Demo Data from EDBT 2026 / reviewers in the wild / expert
Binu John
dblp:63/4340
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2016
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 1Software engineering, systems software and programming languages · 1
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 · 75% Cloud and datacenter computing · 25% | |
| Computer networks
1 paper |
Datacenter networks · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cloud and datacenter computing
datacenter storage |
0.2 | 1 | 2016 | Flash storage disaggregation · EuroSys 2016 |
Storage systems › distributed storage
disaggregated storage |
0.2 | 1 | 2016 | Flash storage disaggregation · EuroSys 2016 |
Storage systems › flash and SSD › flash memory
flash storage |
0.2 | 1 | 2016 | Flash storage disaggregation · EuroSys 2016 |
Storage systems › networked storage › storage networking
remote flash access |
0.2 | 1 | 2016 | Flash storage disaggregation · EuroSys 2016 |
Methods — techniques the papers use, named apart from their topics
resource-efficient scale-out · 0.5remote PCIe flash access · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2016 | Flash storage disaggregationabstractPCIe-based Flash is commonly deployed to provide datacenter applications with high IO rates. However, its capacity and bandwidth are often underutilized as it is difficult to design servers with the right balance of CPU, memory and Flash resources over time and for multiple applications. This work examines Flash disaggregation as a way to deal with Flash overprovisioning. We tune remote access to Flash over commodity networks and analyze its impact on workloads sampled from real datacenter applications. We show that, while remote Flash access introduces a 20% throughput drop at the application level, disaggregation allows us to make up for these overheads through resource-efficient scale-out. Hence, we show that Flash disaggregation allows scaling CPU and Flash resources independently in a cost effective manner. We use our analysis to draw conclusions about data and control plane issues in remote storage. Ana Klimovic, Christoforos E. Kozyrakis, Eno Thereska, Binu John |
EuroSys | 4 |
| 2003 | Designing a Web Service Benchmark
Shanti Subramanyam, Akara Sucharitakul, Biswadeep Nag, Ramesh Ramachandran, Rob Ruyak, Lalit Mathwani, Tony Zhang, Binu John, Prashant Srinivasan, Keng-Tai Ko, Debabrata Sarkar |
ICWS | 8 |