Year II · Semester I
Master of Information Technology
Third Semester Syllabus
YearII
SemesterI
Total Credits14
Core courses
| Course code | Course name | Credit hours |
|---|---|---|
| MIT 211 | Intelligent Systems | 3 |
| MIT 212 | Distributed and Cloud Computing | 3 |
| MIT 213 | Entrepreneurship | 2 |
| MIT 214 | Networking with IPv6 | 3 |
| MIT 215 | Wireless Networking | 3 |
| Total | 14 | |
MIT 211: Intelligent Systems
Lecture30 hrs
Tutorial10 hrs
Practical20 hrs
Internal20 + 20
External60
Credits3
This course introduces the ideas and techniques underlying the principles and design of artificial intelligent systems. It covers the basics and applications of AI, including design of intelligent agents, problem solving, searching, knowledge representation systems, probabilistic reasoning, neural networks, machine learning, and natural language processing.
Course Objectives
- Learn about computer systems that exhibit intelligent behavior
- Design intelligent agents
- Identify AI problems and solve them
- Design knowledge representation and expert systems
- Design neural networks for solving problems
- Identify different machine learning paradigms
Course Contents
Unit I: Introduction 3 hrs
- Artificial Intelligence Overview:
- AI Perspectives: acting and thinking humanly, acting and thinking rationally
- History of AI
- Foundations of AI
- Applications of AI
Unit II: Intelligent Agents 4 hrs
- Agent Structure and Types:
- Introduction of agents, Structure of intelligent agent, Properties of intelligent agents
- Configuration of agents, PEAS description of agents
- Types of agents: Simple Reflexive, Model Based, Goal Based, Utility Based
- Environment types: Deterministic, Stochastic, Static, Dynamic, Observable, Semi-observable, Single Agent, Multi Agent
Unit III: Problem Solving by Searching 9 hrs
- Problem Formulation:
- Definition, problem as a state space search, problem formulation, well-defined problems
- Solving problems by searching, search strategies, performance evaluation of search techniques
- Uninformed Search Strategies:
- Depth First Search (DFS), Breadth First Search (BFS), Depth Limited Search, Iterative Deepening Search, Bidirectional Search
- Informed Search Strategies:
- Greedy Best First Search, A* Search, Hill Climbing, Simulated Annealing
- Game Playing & Constraint Satisfaction:
- Game playing, adversarial search techniques, Mini-max Search, Alpha-Beta Pruning, Constraint Satisfaction Problems and Search
Unit IV: Knowledge Representation 14 hrs
- Fundamentals of Knowledge Representation:
- Definition and importance of knowledge, Issues in knowledge representation, Properties of knowledge representation systems
- Structured Knowledge Representation Systems:
- Semantic Nets, Frames, Conceptual Dependencies, Scripts
- Unstructured Knowledge Representation Systems:
- Rule Based Systems, Propositional Logic, Predicate Logic
- Propositional Logic (PL):
- Syntax and Semantics, Formal logic-connectives, truth tables, tautology, validity, well-formed formulae, Inference using Resolution, Backward Chaining and Forward Chaining
- Predicate Logic (FOPL):
- Syntax and Semantics, Quantification, Inference with FOPL: converting into PL (Existential and Universal instantiation), Unification and lifting, inference using resolution
- Uncertain Knowledge:
- Knowledge representation in uncertain domain, Statistical reasoning using Probability, Bayes' Rule and its use, Bayesian/Causal/Belief networks, reasoning in belief networks, Fuzzy Logic
Unit V: Machine Learning 5 hrs
- Introduction to Machine Learning:
- Concepts of learning, importance of machine learning
- Learning from examples
- Explanation Based Learning
- Learning by Analogy
- Learning by simulating evolution — Genetic Algorithms
Unit VI: Learning with Neural Networks 5 hrs
- Artificial Neural Networks:
- Biological vs Artificial Neural Networks (ANN), Mathematical model of ANN
- Types of ANN: Feed-forward, Recurrent, Single Layered, Multi-Layered
- Applications of Artificial Neural Networks
- Learning in Neural Networks:
- Learning by training ANN, Supervised vs Unsupervised Learning, Hebbian Learning, Perceptron Learning, Back-propagation
Unit VII: Applications of AI 5 hrs
- Expert Systems & NLP:
- Expert systems, development of expert systems
- Natural Language Processing: Natural Language Understanding and Natural Language Generation
- Steps of Natural Language Processing
- Machine Vision Concepts
Laboratory Work
Students should write programs and prepare lab sheets for most units. Focus areas include design and implementation of intelligent agents and expert systems, various search techniques, Neural Networks, and Genetic Algorithms. Recommended languages: LISP, PROLOG, JAVA (or as decided by the instructor). Minimum 3 lab hours per week.
