Information technology engineering semester 8 syllabus

Information technology engineering semester 8 syllabus – The final semester for Information technology engineering in Mumbai University Bachelors degree for semester 8 has 5 main subjects and a project.These are Computer simulation modelling,Big data Analytics, Enterprise resource planning,Wireless sensor networks and Robotics.

Information technology engineering semester 8 syllabus

Storage Network Management  and Retrieval

 

NEED FOR INTRODUCTION:- Limitations of traditional server 10
STORAGE centric architecture,. Storage centric architecture and its
NETWORK advantages.
BASICS OF STORAGE NETWORK:- Intelligent
Storage Systems (ISS), Data protection ( RAID
implementation methods).RAID arrays ,Components,
RAID technologies, RAID levels, RAID impact on disk,
performance & RAID comparison.
II STORAGE SCSI, SAN: FC SAN FC Protocol Stack, IP Storage, 08
NETWORK Infiniband, Virtual Interfaces
ARCHITECTURE
III ADVANCED NETWORK ATTACHED STORAGE (NAS):- Local 14
STORAGE File systems, Network File systems and file servers,
TECHNOLOGY Shared Disk File systems: Case study, Comparison:
NAS, FC SAN and iSCSI SAN.
STORAGE VIRTUALIZATION:- Virtualization in I/O
path, Limitations and requirements, Definition of
Storage Virtualization, Storage virtualization on Block
and file level, Storage virtualization on various levels of
Storage network, Symmetric and Asymmetric
Virtualization.
IV STORGAE BC Terminology, BC Planning Lifecycle, General 06
NETWORK Conditions for Backup, Recovery Considerations,
BACKUP AND Network Backup Services Performance Bottlenecks of
RECOVERY Network Backup, Backup Clients, Back up file systems,
Backup Databases, Next Generation Backup.
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V INFORMATION Overview, Abstraction , Information System, Measures, 10
RETRIEVAL IN from Data to Wisdom, Document and Query Form,
STORAGE Query structures, The matching process, Text analysis:
NETWORK Indexing, Matrix representation, Term extraction, Term
association, , Stemming , Multilingual retrieval systems
Text Books:
1. ULF Troppen, Rainer Erkens and Wolfgang Muller , “ Storage Networks Explained:
Basic and Applications of Fibre Channel SAN, NAS and ISCSI and Infifniband “ ,
Wiley
2. EMC Educational Services, “Information Storage and Management”, wiley India
3. R. R. Korfhage, “Information Storage and Retrieval”, Wiley
References:
1. Richard Barker and Paul Massiglia, “ Storage Area Network Essentials: A Complete
Guide to Understanding and Implementing SANs” , Wiley.
2. Robert Spalding, “ Storage Networks: The Complete Reference”, Tata McGraw Hill
3. W. Curtis Preston, “Using SANs and NAS”, O’Reilly

