Data-intensive computing is the driver of the continuing growth and success of global Internet services and cloud applications. The system infrastructure for data-intensive computing is built and run on top of compute resources housed in large, centralized data centers. These data centers are typically placed away from populous regions for economic reasons. This leads to a fundamental limit on the speed of communication between users and data centers. To overcome this limit, the project aims to extend data management systems to be edge-aware. Edge-awareness is the capability of utilizing resources that are closer to users to reduce the latency they experience by one to two orders of magnitude.

The project will investigate two closely related research challenges to enable edge-aware data management systems. The first research challenge focuses on one of the most important building blocks of distributed systems, namely the problem of agreement between different nodes (also called the consensus problem.) The project proposes a design of a new consensus protocol that, unlike existing consensus protocols, is edge-aware and thus enables preserving consensus and fault-tolerance while achieving the low-latency performance enabled by edge-awareness. The second research challenge is building edge data management systems that react efficiently to user mobility. The project proposes augmenting consensus protocols with a mobility component that enables handling user mobility efficiently while preserving consensus and fault-tolerance.

Large sectors of business and industry, in addition to the modern style of living, increasingly rely on data-intensive Internet and cloud applications. This project aims to advance the data and system infrastructure for these applications. The project will also provide the opportunity for undergraduate and graduate students to learn and work on fundamental data management systems research.

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)
Type
Standard Grant (Standard)
Application #
1815212
Program Officer
Marilyn McClure
Project Start
Project End
Budget Start
2018-10-01
Budget End
2021-09-30
Support Year
Fiscal Year
2018
Total Cost
$249,500
Indirect Cost
Name
University of California Santa Cruz
Department
Type
DUNS #
City
Santa Cruz
State
CA
Country
United States
Zip Code
95064