isomorphic Graphs, Paths and Circuits, Eulerian and Hamiltonian Graphs, Multigraphs, Planar Graphs, Euler's Formula, Graph Colouring and Covering, Chromatic Number, Spanning Trees, Algorithms for Spanning Trees (Problems Only and Theorems without Proofs).

Text Books:

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1. Discrete Mathematical Structures with Applications to Computer Science, J. P. Tremblay and P. Manohar, Tata McGraw Hill.
2. Elements of Discrete Mathematics-A Computer Oriented Approach, C. L. Liu and D. P. Mohapatra, 3rd Edition, Tata McGraw Hill.
3. Discrete Mathematics and its Applications.

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Theory, K. H. Rosen, 7th Edition, Tata McGraw Hill.

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Reference Books:

1. Discrete Mathematics for Computer Scientists and Mathematicians, J. L. Mott, A. Kandel, T. P. Baker, 2nd Edition, Prentice Hall of India.
2. Discrete Mathematical Structures, Bernand Kolman, Robert C. Busby, Sharon Cutler Ross, PHI.
3. Discrete Mathematics, S. K. Chakraborthy and B.K. Sarkar, Oxford, 2011.

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I Year - I Semester

Advanced Data Structures (MTCS1102)

Course objectives:

• To be familiar with basic techniques of object oriented principles and exception handling using C++
• To be familiar with the concepts like Inheritance, Polymorphism

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• Solve problems using data structures such as linear lists, stacks, queues, hash tables
• Be familiar with advanced data structures such as balanced search trees, AVL Trees, and B Trees.

Course outcomes:

• Select appropriate data structures as applied to specified problem definition.
• Apply advanced data structure strategies for exploring complex data structures.

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• Implement all data structures like stacks, queues, trees, lists and graphs and compare their Performance and trade offs
• Implement operations like searching, insertion, and deletion, traversing mechanism etc. on various data structures.
• Incorporate data structures into the applications such as binary search trees, AVL, Red Black, splay and B Trees
• Determine and analyze the complexity of given Algorithms

UNIT I: Arrays Abstract Data Types and the C++ Class, The Array as an Abstract Data Type, The Polynomial Abstract Data type, Spares Matrices, Introduction- Sparse Matrix Representation- Transposing a Matrix- Matrix Multiplication, Representation of Arrays. Stacks And Queues- Templates in C++, The Stack Abstract Data Type, The Queue Abstract Data Type, Subtyping and Inheritance in C++, Evaluation of Expressions, Expression- Postfix Notation- Infix to Postfix.

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UNIT II: Linked Lists Single Linked List and Chains, Representing Chains in C++, The Template Class Chain, Circular Lists, Available Space Lists, Linked Stacks and Queues, Polynomials, Equivalence Classes, Sparse Matrices, Doubly Linked Lists, Generalized Lists, Representation of Generalized Lists, Trees Introduction, Binary Trees, Binary Tree Traversal and Tree Iterators-Introduction, Inorder, Preorder, Postorder Traversal, Thread Binary Trees, Heaps, Binary Search Trees.

UNIT III: Graphs The Graph Abstract Data Type, Elementary Graph Operation, Minimum Cost Spanning Trees, Shortest Paths and Transitive Closure, Hashing- Introduction, Static Hashing, Dynamic Hashing

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UNIT IV: Priority Queues Binomial heaps, Fibonacci Heaps, Symmetric Min-Max Heaps, Efficient Binary Search Trees Optimal Binary Search Trees, AVL trees, Red-Black Trees, Splay Trees.

UNIT V: Multyway Search Trees m-way Search Trees, B- Trees, B+- Trees Digital Search Trees Digital Search Trees, Binary Tries and Patricia, Multiway Tries

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Text Books:

1. Data structures, Algorithms and Applications in C++, S.Sahni, 2nd edition, Universities Press, Pvt. Ltd.
2. Data structures and Algorithm Analysis in C++, Mark Allen Weiss, Pearson Education. Ltd., Second Edition.
3. Data structures and Algorithms in C++, Michael T.Goodrich, R.Tamassia and Mount, Wiley student edition, John Wiley and Sons.

Reference Books:

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1. Data structures and algorithms in C++, 3rd Edition, Adam Drozdek, Thomson
2. Data structures using C and C++, Langsam, Augenstein and Tanenbaum, PHI.
3. Problem solving with C++, The OOP, Fourth edition, W.Savitch, Pearson education.

