INTERNET OF THINGS TECHNOLOGY [As per Choice Based Credit System (CBCS) scheme] (Effective from the academic year 2016 -2017) SEMESTER – VIII IA Marks 15CS81

20

Number of Lecture Hours/Week

04

Exam Marks

80

Total Number of Lecture Hours

50

Exam Hours

03

CREDITS – 04 Course Objectives:This course will enable students to • • • • •

Assess the genesis and impact of IoT applications, architectures in real world. Illustrate diverse methods of deploying smart objects and connect them to network. Compare different Application protocols for IoT. Infer the role of Data Analytics and Security in IoT. Identifysensor technologies for sensing real world entities and understand the role of IoT in various domains of Industry. Module – 1 Teaching Hours What is IoT, Genesis of IoT, IoT and Digitization, IoT Impact, Convergence of IT and IoT, IoT Challenges, IoT Network Architecture and Design, Drivers Behind New Network Architectures, Comparing IoT Architectures, A Simplified IoT Architecture, The Core IoT Functional Stack, IoT Data Management and Compute Stack.

10 Hours

Module – 2 Smart Objects: The “Things” in IoT, Sensors, Actuators, and Smart Objects, Sensor Networks, Connecting Smart Objects, Communications Criteria, IoT Access Technologies.

10 Hours

Module – 3 IP as the IoT Network Layer, The Business Case for IP, The need for Optimization, Optimizing IP for IoT, Profiles and Compliances, Application Protocols for IoT, The Transport Layer, IoT Application Transport Methods.

10 Hours

Module – 4 Data and Analytics for IoT, An Introduction to Data Analytics for IoT, Machine Learning, Big Data Analytics Tools and Technology, Edge Streaming Analytics, Network Analytics, Securing IoT, A Brief History of OT Security, Common Challenges in OT Security, How IT and OT Security Practices and Systems Vary, Formal Risk Analysis Structures: OCTAVE and FAIR, The Phased Application of Security in an Operational Environment

10 Hours

Module – 5 IoT Physical Devices and Endpoints - Arduino UNO: Introduction to Arduino, Arduino UNO, Installing the Software, Fundamentals of Arduino Programming. IoT Physical Devices and Endpoints - RaspberryPi: Introduction to RaspberryPi, About the RaspberryPi Board: Hardware Layout, Operating Systems on RaspberryPi, Configuring RaspberryPi, Programming RaspberryPi with Python, Wireless Temperature Monitoring System Using Pi, DS18B20 Temperature Sensor, Connecting Raspberry Pi via SSH, Accessing Temperature from DS18B20 sensors, Remote access to RaspberryPi, Smart and Connected Cities, An IoT Strategy for Smarter Cities, Smart City IoT Architecture,

10 Hours

Smart City Security Architecture, Smart City Use-Case Examples. Course Outcomes:After studying this course, students will be able to •

Interpret the impact and challenges posed by IoT networks leading to new architectural models. • Compare and contrast the deployment of smart objects and the technologies to connect them to network. • Appraise the role of IoT protocols for efficient network communication. • Elaborate the need for Data Analytics and Security in IoT. • Illustrate different sensor technologies for sensing real world entities and identify the applications of IoT in Industry. Question paper pattern: The question paper will have ten questions. There will be 2 questions from each module. Each question will have questions covering all the topics under a module. The students will have to answer 5 full questions, selecting one full question from each module. Text Books: 1. David Hanes, Gonzalo Salgueiro, Patrick Grossetete, Robert Barton, Jerome Henry,"IoT Fundamentals: Networking Technologies, Protocols, and Use Cases for the Internet of Things”, 1stEdition, Pearson Education (Cisco Press Indian Reprint). (ISBN: 9789386873743) 2. Srinivasa K G, “Internet of Things”,CENGAGE Leaning India, 2017 Reference Books: 1. Vijay Madisetti and ArshdeepBahga, “Internet of Things (A Hands-on-Approach)”, 1stEdition, VPT, 2014. (ISBN: 978-8173719547) 2. Raj Kamal, “Internet of Things: Architecture and Design Principles”, 1st Edition, McGraw Hill Education, 2017. (ISBN: 978-9352605224)

