AI363

Course Name: 

Performance Modeling (AI363)

Programme: 

B.Tech (AI)

Category: 

Programme Specific Electives (PSE)

Credits (L-T-P): 

(3-0-2) 4

Content: 

Operational Laws: Little's Law, response-time law, asymptotic bounds, modification analysis, performance metrics; Markov Chain Theory: discrete-time Markov chains, continuous-time Markov chains, renewal theory, time-reversibility; Poisson Process: memorylessness, Bernoulli splitting, uniformity, PASTA; Queueing Theory: open networks, closed networks, time-reversibility, RenewalReward, M/M/1, M/M/k, M/M/k/k, Burke's theorem, Jackson networks, classed networks, load-dependent servers, BCMP result and proof, M/G/1 full analysis, M/G/k, G/G/1, transform analysis (Laplace and z-transforms); Simulations: time averages versus ensemble averages, generating random variables for simulation, Inspection Paradox; Modeling Empirical Workloads: heavy-tailed property, Pareto distributions, heavy-tailed distributions, understanding variability and tail behavior, Matrixanalytic methods; Management of Server Farms: capacity provisioning, dynamic power management, routing policies; Analysis of Scheduling: FCFS, non-preemptive priorities, preemptive priorities, PS, LCFS, FB, SJF, PSJF, SRPT, etc

References: 

Mor Harchol-Balter,Performance Modeling and Design of Computer Systems: Queueing Theory in Action, Cambridge University Press.
Papoulis and S. U. Pillai, Probability, Random Variables, and Stochastic Processes, McGraw-Hill.
Leon-Garcia, Probability and Random Processes for Electrical Engineering, Prentice Hall.
Michael Pinedo, Scheduling Theory, Algorithms, and Systems, Prentice Hall.

Department: 

Information Technology
 

Contact us

Head of the Department,
Department of Information Technology,
National Institute of Technology Karnataka,
SurathkalP. O. Srinivasnagar, Mangalore - 575 025
Ph.:    +91-824-2474056
Email:  hodit [at] nitk [dot] edu [dot] in
 

Web Admin: Sowmya Kamath S

Connect with us

We're on Social Networks. Follow us & stay in touch.