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I Year - I Semester

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Advanced Operating Systems ( MTCS11XX)

Course Objectives:

This course is aimed at enabling the students to

• provide comprehensive and up-to-date coverage of the major developments in distributed Operating System, Multi-processor Operating System and Database Operating System and to cover important theoretical foundations including Process Synchronization, Concurrency, Event ordering, Mutual Exclusion, Deadlock, Agreement Protocol, Security, Recovery and fault tolerance.

Course Outcomes:

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After the completion of the course, student will be able to

• Illustrate on the fundamental concepts of distributed operating systems, its architecture and distributed mutual exclusion.
• Analyze on deadlock detection algorithms and agreement protocols.
• Make use of algorithms for implementing DSM and its scheduling.
• Apply protection and security in distributed operating systems.

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• Elaborate concurrency control mechanisms in distributed database systems.

UNIT I: Introduction- Architectures of Distributed Systems - System Architecture types - issues in distributed operating systems - communication networks - communication primitives. Theoretical Foundations - inherent limitations of a distributed system - lamp ports - logical clocks - vector clocks - casual ordering of messages - global state - cuts of a distributed computation - termination detection. Distributed Mutual Exclusion - introduction - the classification of mutual exclusion and associated algorithms - a comparative performance analysis.

UNIT II: Distributed Deadlock Detection -Introduction - deadlock handling strategies in distributed systems - issues in deadlock detection and resolution - control organizations for distributed deadlock detection - centralized and distributed deadlock detection algorithms -hierarchical deadlock detection algorithms. Agreement protocols - introduction-the system model, a classification of agreement problems, solutions to the Byzantine agreement problem, applications of agreement algorithms. Distributed resource management: introduction-mechanism for building distributed file systems - design issues - log structured file systems

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UNIT III: Distributed shared memory-Architecture- algorithms for implementing DSM - memory coherence and protocols - design issues. Distributed Scheduling - introduction - issues in load distributing - components of a load distributing algorithm - stability - load distributing algorithm - performance comparison - selecting a suitable load sharing algorithm - requirements for load distributing -task migration and associated issues. Failure Recovery and Fault tolerance: introduction- basic concepts - classification of failures - backward and forward error recovery, backward error recovery- recovery in concurrent systems - consistent set of check points - synchronous and asynchronous check pointing and recovery - check pointing for distributed database systems- recovery in replicated distributed databases.

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UNIT IV: Protection and security -preliminaries, the access matrix model and its implementations.-safety in matrix model- advanced models of protection. Data security - cryptography: Model of cryptography, conventional cryptography- modern cryptography, private key cryptography, data encryption standard- public key cryptography - multiple encryption - authentication in distributed systems.

UNIT V: Multiprocessor operating systems - basic multiprocessor system architectures - inter connection networks for multiprocessor systems - caching - hypercube architecture. Multiprocessor Operating System - structures of multiprocessor operating system, operating system design issues- threads- process synchronization and scheduling. Database Operating systems :Introduction- requirements of a database operating system Concurrency control : theoretical aspects - introduction, database systems - a concurrency control model of database systems- the problem of concurrency control - serializability theory- distributed database systems, concurrency control algorithms - introduction, basic synchronization primitives, lock based algorithms-timestamp based algorithms, optimistic algorithms - concurrency control algorithms, data replication.

Text Books:

1. Mukesh Singhal, Niranjan G.Shivaratri, "Advanced concepts in operating systems: Distributed, Database and multiprocessor operating systems", TMH, 2001
2. Distributed principles, Algorithms and Systems Computing Reissue Edition, Kindle Edition by Ajay D. Kshemkalyani, Mukesh Singhal

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Reference Books:

1. Andrew S.Tanenbaum, "Modern operating system", PHI, 2003.
2. Pradeep K.Sinha, "Distributed operating system-Concepts and design", PHI, 2003.
3. Andrew S.Tanenbaum, "Distributed operating system", Pearson education, 2003

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I Year - I Semester

Advanced Computer Architecture

Course Objective:

• Understand the Concept of Parallel Processing and its applications.
• Implement the Hardware for Arithmetic Operations.

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• Analyze the performance of different scalar Computers.
• Develop the Pipelining Concept for a given set of Instructions.
• Distinguish the performance of pipelining and non pipelining environment in a processor.

Course Outcomes:

After the completion of the course, student will be able to

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• know the types of computers, and new trends and developments in computer architecture.
• Understand pipelining, instruction set architectures, memory addressing.
• Understand exploiting ILP using dynamic scheduling, multiple issue, and speculation.
• Understand the various techniques to enhance a processors ability to exploit Instruction-level parallelism (ILP), and its challenges.
• Understand multithreading by using ILP and supporting thread-level parallelism (TLP).

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UNIT I: Fundamentals of Computer Design-Fundamentals of Computer design, Changing faces of computing and task of computer designer, Technology trends, Cost price and their trends, Measuring and reporting performance, Quantitative principles of computer design, Amdahl's law, Instruction set principles and examples- Introduction, Classifying instruction set- Memory addressing- type and size of operands, Operations in the instruction set.

UNIT II: Pipelines- Introduction, Basic RISC instruction set, Simple implementation of RISC instruction set, Classic five stage pipe lined RISC processor, Basic performance issues in pipelining, Pipeline hazards, Reducing pipeline branch penalties, Memory Hierarchy Design- Introduction, Review of ABC of cache, Cache performance, Reducing cache miss Penalty, Virtual memory.

UNIT III: Instruction Level Parallelism the Hardware Approach: Instruction- Level parallelism, Dynamic scheduling, Dynamic scheduling using Tomasulo's approach, Branch prediction, high performance instruction delivery- hardware based speculation.

UNIT IV: ILP Software Approach Basic compiler level techniques, Static branch prediction, VLIW approach, Exploiting ILP, Parallelism at compile time, Cross cutting issues -Hardware verses Software.

UNIT V: Multi Processors and Thread Level Parallelism:

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Multi Processors and Thread level Parallelism- Introduction, Characteristics of application domain, Systematic shared memory architecture, Distributed shared memory architecture, Synchronization, Inter Connection and Networks- Introduction, Interconnection network media, Practical issues in interconnecting networks, Examples of inter connection, Cluster, Designing of clusters, Intel Architecture- Intel IA-64 ILP in embedded and mobile markets Fallacies and pit falls.

Text Books:

1. John L. Hennessy, David A. Patterson Computer Architecture: A Quantitative Approach, 3rd Edition, An Imprint of Elsevier.

References:

1. John P. Shen and Miikko H. Lipasti – Modern Processor Design : Fundamentals of Super Scalar Processors

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2. Computer Architecture and Parallel Processing Faye A.Brigs., MC Graw Hill.
3. Advanced Computer Architecture – A Design Space Approach Dezso Sima, Terence Fountain,

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Peter Kacsuk, Pearson Ed

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I Year - I Semester

Parallel Computing ( MTCS11XX)

Course Objective: Students will demonstrate an understanding of concepts, algorithms, and design principles underlying parallel computing, develop algorithm design and implementation skills, and gain practical experience in programming large scale parallel machines.

Course Outcomes:

After the completion of the course, student will be able to

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• Describe different parallel architectures; inter-connect networks, programming models, and algorithms for common operations such as matrix-vector multiplication.
• Develop an efficient parallel algorithm to solve it.
• Analyze a parallel algorithm time complexity as a function of the problem size and number of processors.
• Analyze parallel code performance, determine computational bottlenecks, and optimize the performance of the code.
• Implement parallel algorithm using MPI, OpenMP, pthreads, or a combination of MPI and OpenMP.

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UNIT I: History- Introduction, Modern Scientific Method, Evolution of Supercomputing, Modem Parallel Computers, Seeking Concurrency, Data Clustering, Programming Parallel Computers. Parallel Architectures: Introduction, Interconnection Networks, Processor Arrays, Multiprocessors, Multi computers, Flynn's Taxonomy

UNIT II: Parallel Algorithm Design- Introduction, The Task/Channel Model, Foster's Design Methodology, Boundary Value Problem ,Finding the Maximum, The n-Body Problem, Adding Data Input, Message-Passing Programming- Introduction, The Message-Passing Model, The Message- Passing Interface, Circuit Satisfiability, Introducing Collective Communication, Benchmarking Parallel Performance.

UNIT III: The Sieve of Eratosthenes-Introduction, Sequential Algorithm, Sources of Parallelism, Data Decomposition options, Developing the Parallel Algorithm, Analysis of Parallel Sieve Algorithm, Documenting the Parallel Program, Benchmarking, Improvements, Performance Analysis- Introduction, Speedup and Efficiency, Amdahl's Law, Gustafson-Barsis's Law, The Karp-Flatt Metric, The Iso- efficiency Metric.