BIG DATA ANALYTICS [As per Choice Based Credit System (CBCS) scheme] (Effective from the academic year 2016 -2017) SEMESTER – VIII Subject Code 15CS82 IA Marks 20 Number of Lecture Hours/Week 4 Exam Marks 80 Total Number of Lecture Hours 50 Exam Hours 03 CREDITS – 04 Course objectives: This course will enable students to • Understand Hadoop Distributed File system and examine MapReduce Programming • Explore Hadoop tools and manage Hadoop with Ambari • Appraise the role of Business intelligence and its applications across industries • Assess core data mining techniques for data analytics • Identify various Text Mining techniques Module – 1 Teaching Hours Hadoop Distributed File System Basics, Running Example Programs and 10 Hours Benchmarks, Hadoop MapReduce Framework, MapReduce Programming Module – 2 Essential Hadoop Tools, Hadoop YARN Applications, Managing Hadoop with 10 Hours Apache Ambari, Basic Hadoop Administration Procedures Module – 3 Business Intelligence Concepts and Application, Data Warehousing, Data 10 Hours Mining, Data Visualization Module – 4 Decision Trees, Regression, Artificial Neural Networks, Cluster Analysis, 10 Hours Association Rule Mining Module – 5 Text Mining, Naïve-Bayes Analysis, Support Vector Machines, Web Mining, 10 Hours Social Network Analysis Course outcomes: The students should be able to: • Master the concepts of HDFS and MapReduce framework • Investigate Hadoop related tools for Big Data Analytics and perform basic Hadoop Administration • Recognize the role of Business Intelligence, Data warehousing and Visualization in decision making • Infer the importance of core data mining techniques for data analytics • Compare and contrast different Text Mining Techniques Question paper pattern: The question paper will have ten questions. There will be 2 questions from each module. Each question will have questions covering all the topics under a module. The students will have to answer 5 full questions, selecting one full question from each module. Text Books: 1. Douglas Eadline,"Hadoop 2 Quick-Start Guide: Learn the Essentials of Big Data Computing in the Apache Hadoop 2 Ecosystem", 1stEdition, Pearson Education, 2016. ISBN-13: 978-9332570351

2. Anil Maheshwari, “Data Analytics”, 1st Edition, McGraw Hill Education, 2017. ISBN-13: 978-9352604180 Reference Books: 1) Tom White, “Hadoop: The Definitive Guide”, 4th Edition, O’Reilly Media, 2015.ISBN-13: 978-9352130672 2) Boris Lublinsky, Kevin T.Smith, Alexey Yakubovich,"Professional Hadoop Solutions", 1stEdition, Wrox Press, 2014ISBN-13: 978-8126551071 3) Eric Sammer,"Hadoop Operations: A Guide for Developers and Administrators",1stEdition, O'Reilly Media, 2012.ISBN-13: 978-9350239261

