- Coding and Graph-Theoretic Approaches to the Service Capacity Problem
- Project Year:
2019
- REU Student (s):
Austin Allen | Carnegie Mellon University PA
- Student 1 Institution:
Carnegie Mellon University
- Project Mentor:
Emina Soljanin
- Project Mentor Area:
Electrical and Computer Engineering
- Project Abstract:
Traditionally coding has been associated with error correction of data that has been transmitted across a noisy channel. Recently coding has been applied to increased fault tolerance for distributed storage systems. Data storage is extremely important to companies such as Amazon and Google who wish to deliver content efficiently and in a timely manner.However, an aspect that is often neglected is understanding how many users that the system can support. This is the goal of the service capacity problem. The problem has been studied in a continuous setting, however, our goal is to study some of the connections of the service capacity problem to problems in graph theory and combinatorial optimization. Overall these connections may be able to give us insight into a codes' load-balancing properties in distributed storage systems.