BIG DATA ANALYTICS

Introduction to Big Introduction to Big Data, Big Data characteristics, types From 03
Data of Big Data, Traditional vs. Big Data business approach, Ref.
Case Study of Big Data Solutions. Books
2 Introduction to What is Hadoop? Core Hadoop Components; Hadoop Hadoop 02
Hadoop Ecosystem; Physical Architecture; Hadoop limitations. in
Practise
Chapter 1
3 NoSQL 1. What is NoSQL? NoSQL business drivers; No-SQL 04
NoSQL case studies; book
2. NoSQL data architecture patterns: Key-value stores,
Graph stores, Column family (Bigtable) stores,
Document stores, Variations of NoSQL
architectural patterns;
3. Using NoSQL to manage big data: What is a big
data NoSQL solution? Understanding the types of
big data problems; Analyzing big data with a
shared-nothing architecture; Choosing distribution
models: master-slave versus peer-to-peer; Four
ways that NoSQL systems handle big data problems
4 MapReduce and Distributed File Systems : Physical Organization of Text 06
the New Software Compute Nodes, Large-Scale File-System Organization. Book 1
Stack MapReduce: The Map Tasks, Grouping by Key, The
Reduce Tasks, Combiners, Details of MapReduce
Execution, Coping With Node Failures.
Algorithms Using MapReduce:
Matrix-Vector Multiplication by MapReduce ,
Relational-Algebra Operations, Computing Selections
by MapReduce,
Computing Projections by MapReduce, Union,
Intersection, and Difference by MapReduce, Computing
Natural Join by MapReduce, Grouping and Aggregation
by MapReduce, Matrix Multiplication, Matrix
Multiplication with One MapReduce Step.
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5 Finding Similar Applications of Near-Neighbor Search, Jaccard Text 03
Items Similarity of Sets, Similarity of Documents, Book 1
Collaborative Filtering as a Similar-Sets Problem .
Distance Measures: Definition of a Distance Measure ,
Euclidean Distances, Jaccard Distance, Cosine Distance,
Edit Distance, Hamming Distance.
6 Mining Data The Stream Data Model: A Data-Stream-Management Text 06
Streams System, Examples of Stream Sources, Stream Querie, Book 1
Issues in Stream Processing.
Sampling Data in a Stream : Obtaining a
Representative Sample , The General Sampling
Problem, Varying the Sample Size.
Filtering Streams:
The Bloom Filter, Analysis.
Counting Distinct Elements in a Stream
The Count-Distinct Problem, The Flajolet-Martin
Algorithm, Combining Estimates, Space Requirements
.
Counting Ones in a Window:
The Cost of Exact Counts, The Datar-Gionis-IndykMotwani
Algorithm, Query Answering in the DGIM
Algorithm, Decaying Windows.
7 Link Analysis PageRank Definition, Structure of the web, dead ends, Text 05
Using Page rank in a search engine, Efficient Book 1
computation of Page Rank: PageRank Iteration Using
MapReduce, Use of Combiners to Consolidate the
Result Vector.
Topic sensitive Page Rank, link Spam, Hubs and
Authorities.
8 Frequent Itemsets Handling Larger Datasets in Main Memory Text 05
Algorithm of Park, Chen, and Yu, The Multistage Book 1
Algorithm, The Multihash Algorithm.
The SON Algorithm and MapReduce
Counting Frequent Items in a Stream
Sampling Methods for Streams, Frequent Itemsets in
Decaying Windows
9 Clustering CURE Algorithm, Stream-Computing , A Stream- Text 05
Clustering Algorithm, Initializing & Merging Buckets,
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Answering Queries Book 1
10 Recommendation A Model for Recommendation Systems, Content-Based Text 04
Systems Recommendations, Collaborative Filtering. Book 1
11 Mining Social- Social Networks as Graphs, Clustering of Social- Text 05
Network Graphs Network Graphs, Direct Discovery of Communities, Book 1
SimRank, Counting triangles using Map-Reduce
Text Books:
1. Anand Rajaraman and Jeff Ullman “Mining of Massive Datasets”, Cambridge
University Press,
2. Alex Holmes “Hadoop in Practice”, Manning Press, Dreamtech Press.
3. Dan McCreary and Ann Kelly “Making Sense of NoSQL” – A guide for managers and
the rest of us, Manning Press.

