Fall 2019

Seminar in Computer Science: Analytical Performance Modeling

Listed in: Computer Science, as COSC-450

Formerly listed as: COSC-40

Moodle site: Course


Kristen S. Gardner (Section 01)


In designing computer systems, one often is trying to meet a performance objective while simultaneously being constrained by resource or budgetary limitations. For example, we might want to ensure that jobs complete service within a certain time bound, while also remaining within a fixed cost or power budget. We also have many choices to make: should we purchase one fast server or two slow servers? In what order should we schedule jobs to run on our server? In a multi-server system, how should we decide to which server an arriving job should best be dispatched?

In this course students will be introduced to analytical performance modeling, the goal of which is to answer the above questions (and more) from a mathematical perspective. Possible topics include operational laws, elementary queueing theory, capacity provisioning for server farms, and scheduling theory.

Requisite: COSC 223 or MATH 360/STAT 360. Limited to 20 students. Preference given to CS majors. Fall semester. Professor Gardner.

If Overenrolled: Priority to Computer Science majors


2020-21: Not offered
Other years: Offered in Fall 2008, Spring 2011, Fall 2012, Fall 2014, Spring 2015, Fall 2019