Ph.D. (Research Program)

A Doctor of Philosophy (Ph.D.) is the highest academic degree awarded by universities in most countries. PhDs are awarded for programs across the whole breadth of academic fields.Institute of Informatics and Communication (IIC), UDSC invites applications for Full Time Ph.D. programme for the academic year 2017-18. A total of 01 seat is available in the areas of Informatics and Communication. The Institute/Department/University reserves the right to change the number of seats or not to award any Ph.D. position.


PHIT-01: Computational Modelling and Performance of Stochastic Systems:


Category: Course work
Teaching: Lectures 4 hours (per week).

Learning outcomes: At the end of the course the student will be able to:

• Understand the basic concepts involved in designing a stochastic system model.
• Use a simulation package or a simulation program (Matlab).
• Present results from a simulation, in both verbal and written formats.
• Work as part of a team through an extended project.
• Follow a system modelling and simulation exercise from conception through to
completion.

Course contents:

Unit-I: Introduction to probability theory Definition

Identities, probability distribution -Bernoulli, Binomial, Poisson, Gaussian, Weibul, Pareto etc. and their basic properties; Testing hypotheses.

Unit-II: Stochastic Processes Basic introduction

Random walk, Computer simulation and Monte Carlo Methods (MCM) simulation of random variables, solving problems by 0.23 MCM, Markov processes, Markov chains, simulation of stochastic processes.

Unit-III: Queuing system Poisson processes

Birth and death process, Bernoulli single server queuing system, single server queue (M/M/1), multiple server queue (M/M/c), Client-server model, single server queue with general service (M/G/1), Performance of queuing systems; busy time analysis, basics of Forward Data Link Performance and optimization; Queuing Network.

Assessment: A midterm exam and internal assessment of 30% and final exam (end of semester) for 70% of the final grade.

 

 

 

PHIT-02: Advanced Communication Networks:


Category: Course work
Teaching: Lectures 4 hours(per-week).

Learning outcomes: At the end of the course the student will be able to:

• To identify and discuss the concepts underlying IPv6 protocol, and their main characteristics
and functionality;
• to understand the principles and functionality of mobile IP, explaining its containerization in IPv6; to understand the needs of optimization of the mobility mechanisms and description of some extensions that aim to reduce handover latency and requirements from terminals;
• To recognize the need for service integration and discuss how it can be accomplished;
• To explain and exemplify current QoS architectures and mechanisms, and the QoS support challenges in future networks;
• to understand and explain the design issues in transport services in face of applications and services requirements;
• to understand theoretical and practical concepts behind the design of multiconstained applications and services;
• to discuss relevant management issues and devise adequate network management solutions;
• to identify and assess possible research opportunities and difficulties within the course scope.

Course contents:


Unit-I: Modeling and Traffic Management

Birth-Death model, Continuous-Time and Discrete-Time modeling for Incoming Traffic and Inter-arrival time characterization using Poisson and Bernoulli traffic models. Modeling and Performance evaluations of Flow Control Protocols like Leaky Bucket algorithm, Token Bucket algorithm using Single Arrival/Single Departure Model (M/M/1/B) and Multiple Arrival/Single Departure Model (Mm/M/1/B). Modeling and Performance evaluations of Error Control Protocols like Stop-and-Wait ARQ, Go-Back-N (GBN ARQ), Selective-Repeat (SR ARQ). Modeling and Performance evaluations of Medium Access Control Protocols like ALOHA, Slotted ALOHA, CSMA, CSMA/CD, Distributed and Point Co-ordination functions for Wireless LANs.

Unit-II: Scheduling and Routing Algorithms

Packet selection, dropping and fair scheduling, Time-based and rate-based scheduling, Modeling and analysis of common scheduling algorithms like FIFO, weighted round-robin, processor sharing, packet-by-packet generalized processor sharing, frame based fair queuing, core-stateless fair queuing, random early detection, etc. Switches, Routers, Analysis and performance evaluations for Input and Output queuing switch, Shared-buffer switch, single-stage and multi-stage interconnection networks, Generalized Cube Network, Banyan Network, Improved Logical Neighborhood networks.

Assessment: A midterm exam and internal assessment of 30% and final exam (end of semester) for 70% of the final grade.

 

 

 

PHIT-03: Communication Theory and Wave Propagation

Category: Course work
Teaching: Lectures 4 hours(per-week).