COMPUTER SIMULATION AND MODELING

UNIT – I Introduction to Simulation.
Introduction to Simulation Examples.
simulation
General Principles 15
2 UNIT – II
Mathematical & Statistical Models in simulation.
Statistical Models
Queuing Models 8 in Simulation
3 UNIT – III Random Number Generation.
Random Numbers Testing random numbers (Refer to Third edition)
Random Variate Generation: Inverse transform 9
technique, Direct Transformation for the Normal
Distribution, Convolution Method, AcceptanceRejection
Technique (only Poisson Distribution).
4 UNIT – IV Input Modeling
Analysis of Verification, Calibration and Validation of Simulation
simulation data Models
12
Estimation of absolute performance.
Case study
5 UNIT V
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Application ? Processor and Memory simulation 4
? Manufacturing & Material handling
Text Books:
Discrete Event System Simulation; Third Edition, Jerry Banks, John Carson, Barry Nelson, and
David M. Nicol, Prentice-Hall
Discrete Event System Simulation; Fifth Edition, Jerry Banks, John Carson, Barry Nelson, and
David M. Nicol, Prentice-Hall
References:
1. System Modeling & Analysis; Averill M Law, 4th Edition TMH.
2. Principles of Modeling and Simulation; Banks C M , Sokolowski J A; Wiley
3. System Simulation ; Geoffrey Gordon ; EEE
4. System Simulation with Digital Computer; Narsing Deo, PHI

 

ENTERPRISE RESOURCE PLANNING

Introduction to Enterprise – An Overview 04
ERP Integrated Management Information, Business
Modeling, Integrated Data Model
2. ERP and Related Business Processing Reengineering(BPR), Data 06
Technologies Warehousing, Data Mining,
On-line Analytical Processing(OLAP), Supply Chain
Management (SCM),
Customer Relationship Management(CRM), MIS –
Management Information
System, DSS – Decision Support System, EIS –
Executive Information System
3. ERP MRP – Material Requirement Planning, BOM – Bill Of 06
Manufacturing Material, MRP –
Perspective Manufacturing Resource Planning, DRP – Distributed
Requirement Planning,
PDM – Product Data Management
4. ERP Modules Finance, Plant Maintenance, Quality Management, 06
Materials Management
5. Benefits of ERP Reduction of Lead-Time, On-time Shipment, Reduction 06
in Cycle Time, Improved Resource Utilization, Better
Customer Satisfaction, Improved Supplier Performance,
Increased Flexibility, Reduced Quality, Costs, Improved
Information Accuracy and Design-making Capability
6. ERP Pre-evaluation Screening, Package Evaluation, Project 06
Implementation Planning Phase, Gap Analysis, Reengineering,
Lifecycle Configuration, Implementation Team Training,
Testing, Going Live, End-user Training, Postimplementation
(Maintenance mode)
7. ERP case Studies E-Commerce to E-business 06
E-Business structural transformation, Flexible Business
Design, Customer Experience, Create the new techo
enterprise, New generation e-business leaders, memo to
CEO, Empower your customer, Integrate Sales and
Service, Integrated Enterprise applications
8. E-Business Enterprise resource planning the E-business Backbone 08
Enterprise architecture, planning, ERP usage in Real
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Architecture world, ERP Implementation, Future of ERP
applications, memo to CEO ,E-Procurement, EGovernance,
Developing the E-Business Design
9. Introduction to JD Edwards-Enterprise One 04
ERP tools Microsoft Dynamics-CRM Module
Text Books:
1. Enterprise Resource Planning – Alexis Leon, Tata McGraw Hill.
2. Enterprise Resource Planning – Diversified by Alexis Leon, TMH.
3. Enterprise Resource Planning – Ravi Shankar & S. Jaiswal , Galgotia

