MA9209 APPLIED MATHEMATICS FOR PERVASIVE COMPUTING SYLLABUS | ANNA UNIVERSITY ME MOBILE AND PERVASIVE COMPUTING 1ST SEM SYLLABUS REGULATION 2009 2011 2012-2013 BELOW IS THE ANNA UNIVERSITY FIRST SEMESTER M.E MOBILE AND PERVASIVE COMPUTING DEPARTMENT SYLLABUS, TEXTBOOKS, REFERENCE BOOKS,EXAM PORTIONS,QUESTION BANK,PREVIOUS YEAR QUESTION PAPERS,MODEL QUESTION PAPERS, CLASS NOTES, IMPORTANT 2 MARKS, 8 MARKS, 16 MARKS TOPICS. IT IS APPLICABLE FOR ALL STUDENTS ADMITTED IN THE YEAR 2011 2012-2013 (ANNA UNIVERSITY CHENNAI,TRICHY,MADURAI, TIRUNELVELI,COIMBATORE), 2009 REGULATION OF ANNA UNIVERSITY CHENNAI AND STUDENTS ADMITTED IN ANNA UNIVERSITY CHENNAI DURING 2009
MA9209 APPLIED MATHEMATICS FOR PERVASIVE COMPUTING L T P C
3 1 0 4 OBJECTIVES
Provides mathematical concepts for Pervasive Computing system analysis which includes,
graph theory for network modeling, optimization technique for using System and Net resources,
Probability and Queuing theories to address stochastic and dynamic environment in data
transfer. Also it Provides solutions for linear equations of large systems.
PREREQUISITES
Essential
Knowledge of Matrices, Differential equations and Numerical methods
Optional
-------
UNIT I LINEAR ALGEBRA 9
Introduction to Vector spaces, basic vector analysis methods, Matrix norms – Jordan canonical
form – Generalized eigenvectors – Singular value decomposition – Pseudo inverse – Least
square approximations – QR algorithm.
UNIT II GRAPH THEORY 9
Introduction to Paths, Trees, Vector spaces, Matrix Coloring and directed graphs; Some basic
algorithms – Shortest path algorithms – Depth-First search on a graph – Isomorphism – Other
Graph - Theoretic algorithms – performance of graph theoretic algorithms – Graph-theoretic
Computer languages
UNIT III OPTIMIZATION TECHNIQUES 9
Linear programming - Basic concepts – Graphical and Simplex methods –Transportation
problem – Assignment problem; Dynamic programming - Elements of the dynamic
programming model – optimality principle – Examples of dynamic programming models and
their solutions.
UNIT IV PROBABILITY AND RANDOM VARIABLES 9
Probability – 1D Random variables – Binomial, Poisson, Geometric, Uniform, Normal,
Exponential distributions – Moment generating functions and their properties – Functions
Transformation of Random variables, Finite probability - Probability distributions - Conditional
Probability – Independence – Baye’s theorem; Expectations. Reliability and Markov chain
transition probability matrix.
UNIT V QUEUEING THEORY 9
Single and Multiple servers Markovian Queuing models, finite and Infinite capacity Queues –
Finite source model – Queuing applications. L : 45 T : 15 Total : 60 PERIODS REFERENCES
1. Taha H .A., Operations Research: An Introduction, Pearson Education Edition, Asia, New
Delhi, Seventh Edition 2002.
2. Walpole R.E., Myer R.H., Myer S.L., and Ye, K., Probability and Statistics for Engineers and
Scientists, Pearson Education, 7th Edition, Delhi, 2002.
3. Lewis.D.W. “Matrix Theory” , Allied Publishers, Chennai 1995
4. Bronson, “Matrix Operations, Schaums outline Series”, McGraw Hill, New York. 1989.
5. Kishor S.Trivedi, Probability & Statistics with reliability, queuing and Computer Science
Applications, Prentice Hall India, 2001
6. Narasingh Deo,Graph Theory with applications to Engineering and Computer Science,
Prentice Hall India,1997
7. Harary, Graph Theory, Narosa publishing house - 2000
3
SOURCES
1. Oxford University UK ,
http://www.admin.ox.ac.uk/postgraduate/caz/comp.shtml
2. University of Essex – UK ,
http://cswww.essex.ac.uk/prospectivestudents/pg/msccompsci.htm
3. PPAM2005 sixth international conference on parallel processing and applied mathematics.
http://ppam.pcz.pl/topics.htm
MA9209 APPLIED MATHEMATICS FOR PERVASIVE COMPUTING L T P C
3 1 0 4 OBJECTIVES
Provides mathematical concepts for Pervasive Computing system analysis which includes,
graph theory for network modeling, optimization technique for using System and Net resources,
Probability and Queuing theories to address stochastic and dynamic environment in data
transfer. Also it Provides solutions for linear equations of large systems.
PREREQUISITES
Essential
Knowledge of Matrices, Differential equations and Numerical methods
Optional
-------
UNIT I LINEAR ALGEBRA 9
Introduction to Vector spaces, basic vector analysis methods, Matrix norms – Jordan canonical
form – Generalized eigenvectors – Singular value decomposition – Pseudo inverse – Least
square approximations – QR algorithm.
UNIT II GRAPH THEORY 9
Introduction to Paths, Trees, Vector spaces, Matrix Coloring and directed graphs; Some basic
algorithms – Shortest path algorithms – Depth-First search on a graph – Isomorphism – Other
Graph - Theoretic algorithms – performance of graph theoretic algorithms – Graph-theoretic
Computer languages
UNIT III OPTIMIZATION TECHNIQUES 9
Linear programming - Basic concepts – Graphical and Simplex methods –Transportation
problem – Assignment problem; Dynamic programming - Elements of the dynamic
programming model – optimality principle – Examples of dynamic programming models and
their solutions.
UNIT IV PROBABILITY AND RANDOM VARIABLES 9
Probability – 1D Random variables – Binomial, Poisson, Geometric, Uniform, Normal,
Exponential distributions – Moment generating functions and their properties – Functions
Transformation of Random variables, Finite probability - Probability distributions - Conditional
Probability – Independence – Baye’s theorem; Expectations. Reliability and Markov chain
transition probability matrix.
UNIT V QUEUEING THEORY 9
Single and Multiple servers Markovian Queuing models, finite and Infinite capacity Queues –
Finite source model – Queuing applications. L : 45 T : 15 Total : 60 PERIODS REFERENCES
1. Taha H .A., Operations Research: An Introduction, Pearson Education Edition, Asia, New
Delhi, Seventh Edition 2002.
2. Walpole R.E., Myer R.H., Myer S.L., and Ye, K., Probability and Statistics for Engineers and
Scientists, Pearson Education, 7th Edition, Delhi, 2002.
3. Lewis.D.W. “Matrix Theory” , Allied Publishers, Chennai 1995
4. Bronson, “Matrix Operations, Schaums outline Series”, McGraw Hill, New York. 1989.
5. Kishor S.Trivedi, Probability & Statistics with reliability, queuing and Computer Science
Applications, Prentice Hall India, 2001
6. Narasingh Deo,Graph Theory with applications to Engineering and Computer Science,
Prentice Hall India,1997
7. Harary, Graph Theory, Narosa publishing house - 2000
3
SOURCES
1. Oxford University UK ,
http://www.admin.ox.ac.uk/postgraduate/caz/comp.shtml
2. University of Essex – UK ,
http://cswww.essex.ac.uk/prospectivestudents/pg/msccompsci.htm
3. PPAM2005 sixth international conference on parallel processing and applied mathematics.
http://ppam.pcz.pl/topics.htm
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