UNIT IV: Matrix Multiplication, Introduction, Sequential Matrix Multiplication, Row wise Block- Striped Parallel Algorithm, Cannon's Algorithm, Solving Linear Systems, Back Substitution, Gaussian Elimination, Iterative Methods, Sorting Introduction, Quick sort, A Parallel Quick sort Algorithm, Hyper quick sort Algorithm, Parallel Sorting by Regular Sampling.

UNIT V: Shared-Memory Programming – Introduction, The Shared-Memory Model, Parallel for Loops, Declaring Private Variables, Critical section, Reductions, Performance Improvements, More General Data Parallelism, Functional Parallelism, Combining MPI and OpenMP -Introduction, Conjugate Gradient Method, Jacobi Method.

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Text Books:

1. Parallel Programming in C with MPI and OpenMP Michael J, Quinn Oregon State University.

Reference books:

1. Distributed and Cloud Computing: From Parallel Processing to the Internet of Things 1st Edition, Kai Hwang, Jack Dongarra, Geoffrey C. Fox

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I Year - I Semester

ADVANCED DATABASES ( MTCS11XX)

Course Objectives:

• Design and implement advanced queries using Structured Query Language
• To study the usage and applications of Object Oriented database

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• To acquire knowledge on variety of NoSQL databases
• To attain inquisitive attitude towards research topics in NoSQL databases

Course Outcomes:

• Understand Distributed Database Process, Architecture, and Design Principles.
• Apply Distributed Query Optimization Techniques and Algorithms.

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• Analyze and apply Concurrency Control and Reliability Techniques,
• Analyze Need of Complex Data type like ORDBMS and OODBMS
• Identify Emerging Database Models.

UNIT I: Database Analysis and Design Techniques: Review of basic Database Concepts, Database Design Methodologies. ER Modeling: Specialization, Generalization, Aggregation, Normalization Theory. Database Implementation using UML: Introduction to UML, Structure diagrams, behavioral diagrams, object oriented analysis, class diagram, Advanced Transaction Processing and Concurrency Control: Transaction Concepts, Concurrency Control: Locking Methods, Time stamping Methods, Optimistic Methods for Concurrency Control, Concurrency Control in Distributed Systems.

UNIT II: Query Compiler: Introduction, parsing, generating logical query plan from parse tree. Query Processing: Physical-Query-plan Operators. Operations: selection, sorting, join, project, set. Query Evaluation: Introduction, Approaches to QE, Transformation of relational expressions in Query optimization, heuristic optimization, cost estimation for various operations, transformation rule.

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UNIT III: Distributed Database Centralized DBMS and Distributed DBMS, functions and architecture of a DDBMS, Distributed Data Storage, Transparency issues in DDBMS, Query Processing DDBMS, Distributed transaction Management and Protocols, Distributed Concurrency Control and Deadlock Management.

UNIT IV: Object Oriented Database Limitations of RDBMS, Need of Complex Datatype, Data Definition, ODBMS Fundamentals, issues in OODBMS, Object-oriented database design. Comparison of ORDBMS and OODBMS.

UNIT V: Emerging Database Models, Technologies and Applications Multimedia database-Emergence, difference from other data types, structure, deductive databases, GIS and spatial databases, Knowledge database, Information Visualization, Wireless Networks and databases, Personal database, Digital libraries, web databases, case studies.

Text Books:

1. Advanced database management system by RiniChkrabarti and Shibhadra Dasgupta, Dreamtech.

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2. Distributed Databases by Ozsu and Valduriez „Pearson Education.

Reference Books:

1. Fundamentals of Database Systems by Ramez Elmasri, Shamkant Navathe, Pearson Education
2. Database System Concepts by Abraham Silberschatz, Henry F. Korth, S. Sudarshan, Tata McGraw-Hill.

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I Year - I Semester

Advanced Computer Networks ( MTCS11XX)

Course Objectives:

• The course is aimed at providing basic understanding of Protocols at Network layers with special emphasis on IP, TCP & UDP and Routing algorithms.
• Implementation Routing and Addressing.

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• Provide the mathematical background of routing protocols.
• Aim of this course is to develop some familiarity with current research problems and research methods in advance computer networks.



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