Practical 6




НазваниеPractical 6
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TOTAL = 45



REFERENCES:


1. Brian Hambling, “Managing Software Quality”, Tata McGraw Hill.

2. Juran. J.M.Frank, M.Gyrna,Quality Planning and Analysis (from product developmement through use), Tata McGraw Hill.

3. Alcon Gillies, “Software Quality: Theory and Management”, International Thomson, Computer Press 1997.

4. Stephen H.Kan, “Metrics and Models in Software Quality Engineering”, Addison Wesley, 1955.

5. Roger S. Pressman, “Software Engineering - A Practitioner’s Approach”, Fifth Edition, McGraw Hill, 2001.

6. Humphrey Watts, “Managing the Software Process”, Addison Wesley, 1986.


MC9278 TCP/IP DESIGN AND IMPLEMENTATION

L T P C

3 0 0 3

UNIT I INTRODUCTION 9

Internetworking concepts and architectural model– classful Internet address – CIDR–Subnetting and Supernetting –ARP– RARP– IP – IP Routing –ICMP – Ipv6.


UNIT II TCP 9

Services – header – connection establishment and termination– interactive data flow– bulk data flow– timeout and retransmission – persist timer – keep alive timer– futures and performance.


UNIT III IP IMPLEMENTATION 9

IP global software organization – routing table– routing algorithms–fragmentation and reassembly– error processing (ICMP) –Multicast Processing (IGMP).


UNIT IV TCP IMPLEMENTATION I 9

Data structure and input processing – transmission control blocks– segment format– comparison–finite state machine implementation–Output processing– mutual exclusion–computing the TCP data length.


UNIT V TCP IMPLEMENTATION II 9

Timers–events and messages– timer process– deleting and inserting timer event– flow control and adaptive retransmission–congestion avoidance and control – urgent data processing and push function.

TOTAL = 45


TEXT BOOKS:


1. Douglas E.Comer, “Internetworking with TCP/IP Principles, Protocols and

Architecture”, Vol 1 & 2, fourth edition, Pearson Education Asia, 2003.

2. W.Richard Stevens “TCP/IP illustrated” Volume 1 Pearson Education, 2003.


REFERENCES:


1. Forouzan, “TCP/IP protocol suite” Second edition, Tata McGraw Hill, 2003.

2. W.Richard Stevens “TCP/IP illustrated” Volume 2, Pearson Education 2003.




MC9279 DISTRIBUTED SYSTEMS

L T P C

3 0 0 3

UNIT I COMMUNICATION IN DISTRIBUTED ENVIRONMENT 8

Introduction – Various Paradigms in Distributed Applications – Remote Procedure Call – Remote Object Invocation – Message-Oriented Communication – Unicasting, Multicasting and Broadcasting – Group Communication.


UNIT II DISTRIBUTED OPERATING SYSTEMS 12

Issues in Distributed Operating System – Threads in Distributed Systems – Clock Synchronization – Causal Ordering – Global States – Election Algorithms –Distributed Mutual Exclusion – Distributed Transactions – Distributed Deadlock – Agreement Protocols .


UNIT III DISTRIBUTED RESOURCE MANAGEMENT 10

Distributed Shared Memory – Data-Centric Consistency Models – Client-Centric Consistency Models – Ivy – Munin – Distributed Scheduling – Distributed File Systems – Sun NFS.


UNIT IV FAULT TOLERANCE AND CONSENSUS 7

Introduction to Fault Tolerance – Distributed Commit Protocols – Byzantine Fault Tolerance – Impossibilities in Fault Tolerance.


UNIT V CASE STUDIES 8

Distributed Object-Based System – CORBA – COM+ – Distributed Coordination-Based System – JINI.

Total= 45

REFERENCES:

  1. George Coulouris, Jean Dollimore, Tim Kindberg, “Distributed Systems Concepts and Design”, Third Edition, Pearson Education Asia, 2002.

  2. Hagit Attiya and Jennifer Welch, “Distributed Computing: Fundamentals, Simulations and Advanced Topics”, Wiley, 2004.

  3. Mukesh Singhal, “Advanced Concepts In Operating Systems”, McGrawHill Series in Computer Science, 1994.

  4. A.S.Tanenbaum, M.Van Steen, “Distributed Systems”, Pearson Education, 2004.

  5. M.L.Liu, “Distributed Computing Principles and Applications”, Pearson Addison Wesley, 2004.



MC9280 DATA MINING AND DATA WAREHOUSING

L T P C

3 0 0 3

UNIT I 9

Data Warehousing and Business Analysis: - Data warehousing Components –Building a Data warehouse – Mapping the Data Warehouse to a Multiprocessor Architecture – DBMS Schemas for Decision Support – Data Extraction, Cleanup, and Transformation Tools –Metadata – reporting – Query tools and Applications – Online Analytical Processing (OLAP) – OLAP and Multidimensional Data Analysis.

UNIT II 9

Data Mining: - Data Mining Functionalities – Data Preprocessing – Data Cleaning – Data Integration and Transformation – Data Reduction – Data Discretization and Concept Hierarchy Generation.

Association Rule Mining: - Efficient and Scalable Frequent Item set Mining Methods – Mining Various Kinds of Association Rules – Association Mining to Correlation Analysis – Constraint-Based Association Mining.

UNIT III 9

Classification and Prediction: - Issues Regarding Classification and Prediction – Classification by Decision Tree Introduction – Bayesian Classification – Rule Based Classification – Classification by Back propagation – Support Vector Machines – Associative Classification – Lazy Learners – Other Classification Methods – Prediction – Accuracy and Error Measures – Evaluating the Accuracy of a Classifier or Predictor – Ensemble Methods – Model Section.

UNIT IV 9

Cluster Analysis: - Types of Data in Cluster Analysis – A Categorization of Major Clustering Methods – Partitioning Methods – Hierarchical methods – Density-Based Methods – Grid-Based Methods – Model-Based Clustering Methods – Clustering High-Dimensional Data – Constraint-Based Cluster Analysis – Outlier Analysis.

UNIT V 9

Mining Object, Spatial, Multimedia, Text and Web Data:

Multidimensional Analysis and Descriptive Mining of Complex Data Objects – Spatial Data Mining – Multimedia Data Mining – Text Mining – Mining the World Wide Web.


Total = 45

REFERENCES

  1. Jiawei Han and Micheline Kamber “Data Mining Concepts and Techniques” Second Edition,

  2. Elsevier, Reprinted 2008.

  3. Alex Berson and Stephen J. Smith “Data Warehousing, Data Mining & OLAP”, Tata McGraw – Hill Edition, Tenth Reprint 2007.

  4. K.P. Soman, Shyam Diwakar and V. Ajay “Insight into Data mining Theory and Practice”, Easter Economy Edition, Prentice Hall of India, 2006.

  5. G. K. Gupta “Introduction to Data Mining with Case Studies”, Easter Economy Edition, Prentice Hall of India, 2006.

  6. Pang-Ning Tan, Michael Steinbach and Vipin Kumar “Introduction to Data Mining”, Pearson Education, 2007.






MC9281 COMPONENT BASED TECHNOLOGY

L T P C

3 0 0 3

UNIT I INTRODUCTION 9

Software Components – objects – fundamental properties of Component technology – modules – interfaces – callbacks – directory services – component architecture – components and middleware.
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