Prescribed Text
- Stuart Russel and Peter Norvig — Artificial Intelligence: A Modern Approach, Pearson
References
- George F. Luger — Artificial Intelligence: Structures and Strategies for Complex Problem Solving, Benjamin/Cummings
- E. Rich, K. Knight, Shivashankar B. Nair — Artificial Intelligence, Tata McGraw Hill
- D. W. Patterson — Artificial Intelligence and Expert Systems, Prentice Hall
- P. H. Winston — Artificial Intelligence, Addison Wesley
MIT 212: Distributed and Cloud Computing
Lecture50 hrs
Tutorial10 hrs
Practical20 hrs
Internal20
External60
Credits3
The objective of this course is to provide knowledge of distributed systems and cloud computing, cloud security, cloud computing platforms, and cloud for the enterprise as a service.
Course Contents
1. Distributed System Models and Enabling Technologies 5 hrs
- System Models & Environments:
- System models for distributed and cloud computing
- Software environments for distributed systems and cloud
- Performance, security and energy efficiency
2. Computer Clusters for Scalable Parallel Computing 4 hrs
- Clustering for massive parallelism
- Design principles of computer clusters
- Cluster job and resource management
3. Introduction to Cloud Computing 5 hrs
- Definition and characteristics
- Components
- Cloud providers
- Organizational scenarios of clouds
- Administering and monitoring cloud services
- Benefits and limitations
- Deploy applications over cloud
- Comparison among SaaS, PaaS, IaaS
- Cloud computing platforms and Infrastructure as a Service
4. Introduction to Cloud Technologies 5 hrs
- Virtualization & Multitenancy:
- Study of Hypervisors
- Compare SOAP and REST
- Web services, AJAX and mashups: SOAP vs REST, AJAX asynchronous rich interfaces, Mashups
- Virtual machine technology, virtualization applications in enterprises, pitfalls of virtualization
- Multitenant software: Multi-entity support, Multi-schema approach, Multi-tenancy using cloud data stores, Data access control for enterprise applications
5. Data in the Cloud 6 hrs
- Relational databases
- Map-Reduce and extensions: Parallel computing, the Map-Reduce model
- Parallel efficiency of Map-Reduce, Relational operations using Map-Reduce
- Enterprise batch processing using Map-Reduce
- Introduction to cloud development, Map-Reduce model
6. Cloud Security Fundamentals 10 hrs
- Security Architecture & Challenges:
- Vulnerability assessment tools for cloud
- Privacy and security in cloud
- Cloud computing security architecture: Architectural considerations, General Issues, Trusted Cloud computing
- Secure Execution Environments and Communications, Micro-architectures
- Identity Management and Access Control, Autonomic Security
- Operational Security Topics:
- Cloud computing security challenges: Virtualization security management, virtual threats, VM Security Recommendations
- Secure Execution Environments and Communications in cloud
- Issues in cloud computing, QoS Issues, Dependability
- Data migration and streaming in cloud
- Quality of Service (QoS) monitoring in a cloud computing environment
- Cloud Middleware, Mobile Cloud Computing, Inter Cloud issues
- A grid of clouds, Sky computing, Load balancing
- Resource optimization, Resource dynamic reconfiguration, Monitoring in cloud
7. Cloud Computing Platforms 5 hrs
- Installing cloud platforms and performance evaluation
- Features and functions of cloud platforms
- Xen Cloud Platform
- Eucalyptus
- OpenNebula
- Nimbus, TPlatform
- Apache Virtual Computing Lab (VCL)
8. Cloud for the Enterprise as a Service 5 hrs
- Storage, Database, Information, Process, Platform, Integration
- Security, Management / Governance, Infrastructure
References
- Judith Hurwitz, R. Bloor, M. Kanfman, F. Halper — Cloud Computing for Dummies, Wiley India Edition
- Gautam Shroff — Enterprise Cloud Computing, Cambridge
- Ronald Krutz and Russell Dean Vines — Cloud Security, Wiley India
- David S. Linthicum — Cloud Computing and SOA Convergence in your Enterprise, Pearson
MIT 213: Entrepreneurship
Lecture40 hrs
Tutorial10 hrs
Internal20
External80
Credits2
After completion of this course, students will be able to create, start, manage and develop new ventures, buy existing businesses, and apply the working knowledge of entrepreneurship values to analyze and solve problems.