WIRELES SENSOR NETWORKS

Overview and Background of Sensor Network Technology; Types of 6
Introduction of Application; Challenges for WSNs: Characteristics
Wireless Sensor requirements, Required mechanism; Basic Sensor
Network Network Architectural Elements; Sensor Network
scenarios: Types of sources and sinks, single-hop versus
multi hop networks, Multiple sinks and sources, three
types of mobility; Some examples of sensor nodes:
Mica Mote family, EYES nodes, BT nodes.
2. Applications of Category 1(C1WSNs), Category 2(C2WSNs), Range of 4
Wireless Sensor Applications, Examples of Category 1 WSN (C1WSNs)
Network Applications, and Examples of Category 2
WSN(C2WSNs) Applications.
3. MAC Protocols Fundamentals of (wireless) MAC protocols, 9
Requirements and design considerations for MAC
Protocols in WSN, Low duty cycle protocols and
wakeup concepts, STEM,S-MAC, Mediation device
protocol, Wakeup radio concepts, Contention- based
protocols, CSMA protocols, PAMAS, Schedule-based
protocols, LEACH, SMACS, Traffic-adaptive medium
access protocol(TRAMA),IEEE 802.15.4 MAC
protocol, Slotted CSMA-CA protocol
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4. Network and Network layer : 7
Transport layer Data Dissemination and Gathering, Routing Challenges
Protocol. and Design Issues, Routing Strategies: Flooding and it’s
variants, Power-Efficient Gathering in Sensor
Information Systems, Geographical routing,
Transport layer :
Transport protocol Design issues, Examples of Existing
Transport Control Protocols: CODA, ESRT, RMST,
PSFQ, GARUDA, ATP; Performance of Transport
Control Protocols :Congestion, packet loss recovery.
5. Operating Systems Operating System Design Issues, Examples of 7
, Performance and Operating Systems: TinyOS, Mate, MagnetOS,
Traffic MANTIS,OSPM,EYES OS, SenOS, EMERALDS,
PicOS , WSN Design Issues, Management Performance Modeling of WSNs
Issues
6. WSN standards Wireless sensor network standards-IEEE 802.15.4 Low 6
and Future trends rate WPAN standard, The ZIGBEE alliance etc. Future
in wireless sensor trends in wireless sensor networks: Wireless Multimedia
Sensor Networks, Sensor Network Applications in networks Challenging Environments.
7 Security Fundamentals of Network Security ,Challenges of 9
Security in Wireless Sensor Networks, Security Attacks
in Sensor Networks, Protocols and Mechanisms for
Security, IEEE 802.15.4 and ZigBee Security
Text Books:
1. HOLGER KARL,ANDREAS WILLIG., “Protocols, and Architectures: For Wireless
Sensor Networks”, Wiley Student Edition
2. Kazem Sohraby, Daniel Minoli, Taieb Znati., “Wireless Sensor Networks: Technology,
Protocols, and Applications”, Wiley Student Edition.
3. Waltenegus Dargie and Christian Poellabauer., “Fundamentals of Wireless Sensor NetworksTheory
& Practice”, John Wiley publication, 2010.
4. J. Zheng and A. Jamalipour, “Wireless Sensor Networks : A Networking Perspective “ John
Wiley publication,2009