Learning outcomes: At the end of the course the student will be able to:

  • Understand the properties of electromagnetic (EM) waves
  • Analyze the propagation of plane EM waves in free space, media and at interfaces
  • Determine the characteristics of EM waves in bounded media
  • Apply the EM wave theory to transmission lines, antennas, guided wave and fiber-optic communication Course contents: Probability and random variables; Baye's Theorem;
  • Probability density and Probability distribution functions, statistical expectation, moments and characteristic functions, various distributions, multiple random variables, transformation of PDFs; Random

Processes: Basic concept, description of random process, correlation functions, Stationary and non-stationary process, ergodic process, power and energy;

Multiple random process; Random processes in frequency domain; Fourier transform of random processes, power spectrum of stochastic processes; Gaussian and White processes; Markov process; Various modulation systems and multiple access systems like FDMA, TDMA and CDMA. Wave Propagation: Free space propagation model, ground reflection; Earth and its effect on propagation, terrain formation considerations and its effects on free transmission, Diffraction and scattering from obstacles; Atmospheric attenuation; Practical link budget; Troposphere propagation; Troposystem fading characteristics; Troposcatter loss calculations; Fading in LOS troposcatter; Statistical behavior of fading; Diversity techniques.

Assessment: A midterm exam and internal assessment of 30% and final exam (end of semester) for 70% of the final grade.

 

 

 

PHIT-04: Communication Systems


Category: Course work
Teaching: Lectures 4 hours(per-week).

Learning outcomes: At the end of the course the student will be able to:
• Describe the basic aspects of signals and systems analysis in continuous time as well as in
discrete time.
• Describe the features of linear systems and continuous and discrete-time invariants.
• Perform a convolution in discrete and continuous time. Describe the properties of the
convolution operator.

• Describe the properties of the linear systems and invariants in time.
• Apply the Fourier transform for signals in continuous and discrete time.
• Perform signal and system analysis in the transform domain and signal processing.
• Describe the operating principles, performance methods and basic systems for the
transmission of data.
• Describe analogue and digital modulation techniques.
• Define the basic principles, and network architectures and communication services.
• Identify and describe telephone, mobile phone and public data networks and resolve networklevel
related problems.

Course contents:

Introduction to Wireless Communication Systems; Global system for mobile(GSM):

Cellular concept, System design, Transmission system; Receiving system; Frequency reuse; Channel interference and system capacity; Outdoor and indoor propagation models, small scale and multipath fading; practical link budget; Digital modulation with reference to wireless communication; Spread spectrum modulation; Modulation performances in fading and multipath channel; Multiple access techniques as applied to wireless communication;

Pocket Radio system; Wireless networking: 1G, 2G, 3G wireless networks, traffic routing; wireless data service.

Introduction to Satellite Systems;

Orbiting satellites, satellite frequency bands, communication satellite systems, satellite modulation and multiple access formats; Satellite systems in India; Satellite receiving systems, G/T ratio; Satellite uplink and downlink analyses in C, Ku and Ka bands; Spot beam, multiple beam, frequency reuse; Satellite transponder; Satellite front end.

Introduction to Optical Communication Systems; Optical fibers, sources and detectors;

Analog and Digital systems; Modulation and multiplexing; Power budget analysis;
Synchronous optical networks (SONET/SDH); Fiber distributed data interface (FDDI).

Assessment: A midterm exam and internal assessment of 30% and final exam (end of semester) for 70% of the final grade.

 

 

 

PHIT-05: Cloud Computing

Category: Course work
Teaching: Lectures 4 hours(per-week).

Learning outcomes: At the end of the course the student will be able to:
• articulate the main concepts, key technologies, strengths, and limitations of cloud computing and the possible applications for state-of-the-art cloud computing
• identify the architecture and infrastructure of cloud computing, including SaaS, PaaS, IaaS, public cloud, private cloud, hybrid cloud, etc.
• explain the core issues of cloud computing such as security, privacy, and interchangeability.

• choose the appropriate technologies, algorithms, and approaches for the related issues.
• identify problems, and explain, analyze, and evaluate various cloud computing
solutions.
• provide the appropriate cloud computing solutions and recommendations according to
the applications used.
• attempt to generate new ideas and innovations in cloud computing.
• collaboratively research and write a research paper, and present the research online.
• effectively communicate course work in writing and oral presentation.

Course contents:

Overview of Computing Paradigm
Emerging trends in Computing, Grid Computing, Cluster Computing, Distributed Computing, Utility Computing, Cloud Computing, Evolution of cloud computing

Introduction to Cloud Computing
Cloud Computing, Introduction to Cloud Computing, History of Cloud Computing, Cloud service providers, Properties, Characteristics & Disadvantages, Pros and Cons of Cloud Computing, Benefits of Cloud Computing, Cloud computing vs. Cluster computing vs. Grid computing, Role of Open Standards Cloud Architecture, Cloud computing stack, Comparison with traditional computing architecture (client/server), Services provided at various levels, How Cloud Computing Works, Role of Networks in Cloud computing, protocols used, Role of Web services, Service Models (XaaS), Infrastructure as a Service(IaaS), Platform as a Service(PaaS), Software as a Service(SaaS), Deployment Models, Public cloud, Private cloud, Hybrid cloud, Community cloud.