HIGH PERFORMANCE COMPUTING [As per Choice Based Credit System (CBCS) scheme] (Effective from the academic year 2016 -2017) SEMESTER – VIII Subject Code 15CS831 IA Marks 20 Number of Lecture Hours/Week 3 Exam Marks 80 Total Number of Lecture Hours 40 Exam Hours 03 CREDITS – 03 Course objectives: This course will enable students to • Introduce students the design, analysis, and implementation, of high performance computational science and engineering applications. • Illustrate on advanced computer architectures, parallel algorithms, parallel languages, and performance-oriented computing. Module – 1 Teaching Hours Introduction: Computational Science and Engineering: Computational 10 Hours Science and Engineering Applications; characteristics and requirements, Review of Computational Complexity, Performance: metrics and measurements, Granularity and Partitioning, Locality: temporal/spatial/stream/kernel, Basic methods for parallel programming, Real-world case studies (drawn from multiscale, multi-discipline applications) Module – 2 High-End Computer Systems : Memory Hierarchies, Multi-core Processors: 10 Hours Homogeneous and Heterogeneous, Shared-memory Symmetric Multiprocessors, Vector Computers, Distributed Memory Computers, Supercomputers and Petascale Systems, Application Accelerators / Reconfigurable Computing, Novel computers: Stream, multithreaded, and purpose-built Module – 3 Parallel Algorithms: Parallel models: ideal and real frameworks, Basic 10 Hours Techniques: Balanced Trees, Pointer Jumping, Divide and Conquer, Partitioning, Regular Algorithms: Matrix operations and Linear Algebra, Irregular Algorithms: Lists, Trees, Graphs, Randomization: Parallel Pseudo-Random Number Generators, Sorting, Monte Carlo techniques Module – 4 Parallel Programming: Revealing concurrency in applications, Task and 10 Hours Functional Parallelism, Task Scheduling, Synchronization Methods, Parallel Primitives (collective operations), SPMD Programming (threads, OpenMP, MPI), I/O and File Systems, Parallel Matlabs (Parallel Matlab, Star-P, Matlab MPI), Partitioning Global Address Space (PGAS) languages (UPC, Titanium, Global Arrays) Module – 5 Achieving Performance: Measuring performance, Identifying performance 10 Hours bottlenecks, Restructuring applications for deep memory hierarchies, Partitioning applications for heterogeneous resources, using existing libraries, tools, and frameworks Course outcomes: The students should be able to: • Illustrate the key factors affecting performance of CSE applications, and • Make mapping of applications to high-performance computing systems, and

•

Apply hardware/software co-design for achieving performance on real-world applications Question paper pattern: The question paper will have ten questions. There will be 2 questions from each module. Each question will have questions covering all the topics under a module. The students will have to answer 5 full questions, selecting one full question from each module. Text Books: 1. Introduction to Parallel Computing, AnanthGrama, Anshul Gupta, George Karypis, and Vipin Kumar, 2nd edition, Addison-Welsey, 2003. 2. Petascale Computing: Algorithms and Applications, David A. Bader (Ed.), Chapman & Hall/CRC Computational Science Series, 2007 Reference Books: 1. Grama, A. Gupta, G. Karypis, V. Kumar, An Introduction to Parallel Computing, Design and Analysis of Algorithms: 2/e, Addison-Wesley, 2003. 2. G.E. Karniadakis, R.M. Kirby II, Parallel Scientific Computing in C++ and MPI: A Seamless Approach to Parallel Algorithms and their Implementation, Cambridge University Press,2003. 3. Wilkinson and M. Allen, Parallel Programming: Techniques and Applications Using Networked Workstations and Parallel Computers, 2/E, Prentice Hall, 2005. 4. M.J. Quinn, Parallel Programming in C with MPI and OpenMP, McGraw-Hill, 2004. 5. G.S. Almasi and A. Gottlieb, Highly Parallel Computing, 2/E, Addison-Wesley, 1994. 6. David Culler Jaswinder Pal Singh,"Parallel Computer Architecture: A hardware/Software Approach", Morgan Kaufmann, 1999. 7. Kai Hwang, "Scalable Parallel Computing", McGraw Hill 1998.