GEOGRAPHICAL INFORMATION SYSTEMS

Fundamentals of GIS 06
1.1 Introduction, Definition of GIS, Evolution of GIS ,
components of GIS,
1.2 Geospatial Data, Geographic Coordinate System,
Map Projections, Commonly Used Map Projections, UTM
grid system, Map Scale
1.3 Cartographic Symbolization, Types of Maps, Typography,
Map Design, Map Production
2.0 Data Management, Models and Quality Issues 06
2.1 Vector Model : Topology, Non topological Vector models,
Attribute Data in GIS, Attribute Data Entry, Vector Data
Query, Manipulation of Fields and Attribute Data
2.2 Raster Data Model : Elements of Raster Data Model, Types
of Raster Data, Raster Data Structure, Raster Data Query,
Data Compression, Data Conversion, Integration of Raster
and Vector data
2.3 Data input and editing, Data quality Issues: Accuracy,
Consistency, Precision and Resolution, Completeness;
sources of error in GIS
3.0 GIS Data Exploration Analysis and Visualization 2+2+4+4=12
3.1 Data exploration: Descriptive statistics, Graphs, Dynamic
Graphics
3.2 Vector Data Analysis: Buffering, Overlay, Distance
Measurement, Pattern Analysis, Map Manipulation
3.3 Raster Data Analysis: Local Operations, Neighborhood
Operations, Zonal Operations, Data Extraction, Data
Generalization, Comparison of Vector and Raster Based
Data
3.4 Spatial Interpolation: Elements of Spatial Interpolation,
Global methods, Local Methods, Kriging, Comparison of
Spatial Interpolation Methods
4.0 Terrain mapping, Geocoding and Segmentation 04
4.1 Terrain Mapping and Analysis: Data for Terrain Mapping
and Analysis: DIM, TIN, Terrain Mapping, Slope and
Aspect, Surface Curvature, Raster versus TIN
4.2 Geocoding and Dynamic Segmentation: Geocoding,
Applications of Geocoding, Dynamic Segmentation,
Applications of Dynamic Segmentation
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5.0 Remote Sensing Fundamentals 12
5.1 Remote Sensing: Basic Principles, Electromagnetic
Remote Sensing, Energy Sources, Energy Interactions with
Surface Materials, , Energy Interactions with Earth’s
Atmosphere, Spectral Reflectance Curves
5.2 Microwave Remote Sensing, The Radar Principle, Factors
Affecting Microwave Measurements, Radar Wavebands,
SLAR Systems, SAR, Interpreting SAR Images,
Geometrical Characteristics, Remote Sensing, Platform and
Sensors, Satellite System Parameters, Sensor Parameters,
Imaging Sensor Systems, Earth Resources Satellites,
Meteorological Satellites. Data Formats, Standard Products
5.3 Visual Image Interpretation: Information Extraction By
human and Computer, Remote sensing Data Products,
Image Interpretation, Elements of Image Interpretation
6.0 Project Management 04
6.1 Planning of Project , Implementation of Project,
Management of Project, Case study
7.0 Modern trends and Applications of GIS 04
7.1 Multimedia GIS, Internet GIS, Mobile GIS ,Applications of
GIS in Urban and municipal area

 

ROBOTICS

1. Fundamentals Robot Classification, Robot 03 Hrs Chapter 1 –
Components, Degrees of freedom, Text Book 1
Joints, Coordinates, Coordinate
frames, workspace, applications
2. Kinematics of Homogeneous transformation 07 Hrs Chapter 2 –
Robots matrices, Inverse transformation Text Book 1
matrices, Forward and inverse
kinematic equations – position and
orientation, Denavit-Hatenberg
representation of forward
kinematics, Inverse kinematic
solutions, Case studies
3. Differential motions Differential relationship, Jacobian, 06 Hrs Chapter 3 –
and velocities Differential motion of a frame and Text Book 1
robot, Inverse Jacobian
4. Dynamic Analysis of Lagrangian mechanics, Moments of 07 Hrs Chapter 4 –
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Forces Inertia, Dynamic equations of robots, Text Book 1
Transformation of forces and
moment between coordinate frames
5. Trajectory Planning Trajectory planning, Joint-space 07 Hrs Chapter 5 –
trajectory planning, Cartesian-space Text Book 1
trajectories
6. Mobile Robot Concept of motion planning, Bug 04 Hrs Chapter 2 –
Motion Planning Algorithms – Bug1, Bug2, Tangent Text Book 2
Bug
7. Potential Functions Attractive/Repulsive potential, 08 Hrs Chapter 4 &
and Visibility Gradient descent, wave-front 5 – Text
Graphs planner, navigation potential Book 2
functions, Visibility map,
Generalized Voronoi diagrams and
graphs, Silhouette methods
8. Coverage Planning Cell Decomposition, Localization 06 Hrs Chapter 6, 9
and Mapping

