Demo Data from EDBT 2026 / reviewers in the wild / expert
Stephanie N. Jones
dblp:176/7582
· DBLP profile ↗
3ranked-venue papers
2as first author
0since 2021 · last 2016
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 3 · 2 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
2 papers |
Storage systems · 97% High-performance computing · 3% | |
| Network and information security
1 paper |
Authentication and access control · 100% |
Topics — the 5 heaviest of 6, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Storage systems
data placement |
0.2 | 1 | 2016 | Classifying Data to Reduce Long-Term Data Movement in Shingled Write Disks · ACM Trans. Storage 2016 |
Storage systems › magnetic recording
shingled magnetic recording |
0.2 | 1 | 2016 | Classifying Data to Reduce Long-Term Data Movement in Shingled Write Disks · ACM Trans. Storage 2016 |
Storage systems › magnetic storage
hard disk drive |
0.1 | 1 | 2016 | Classifying Data to Reduce Long-Term Data Movement in Shingled Write Disks · ACM Trans. Storage 2016 |
Authentication and access control › access control models
capability-based access control |
0.1 | 1 | 2007 | Scalable security for petascale parallel file systems · SC 2007 |
Storage systems › file systems › distributed file system
parallel file system |
0.1 | 1 | 2007 | Scalable security for petascale parallel file systems · SC 2007 |
Methods — techniques the papers use, named apart from their topics
heuristic-based data classification · 0.2protocol design · 0.1performance evaluation · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Classifying Data to Reduce Long-Term Data Movement in Shingled Write DisksabstractShingled magnetic recording (SMR) is a means of increasing the density of hard drives that brings a new set of challenges. Due to the nature of SMR disks, updating in place is not an option. Holes left by invalidated data can only be filled if the entire band is reclaimed, and a poor band compaction algorithm could result in spending a lot of time moving blocks over the lifetime of the device. We propose using write frequency to separate blocks to reduce data movement and develop a band compaction algorithm that implements this heuristic. We demonstrate how our algorithm results in improved data management, resulting in an up to 45% reduction in required data movements when compared to naive approaches to band management. Stephanie N. Jones, Ahmed Amer, Ethan L. Miller, Darrell D. E. Long, Rekha Pitchumani, Christina R. Strong |
ACM Trans. Storage | 1 |
| 2015 | Classifying data to reduce long term data movement in shingled write disksabstractShingled Magnetic Recording (SMR) is a means of increasing the density of hard drives that brings a new set of challenges. Due to the nature of SMR disks, updating in place is not an option. Holes left by invalidated data can only be filled if the entire band is reclaimed, and a poor band compaction algorithm could result in spending a lot of time moving blocks over the lifetime of the device. We propose using write frequency to separate blocks to reduce data movement and develop a band compaction algorithm that implements this heuristic. We demonstrate how our algorithm results in improved data management, resulting in an up to 47% reduction in required data movements when compared to naive approaches to band management. Stephanie N. Jones, Ahmed Amer, Ethan L. Miller, Darrell D. E. Long, Rekha Pitchumani, Christina R. Strong |
MSST | 1 |
| 2007 | Scalable security for petascale parallel file systemsabstractPetascale, high-performance file systems often hold sensitive data and thus require security, but authentication and authorization can dramatically reduce performance. Existing security solutions perform poorly in these environments because they cannot scale with the number of nodes, highly distributed data, and demanding workloads. To address these issues, we developed Maat, a security protocol designed to provide strong, scalable security to these systems. Maat introduces three new techniques. Extended capabilities limit the number of capabilities needed by allowing a capability to authorize I/O for any number of client-file pairs. Automatic Revocation uses short capability lifetimes to allow capability expiration to act as global revocation, while supporting non-revoked capability renewal. Secure Delegation allows clients to securely act on behalf of a group to open files and distribute access, facilitating secure joint computations. Experiments on the Maat prototype in the Ceph petascale file system show an overhead as little as 6--7%. Andrew W. Leung, Ethan L. Miller, Stephanie N. Jones |
SC | 3 |