USER INTERFACE DESIGN [As per Choice Based Credit System (CBCS) scheme] (Effective from the academic year 2016 -2017) SEMESTER – VIII Subject Code 15CS832 IA Marks 20 Number of Lecture Hours/Week 3 Exam Marks 80 Total Number of Lecture Hours 40 Exam Hours 03 CREDITS – 03 Course objectives: This course will enable students to • To study the concept of menus, windows, interfaces • To study about business functions • To study the characteristics and components of windows andthe various controls for the windows. • To study about various problems in windows design with color, text, graphics. • To study the testing methods Module – 1 Teaching Hours Introduction-Importance-Human-Computer interface-characteristics of graphics 10 Hours interface-Direct manipulation graphical system - web user interface-popularitycharacteristic & principles. Module – 2 User interface design process- obstacles-usability-human characteristics in design 10 Hours - Human interaction speed-business functions-requirement analysis-DirectIndirect methods-basic business functions-Design standards-system timings Human consideration in screen design - structures of menus - functions of menus-contents of menu-formatting -phrasing the menu - selecting menu choicenavigating menus-graphical menus. Module – 3 Windows: Characteristics-components-presentation styles-types-managements- 10 Hours organizations-operations-web systems-device-based controls: characteristicsScreen -based controls: operate control - text boxes-selection controlcombination control-custom control-presentation control. Module – 4 Text for web pages - effective feedback-guidance & assistance- 10 Hours Internationalization-accessibility -Icons-Image-Multimedia-coloring. Module – 5 Windows layout-test :prototypes - kinds of tests - retest - Information search - 10 Hours visualization - Hypermedia - www - Software tools. Course outcomes: The students should be able to: • Design the user interface, design, menu creation and windows creation and connection between menu and windows Question paper pattern: The question paper will have ten questions. There will be 2 questions from each module. Each question will have questions covering all the topics under a module. The students will have to answer 5 full questions, selecting one full question from each module. Text Books: 1. Wilbent. O. Galitz ,"The Essential Guide to User Interface Design", John Wiley&

Sons, 2001. Reference Books: 1. Ben Sheiderman, "Design the User Interface", Pearson Education, 1998. 2. Alan Cooper, "The Essential of User Interface Design", Wiley - Dream Tech Ltd., 2002.

VIRTUAL REALITY [As per Choice Based Credit System (CBCS) scheme] (Effective from the academic year 2016 -2017) SEMESTER – VIII Subject Code 15IS833 IA Marks 20 Number of Lecture Hours/Week 3 Exam Marks 80 Total Number of Lecture Hours 40 Exam Hours 03 CREDITS – 03 Course objectives: This course will enable students to • Explain understanding of this technology, underlying principles, its potential and limits and to learn about the criteria for defining useful applications. • Illustrate process of creating virtual environments Module – 1 Teaching Hours Introduction : The three I’s of virtual reality, commercial VR technology and the 10 Hours five classic components of a VR system. Input Devices : (Trackers, Navigation, and Gesture Interfaces): Threedimensional position trackers, navigation and manipulation, interfaces and gesture interfaces. Text book1: 1.1, 1.3, 1.5, 2.1, 2.2 and 2.3 Module – 2 Output Devices: Graphics displays, sound displays & haptic feedback. 10 Hours Text book1: 3.1,3.2 and 3.3 Module – 3 Modeling : Geometric modeling, kinematics modeling, physical modeling, 10 Hours behaviour modeling, model management. Text book1: 5.1, 5.2 and 5.3, 5.4 and 5.5 Module – 4 Human Factors: Methodology and terminology, user performance studies, VR 10 Hours health and safety issues. Text book1: 7.1, 7.2 and 7.3 Module – 5 Applications: Medical applications, military applications, robotics applications. 10 Hours Text book1: 8.1, 8.3 and 9.2 Course outcomes: The students should be able to: • Illustrate technology, underlying principles, its potential and limits and to learn about the criteria for defining useful applications. • Explain process of creating virtual environments Question paper pattern: The question paper will have ten questions. There will be 2 questions from each module. Each question will have questions covering all the topics under a module. The students will have to answer 5 full questions, selecting one full question from each module. Text Books: 1. Virtual Reality Technology, Second Edition, Gregory C. Burdea & Philippe Coiffet, John Wiley & Sons Reference Books:

SYSTEM MODELLING AND SIMULATION [As per Choice Based Credit System (CBCS) scheme] (Effective from the academic year 2016 -2017) SEMESTER – VIII Subject Code 15CS834 IA Marks 20 Number of Lecture Hours/Week 3 Exam Marks 80 Total Number of Lecture Hours 40 Exam Hours 03 CREDITS – 03 Course objectives: This course will enable students to • Explain the basic system concept and definitions of system; • Discuss techniques to model and to simulate various systems; • Analyze a system and to make use of the information to improve the performance. Module – 1 Teaching Hours Introduction: When simulation is the appropriate tool and when it is not 10 Hours appropriate, Advantages and disadvantages of Simulation; Areas of application, Systems and system environment; Components of a system; Discrete and continuous systems, Model of a system; Types of Models, Discrete-Event System Simulation Simulation examples: Simulation of queuing systems. General Principles, Simulation Software:Concepts in Discrete-Event Simulation. The Event-Scheduling / Time-Advance Algorithm, Manual simulation Using Event Scheduling Module – 2 Statistical Models in Simulation :Review of terminology and concepts, Useful 10 Hours statistical models,Discrete distributions. Continuous distributions,Poisson process, Empirical distributions. Queuing Models:Characteristics of queuing systems,Queuing notation,Long-run measures of performance of queuing systems,Long-run measures of performance of queuing systems cont…,Steady-state behavior of M/G/1 queue, Networks of queues, Module – 3 Random-NumberGeneration:Properties of random numbers; Generation of 10 Hours pseudo-random numbers, Techniques for generating random numbers,Tests for Random Numbers, Random-Variate Generation: ,Inverse transform technique Acceptance-Rejection technique. Module – 4 Input Modeling: Data Collection; Identifying the distribution with data, 10 Hours Parameter estimation, Goodness of Fit Tests, Fitting a non-stationary Poisson process, Selecting input models without data, Multivariate and Time-Series input models. Estimation of Absolute Performance: Types of simulations with respect to output analysis ,Stochastic nature of output data, Measures of performance and their estimation, Contd.. Module – 5 Measures of performance and their estimation,Output analysis for terminating 10 Hours simulations Continued..,Output analysis for steady-state simulations. Verification, Calibration And Validation: Optimization: Model building, verification and validation, Verification of simulation models, Verification of

simulation models,Calibration and validation of models, Optimization via Simulation. Course outcomes: The students should be able to: • Explain the system concept and apply functional modeling method to model the activities of a static system • Describe the behavior of a dynamic system and create an analogous model for a dynamic system; • Simulate the operation of a dynamic system and make improvement according to the simulation results. Question paper pattern: The question paper will have ten questions. There will be 2 questions from each module. Each question will have questions covering all the topics under a module. The students will have to answer 5 full questions, selecting one full question from each module. Text Books: 1. Jerry Banks, John S. Carson II, Barry L. Nelson, David M. Nicol: Discrete-Event System Simulation, 5 th Edition, Pearson Education, 2010. Reference Books: 1. Lawrence M. Leemis, Stephen K. Park: Discrete – Event Simulation: A First Course, Pearson Education, 2006. 2. Averill M. Law: Simulation Modeling and Analysis, 4 th Edition, Tata McGrawHill, 2007

INTERNSHIP / PROFESSIONAL PRACTISE [As per Choice Based Credit System (CBCS) scheme] (Effective from the academic year 2016 -2017) SEMESTER – VIII Subject Code 15CS84 IA Marks Duration 4 weeks Exam Marks Exam Hours CREDITS – 02 Course objectives: This course will enable students to Description (If any): Course outcomes: The students should be able to: Evaluation of Internship :

50 50 03

PROJECT WORK PHASE II [As per Choice Based Credit System (CBCS) scheme] (Effective from the academic year 2016 -2017) SEMESTER – VIII Subject Code 15CSP85 IA Marks Number of Lecture Hours/Week 06 Exam Marks Total Number of Lecture Hours -Exam Hours CREDITS – 05 Course objectives: This course will enable students to Description (If any): Course outcomes: The students should be able to: Conduction of Practical Examination:

100 100 03

SEMINAR [As per Choice Based Credit System (CBCS) scheme] (Effective from the academic year 2016 -2017) SEMESTER – VIII Subject Code 15CSS86 IA Marks Number of Lecture Hours/Week 04 Exam Marks Total Number of Lecture Hours -Exam Hours CREDITS – 02 Course objectives: This course will enable students to •

Description: •

Course outcomes: The students should be able to: •

Evaluation of seminar:

100 ---