Demo Data from VLDB 2026 / reviewers in the wild / expert
Naresh Patel
dblp:99/6770
· DBLP profile ↗
2ranked-venue papers
1as first author
0since 2021 · last 2018
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 2 · 1 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
1 paper |
Storage systems · 87% Performance modeling and evaluation · 13% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Storage systems › storage architecture
enterprise storage |
0.3 | 1 | 2018 | Empirical Evaluation and Enhancement of Enterprise Storage System Request Scheduling · ACM Trans. Storage 2018 |
Storage systems › flash and SSD › flash memory
flash storage |
0.3 | 1 | 2018 | Empirical Evaluation and Enhancement of Enterprise Storage System Request Scheduling · ACM Trans. Storage 2018 |
Performance modeling and evaluation
workload characterization |
0.1 | 1 | 2018 | Empirical Evaluation and Enhancement of Enterprise Storage System Request Scheduling · ACM Trans. Storage 2018 |
Methods — techniques the papers use, named apart from their topics
trace-driven simulation · 0.3analytical modeling · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2018 | Empirical Evaluation and Enhancement of Enterprise Storage System Request SchedulingabstractSince little has been reported in the literature concerning enterprise storage system file-level request scheduling, we do not have enough knowledge about how various scheduling factors affect performance. Moreover, we are in lack of a good understanding on how to enhance request scheduling to adapt to the changing characteristics of workloads and hardware resources. To answer these questions, we first build a request scheduler prototype based on WAFL®, a mainstream file system running on numerous enterprise storage systems worldwide. Next, we use the prototype to quantitatively measure the impact of various scheduling configurations on performance on a NetApp®'s enterprise-class storage system. Several observations have been made. For example, we discover that in order to improve performance, the priority of write requests and non-preempted restarted requests should be boosted in some workloads. Inspired by these observations, we further propose two scheduling enhancement heuristics called SORD (size-oriented request dispatching) and QATS (queue-depth aware time slicing). Finally, we evaluate them by conducting a wide range of experiments using workloads generated by SPC-1 and SFS2014 on both HDD-based and all-flash platforms. Experimental results show that the combination of the two can noticeably reduce average request latency under some workloads. Deng Zhou, Vania Fang, Tao Xie 0004, Wen Pan, Ram Kesavan, Naresh Patel |
ACM Trans. Storage | 7 |
| 2000 | A Model of Completion Queue Mechanisms using the Virtual Interface APIabstractIn this paper we evaluate the performance of different completion mechanisms for the Virtual Interface (VI) architecture from an application perspective. Based on this comparison we show that the completion queue model offers an optimal way to receive messages in multi-threaded applications under moderate to heavy traffic loads. The application model presented in this paper demonstrates efficient ways of using the VI interface. Naresh Patel, Hari Sivaraman |
CLUSTER | 1 |