Course Contents
Chapter 1: The Foundation of Entrepreneurship 5 hrs
- The world of the entrepreneur — what is an entrepreneur?
- The benefits of entrepreneurship
- The potential drawbacks of entrepreneurship
- Behind the boom: what feeds the entrepreneurial fire
- The cultural diversity of entrepreneurship
- The ten deadly mistakes of entrepreneurship
- Putting failure into perspective
- How to avoid the pitfalls
Chapter 2: Inside the Entrepreneurial Mind — From Ideas to Reality 5 hrs
- Creative innovation and entrepreneurship
- Creative thinking and barriers to creativity
- How to enhance creativity — the creative process
- Techniques for improving creativity
- Intellectual property: protecting your ideas
Chapter 3: Designing a Competitive Business Model and Strategic Plan 2 hrs
- Building competitive advantages
- The strategic management process
Chapter 4: Conducting a Feasibility Analysis and Crafting a Winning Business Plan 4 hrs
- Conducting a feasibility analysis
- Why develop a business plan
- The elements of a business plan
- What lenders and investors look for in a business plan
- Making the business plan presentation
- Business plan format
Chapter 5: Forms of Business Ownership 2 hrs
- The sole proprietorship
- The partnership
- Corporations
- Other forms of ownership
Chapter 6: Building a Powerful Marketing Plan 2 hrs
- Determine customer needs, wants and demands through marketing research
- Building a guerrilla marketing plan
- Pinpointing the target market
- Marketing mix
Chapter 7: Pricing Strategies 4 hrs
- Image, competition and values
- Pricing strategies and tactics / methods
- Pricing concept for manufacturers
- Pricing strategies and methods for service firms
- The impact of credit on pricing
Chapter 8: Creating a Successful Financial Plan 4 hrs
- Basic financial statements
- Ratio analysis — interpreting business ratios
- Break-even analysis with graphical presentation
Chapter 9: Managing Cash Flow 4 hrs
- Cash management — cash and profits are not the same
- Preparing the cash budget
- The big three of cash management
- Avoiding the cash crunch
Chapter 10: Sources of Financing 2 hrs
- Planning for capital needs
- Equity capital versus debt capital
- Sources of equity and debt financing
Chapter 11: Choosing the Right Location and Layout 3 hrs
- Location criteria and options
- The location decision for manufacturers
- Layout and designing considerations
Chapter 12: Franchising and Entrepreneur 3 hrs
- Types of franchising
- The benefits and drawbacks of buying a franchise
References
- Thomas W. Zimmerer and Norman M. Scarborough — Entrepreneurship, PHI Pvt. Ltd India
MIT 214: Networking with IPv6
Lecture50 hrs
Tutorial10 hrs
Practical20 hrs
Internal20
External60
Credits3
Students will gain knowledge about fundamental issues in network protocol design and implementation, with the principles underlying TCP/IP protocol design; historical development of Internet Protocol Version 6; IPv6 and QoS, IP network migrations and applications.
