| GHC 7207
Charlotte Yano - (412) 268-7656
|Mailing Address:|| Computer Science Department
School of Computer Science
Carnegie Mellon University
5000 Forbes Avenue
Pittsburgh, PA 15213-3891
| Professor, SCS
Distributed computing, performance analysis, scheduling and resource allocation,
I am interested in the performance analysis and design of computer systems, particularly distributed systems. I work on finding analytical models which capture the important characteristics of a computer system and allow me to redesign the system to improve its performance.
I am interested in the performance analysis and design of computer systems, particularly distributed systems. I work on finding analytical models which capture the important characteristics of a computer system and allow me to redesign the system to improve its performance (response time).
I believe that many conventional wisdoms on which we base system designs are not well understood and sometimes false, leading to inferior designs. Many of our existing beliefs stem from queueing research in the 60's and 70's -- the great era for system performance modeling. Unfortunately, back then we did not have all the analytical and computational tools available today. Consequently, some questions were answered only under the approximation of Markovian workloads (exponentially distributed job sizes) which we now know to be non-representative of many real-world workloads (which show much greater variability and often heavy tails). Also, many multi-server system models and scheduling/routing schemes were not analytically tractable at that time.
My research revisits these very classic questions in system design, armed with today's new queueing and computational techniques, as well as a new perspective on real-world workloads, performance metrics, and implementation experience. I work on deriving new fundamental theorems in system design, many of which seem couterintuitive in light of age-old beliefs. I then incorporate these theorems into implementations of Web servers, database servers, and distributed server systems.
Here are a few examples of commonly-held beliefs that my research challenges: