Carnegie Mellon University

Advanced Stochastic Analysis & Applications II

Course Number: 47775

In designing computer systems one is usually constrained by certain performance requirements and limitations. For example, one might need to guarantee a response time SLA or certain throughput requirement, while at the same time staying within a power budget or cost budget. On the other hand, one often has many choices: One fast disk, or two slow ones? More memory, or a faster processor? A fair scheduler or one that minimizes mean response time? For multi-server systems, one can choose from a wide array of load balancing policies, a wide array of migration policies, capacity provisioning schemes, power management policies ... The possibilities are endless. The best choices are often counter-intuitive. Ideally, one would like to have answers to these questions before investing the time and money to build a system. This class will introduce students to analytic stochastic modeling with the aim of answering the above questions. This class is heavy on math. Students should have a strong background in probability before embarking on this class. If you are worried about your probability background, please work through all the examples and exercises in Chpt 3 of the class textbook. You can also see the instructor for more probability materials.

 

Degree: PhD
Concentration: Operations Research
Academic Year: 2023-2024
Semester(s): Mini 2
Required/Elective: Elective
Units: 6

Format

Lecture: 100min/wk and Recitation: 50min/wk