Providing high-speed Internet services to communities and businesses while limiting the infrastructure cost has been a long-term goal of network protocol designs. There have been challenges in achieving fast, scalable, and fine-grained network processing while maintaining low network cost, mainly due to the limited resources on network devices such as fast memory. The promising approach of exploiting programmable networks, such as software defined networking, were considered difficult to execute on conventional network devices. This project aims to use an innovative hashing scheme, Othello, to improve network performance without special and expensive hardware by exploring fast, memory-efficient, and portable primitives for network processing based on innovative data structures and algorithms.

This project proposes Othello Hashing, a key-value lookup algorithm developed on the theoretical foundation of Minimal Perfect Hashing. Othello Hashing achieves faster lookup speed and much smaller memory cost compared to existing network lookup methods. It utilizes network programmability to support dynamic updates on its lookup structures. This project plans to develop a number of important network primitives using Othello, including forwarding information bases, software load balancers, distributed data placement, and private data access. The success of this project will demonstrate Othello Hashing as a fundamental tool in designing novel network algorithms, protocols, and systems, for which existing tools may not be suitable. The impact of Othello Hashing may go beyond the networking research: the collaboration of the PI with genome biology researchers on applying Othello to metagenomic sequence classification has led to promising results. The project also offers a number of education activities for student training, undergraduate research participation, diversity promotion, and outreach activities.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Agency
National Science Foundation (NSF)
Institute
Division of Computer and Network Systems (CNS)
Application #
1750704
Program Officer
Darleen Fisher
Project Start
Project End
Budget Start
2018-07-01
Budget End
2023-06-30
Support Year
Fiscal Year
2017
Total Cost
$303,388
Indirect Cost
Name
University of California Santa Cruz
Department
Type
DUNS #
City
Santa Cruz
State
CA
Country
United States
Zip Code
95064