Course Contents
Unit 1: Networking Protocols 20 hrs
- OSI Model and Internet Protocols:
- OSI Model, Internet IP/UDP/TCP
- Routing in the Internet and CIDR, Multicasting
- Unidirectional Link Routing, Next Generation Internet
- Internet Protocol Version 6 (IPv6): History and Header Format
- Feature of IPv6, International trends and standards
- IPv6 Addressing: Unicast, Anycast and Multicast
- ICMPv6 and Neighbor Discovery: ICMPv6 General Message Format, ICMP Error and Information Message Types
- Neighbor Discovery Processes and Messages, Path MTU Discovery
- MLD Overview
Unit 2: Security, Quality of Service and Routing in IPv6 15 hrs
- Types of Threats and Security Techniques
- IPSEC Framework
- QoS Paradigms, QoS in IPv6 Protocols
- IPv6 Routing: RIPng, OSPF for IPv6, BGP extensions for IPv6
- PIM-SM and DVMRP for IPv6
Unit 3: IPv4/IPv6 Transition Mechanisms and IPv6 Network and Server Deployment 15 hrs
- Migration Strategies, Tunneling, Automatic Tunneling, Configured Tunneling
- Dual Stack, Translation, NAT-PT
- IPv6 Network Configuration in Linux and Windows Machines
- IPv6 enabled WEB/PROXY/DNS/MAIL Server Configuration
- IPv6 Deployment: Challenges and Risks
- IPv6 and the NGN (Next Generation Network)
Laboratory Work
- Lab 1: Enable IPv6 in Windows/Linux
- Lab 2: IPv6 Header Analysis
- Lab 3: IPv6 Packet Analysis (neighbor/router solicitation/discovery)
- Lab 4: Unicast Routing Implementation using Zebra-OSPF and OSPF phase analysis
- Lab 5: Multicast Routing Implementation using XORP-PIM/SM and PIM/SM phase analysis
- Lab 6: IPv6 DNS/WEB/Proxy implementation and test
- Lab 7: Case Study
Reference Books
- Silvia Hagen — IPv6 Essentials, O'Reilly
- Joseph Davies — Understanding IPv6, Eastern Economy Edition
- J. F. Kurose and K. W. Ross — Computer Networking: A Top-Down Approach Featuring the Internet, Addison-Wesley, 2000
- S. A. Thomas — IPng and the TCP/IP Protocols, Wiley, 1995
- O. Hersent, D. Gurle, J.-P. Petit — IP Telephony, Addison-Wesley, 2000
MIT 215: Wireless Networking
Lecture50 hrs
Tutorial10 hrs
Practical20 hrs
Internal20
External60
Credits3
This course focuses on higher-layer protocol design and analysis for wireless networks, providing a detailed introduction to protocols for power control, medium access, routing, and congestion control — the fundamental basis for cellular networks, mobile ad-hoc networks, and sensor networks.
Course Contents
Unit 1: Introduction to Wireless Network Architectures 17 hrs
- Wireless Technologies Overview:
- Cellular networks, wireless local area networks, multi-hop networks
- Radio propagation models
- Narrowband digital modulation and coding under wireless fading environments
- Basics of CDMA and OFDM, Diversity and MIMO, Equalization
- Power Allocation and Medium Access:
- Power allocation for rate-adaptive parallel channels (Waterfilling)
- Power control for fixed-rate independent channels: Centralized linear solution, Foschini-Miljanic distributed algorithm, Randomized
- Medium access 1: Unslotted and Slotted Aloha — System throughput analysis and two-user saturation rate region analysis
- Medium access 2: CSMA — System throughput analysis and two-user rate region analysis for p-persistent CSMA
- Bianchi's Markov chain analysis of throughput for the IEEE 802.11 CSMA protocol
- Other window adaptation mechanisms
- Graph coloring and its application to channel allocation in TDMA/FDMA/CDMA-based wireless networks
Unit 2: Linear Programming in Wireless Networks 11 hrs
- Integer Linear Programming formulation of channel allocation for both protocol and SINR interference models
- Extensions to other objective functions: non-homogeneous channel preferences, throughput maximization and fairness
- Introduction to wireless network simulator (NS-2/QualNet)
- Introduction to multi-hop wireless network routing
- The AODV and OLSR protocols for mobile ad-hoc networks
- Link estimation and neighbor management
Unit 3: Routing in Wireless Networks 17 hrs
- Routing Techniques:
- Geographic routing: greedy routing and solutions for avoiding routing holes
- Routing in intermittently connected mobile networks
- Theory and Practice of Dynamic Backpressure Routing
- Lyapunov drift minimization — centralized maximum weight independent set matching solution
- Opportunistic routing and Cooperative Routing: ExOR, Flash flooding, Barrage relay
- Congestion Control and Emerging Standards:
- TCP over wireless networks
- Congestion sharing: IFRC, WCAP
- Centralized and distributed explicit and precise rate control: RCRT, WRCP
- Optimization-based rate control with Lagrange duality and queue backpressure
- Discussion of emerging industry standards: 4G Cellular, IEEE 802.11p
Laboratory Work
Lab exercises cover all chapters using Matlab and C programming:
- Assignment 1: Network architecture and PHY-layer
- Project 1: Simulation of coding and modulation on a single link
- Assignment 2: Power allocation/control and randomized medium access
- Project 2: Simulation of IEEE 802.11 MAC
- Assignment 3: Graph Coloring and ILP
- Assignment 4: Wireless Routing
- Project 3: Simulation of MANET routing protocol
- Assignment 5: Wireless Congestion Control
References
- Andrea Goldsmith — Wireless Communications, Cambridge University Press