SOFT COMPUTING

Introduction to Soft Fuzzy logic: Definition, Applications. Hybrid System: 2
Computing Definition, Types of Hybrid Systems, Applications. Genetic
Algorithms: Definition, Applications.
Fundamental Concepts and Models of Artificial Neural
Systems: Biological Neurons and Their Artificial Models,
Models of Artificial Neural Networks, Neural Processing,
Learning and Adaptation, Neural Network Learning Rules and
Comparison. Linearly and Non-Linearly Separable Pattern
2 Neural Networks Classification. Perceptron Convergence Theorem. Multi-layer 20 Feedforward Network: Delta Learning Rule for
Multiperceptron Layer, Generalized Delta Learning Rule,
Feedforward Recall and Error Back-propagation Training,
LearningFactors,CharacterRecognitionApplication.
Associative Memory: Hopfield Network, Bidirectional
Associative Memory. Radial Basis Function Networks.
Brief Review of Conventional Set Theory, Introduction to Fuzzy
Sets, Properties of Fuzzy Sets, Operations on Fuzzy Sets,
Membership Functions.Fuzzy Extension Principle, Fuzzy
3 Fuzzy Set Theory Relations, Projection and Cylindrical Extension of Fuzzy 16 Relations, Fuzzy Max-Min and Max-Product Composition. Fuzzy
Knowledge Based Systems with Applications, Defuzzification
Methods, Fuzzy Composition Rules, Architecture of Mamdani
Type Fuzzy Control Systems.
4 Hybrid Systems ANFIS: Adaptive Neuro-Fuzzy Inference Systems: Introduction, 4
ANFIS Architecture, and Hybrid Learning Algorithm.
What are Genetic Algorithms? Why Genetic Algorithms?
Biological Background: The Cell, Chromosomes, Genetics,
Reproduction, Neural Selection, Traditional Optimization and
5 Genetic Algorithms Search Techniques, Genetic Algorithm and Search space: Simple 6
GA, General GA, Operators in GA, Encoding, Selection,
Crossover, Mutation, Stopping Condition for GA flow,
Constraints in GA, Problem solving using GA, Classification of
GA.

SOFTWARE TESTING AND QA

Unit-I Testing Introduction, Goals of Software Testing, Software Testing 10
Methodology Definitions, Model for Software Testing, Effective Software
Testing vs Exhaustive Software Testing, Software Failure
Case Studies, Software Testing Terminology, Software
Testing Life Cycle (STLC), Software Testing methodology,
Verification and Validation, Verification requirements,
Verification of high level design, Verification of low level
design, validation.
Unit II Testing Dynamic Testing : Black Box testing: boundary value 12
Techniques analysis, equivalence class testing, state table based testing,
cause-effect graphing based testing, error guessing.
White box Testing Techniques: need, logic coverage
criteria, basis path testing, graph matrices, loop testing, data
flow testing, mutation testing. Static Testing.
Validation Activities: Unit validation, Integration,
Function, System, Acceptance Testing.
Regression Testing: Progressive vs. Regressive, regression
testing produces quality software, regression testability,
objectives of regression testing, regression testing types,
define problem, regression testing techniques.
Unit III Test Management: test organization, structure and of testing 10
Managing the group, test planning, detailed test design and test
Test Process specification.
Software Metrics: need, definition and classification of
software matrices.
Testing Metrics for Monitoring and Controlling the Testing
Process: attributes and corresponding matrics, estimation
model for testing effort, architectural design, information
flow matrix used for testing, function point and test point
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analysis.
Efficient Test Suite Management: minimizing the test suite
and its benefits, test suite minimization problem, test suite
prioritization its type , techniques and measuring
effectiveness.
Unit IV Test Automation and Testing Tools: need, categorization, 8
Automation selection and cost in testing tool, guidelines for testing
tools. Study of testing tools: WinRunner, QTP,
LoadRunner, TestDirector and IBM Rational Functional
Tester, Selenium etc.
Unit V Testing Testing Object Oriented Software: OOT basics, Object- 5
for Specialized oriented testing.
Environment
Testing Web based Systems: Web based system, web
technology evaluation, traditional software and web based
software, challenges in testing for web based software,
testing web based testing, Testing a data warehouse
Unit VI Quality Software Quality Management, McCall’s quality factors 3
Management and Criteria, ISO 9126 quality characteristics, ISO
9000:2000,software quality management