CP5003 PERFORMANCE ANALYSIS OF COMPUTER SYSTEMS SYLLABUS - ANNA UNIVERSITY PG REGULATION 2017 - Anna University Internal marks 2018

CP5003 PERFORMANCE ANALYSIS OF COMPUTER SYSTEMS SYLLABUS - ANNA UNIVERSITY PG REGULATION 2017

CP5003 PERFORMANCE ANALYSIS OF COMPUTER SYSTEMS SYLLABUS
REGULATION 2017
ME CSE - SEMESTER 3

OBJECTIVES:
  • To understand the mathematical foundations needed for performance evaluation of computer systems
  • To understand the metrics used for performance evaluation
  • To understand the analytical modeling of computer systems
  • To enable the students to develop new queuing analysis for both simple and complex systems
  • To appreciate the use of smart scheduling and introduce the students to analytical techniques for evaluating scheduling policies

UNIT I OVERVIEW OF PERFORMANCE EVALUATION
Need for Performance Evaluation in Computer Systems – Overview of Performance Evaluation Methods – Introduction to Queuing – Probability Review – Generating Random Variables for Simulation – Sample Paths, Convergence and Averages – Little‘s Law and other Operational Laws – Modification for Closed Systems.

UNIT II MARKOV CHAINS AND SIMPLE QUEUES

Discrete-Time Markov Chains – Ergodicity Theory – Real World Examples – Google, Aloha – Transition to Continuous-Time Markov Chain – M/M/1.

UNIT III MULTI-SERVER AND MULTI-QUEUE SYSTEMS
Server Farms: M/M/k and M/M/k/k – Capacity Provisioning for Server Farms – Time Reversibility and Burke‘s Theorem – Networks of Queues and Jackson Product Form – Classed and Closed Networks of Queues.

UNIT IV REAL-WORLD WORKLOADS
Case Study of Real-world Workloads – Phase-Type Distributions and Matrix-Alalytic Methods – Networks with Time-Sharing Servers – M/G/1 Queue and the Inspection Paradox – Task Assignment Policies for Server Farms.

UNIT V SMART SCHEDULING IN THE M/G/1
Performance Metrics – Scheduling Non-Preemptive and Preemptive Non-Size-Based Policies - . Scheduling Non-Preemptive and Preemptive Size-Based Policies – Scheduling - SRPT and Fairness.

TOTAL : 45 PERIODS

OUTCOMES :
Upon completion of this course, the students should be able to
  • Identify the need for performance evaluation and the metrics used for it
  • Distinguish between open and closed queuing networks
  • Use Little‘e law and other operational laws
  • Apply the operational laws to open and closed systems
  • Use discrete-time and continuous-time Markov chains to model real world systems
  • Develop analytical techniques for evaluating scheduling policies

REFERENCES:
  1. K. S. Trivedi, ―Probability and Statistics with Reliability, Queueing and Computer Science Applications‖, John Wiley and Sons, 2001.
  2. Krishna Kant, ―Introduction to Computer System Performance Evaluation‖, McGraw-Hill, 1992.
  3. Lieven Eeckhout, ―Computer Architecture Performance Evaluation Methods‖, Morgan and Claypool Publishers, 2010.
  4. Mor Harchol - Balter, ―Performance Modeling and Design of Computer Systems – Queueing Theory in Action‖, Cambridge University Press, 2013.
  5. Paul J. Fortier and Howard E. Michel, ―Computer Systems Performance Evaluation and Prediction‖, Elsevier, 2003. 
  6. Raj Jain, ―The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation and Modeling‖, Wiley-Interscience, 1991.

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