Infrastructure as a Service (IaaS): Introduction to IaaS, IaaS definition, Introduction to virtualization, Different approaches to virtualization, Hypervisors, Machine Image, Virtual Machine(VM), Resource Virtualization, Server, Storage, Network, Virtual Machine (resource) provisioning and manageability, storage as a service, Data storage in cloud computing(storage as a service)

Live Case Examples (Not limited to) Amazon EC2, Renting, EC2 Compute Unit, Platform and Storage, pricing, customers,

Eucalyptus Platform as a Service (PaaS) : Introduction to PaaS, What is PaaS, Service Oriented Architecture (SOA), Cloud Platform and Management, Computation, Storage, Live Case Examples: Google App Engine, Microsoft Azure, Sales Force.com’s Force.com platform

Software as a Service (SaaS) : Introduction to SaaS, Web services, Web 2.0, Web OS, Case Study on SaaS Service Management in Cloud Computing

Service Level Agreements (SLAs), Billing & Accounting, Comparing Scaling Hardware:

Traditional vs. Cloud, Economics of scaling: Benefitting enormously, Managing Data, Looking at Data, Scalability & Cloud Services, Database & Data Stores in Cloud, Large Scale Data Processing Cloud Security
Infrastructure Security, Network level security, Host level security, Application level security, Data security and Storage, Data privacy and security Issues, Jurisdictional issues raised by
Data location
• Identity & Access Management
• Access Control
• Trust, Reputation, Risk
• Authentication in cloud computing, Client access in cloud, Cloud contracting Model, Commercial and business considerations, Project Case Study on Open Source & Commercial Clouds [9 hours]
• Eucalyptus
• Microsoft Azure
• Amazon EC2


Assessment: A midterm exam and internal assessment of 30% and final exam (end of semester) for 70% of the final grade.

 

 

 

PHIT-06: Research Methodology


Category: Compulsory

Teaching: Lectures 4 hours(per-week).

Learning outcomes: At the end of the course the student will be able to:
• Defending the use of Research Methodology
• Judging the reliability and validity of experiments
• Being able to perform exploratory data analysis
• Being able to draw conclusions from categorical data
• Using computer-intensive methods for data analysis
• Drawing conclusions from test results
• Being able to compare different models

 

Course contents:

Part I

Research: Definition Objectives, Research and Scientific method, Meaning, Objectives, Motivation, Utility. Concept of theory, empiricism, deductive and inductive theory. Characteristics of scientific method, Plagiarism.

Types of Research:
Descriptive vs. Analytical Research, Applied vs. Fundamental Research, Quantitative vs Qualitative Research, Conceptual vs. Empirical Research,

Research Process: Basic Overview, Formulating the Research Problem, Defining the Research Problem, Research Questions, Research Methods vs. Research Methodology

Part II

Literature Review: Review Concepts and Theories

Formulation of Hypothesis:
Sources of Hypothesis, Characteristics of Hypothesis, Role of Hypothesis, Tests of Hypothesis, Research Design, Sampling Design

Data Collection:
Observation Method, Interview Method, Questionnaires, Case Study Method

Processing and Analysis of Data:
Processing Operations, Statistics in Research, Descriptive Statistics, Inferential Statistics, Elements / Types of Analysis

Interpretation of Data:
Evolutive and Evaluative, Identificatory and Impact studies, Projective and Predictive, Collative, Historical, Comparative Current trends in Research: Mono-disciplinary Research, Trans-disciplinary Research, Inter-disciplinary Research

Computer & Internet:
Its Role in Research, Technology and Software, Use of tools / techniques for Research, methods to search required information effectively, Reference Management Software, Software for paper formatting, Software for detection of Plagiarism Threats and Challenges to Good Research Assessment: A midterm exam and internal assessment of 50% and final exam (end of semester) for 50% of the final grade.

Computer & Internet:
Its Role in Research, Technology and Software, Use of tools / techniques for Research, methods to search required information effectively, Reference Management Software, Software for paper formatting, Software for detection of Plagiarism Threats and Challenges to Good Research

Assessment: A midterm exam and internal assessment of 50% and final exam (end of semester) for 50% of the final grade.