IT369
Course Name:
Performance Modeling (IT369)
Programme:
Category:
Credits (L-T-P):
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