Demo Data from SIGIR 2026 / reviewers in the wild / expert
Francois Richard
dblp:40/175
· DBLP profile ↗
4ranked-venue papers
0as first author
3since 2021 · last 2023
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Software engineering, systems software and programming languages · 4 · 3 since 2021
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
4 papers |
Distributed systems · 56% Cloud and datacenter computing · 30% Storage systems · 15% | |
| Computer networks
1 paper |
Topics — the 7 heaviest of 10, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Distributed systems
fault tolerance |
0.7 | 1 | 2023 | Defcon: Preventing Overload with Graceful Feature Degradation · OSDI 2023 |
Distributed systems › fault tolerance › resilience
graceful degradation |
0.7 | 1 | 2023 | Defcon: Preventing Overload with Graceful Feature Degradation · OSDI 2023 |
Cloud and datacenter computing
datacenter storage |
0.5 | 1 | 2021 | Log-structured Protocols in Delos · SOSP 2021 |
Storage systems › distributed storage
shared log |
0.5 | 1 | 2021 | Log-structured Protocols in Delos · SOSP 2021 |
Distributed systems › replication
state machine replication |
0.5 | 1 | 2021 | Log-structured Protocols in Delos · SOSP 2021 |
Distributed systems
consensus |
0.4 | 1 | 2020 | Virtual Consensus in Delos · OSDI 2020 |
Storage systems
key-value storage |
0.1 | 1 | 2021 | Log-structured Protocols in Delos · SOSP 2021 |
Methods — techniques the papers use, named apart from their topics
state machine replication · 0.5leasing · 0.5batching · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Defcon: Preventing Overload with Graceful Feature Degradation
Justin Meza, Thote Gowda, Ahmed Eid, Tomiwa Ijaware, Dmitry Chernyshev, Md Nazim Uddin, Rohan Das 0003, Chad Nachiappan, Sari Tran, Shuyang Shi, Tina Luo, David Ke Hong, Sankaralingam Panneerselvam, Hans Ragas, Svetlin Manavski, Francois Richard |
OSDI | 18 |
| 2022 | Owl: Scale and Flexibility in Distribution of Hot Content
Jason Flinn, Xianzheng Dou, Arushi Aggarwal, Alex Boyko, Francois Richard, Eric Sun, Wendy Tobagus, Nick Wolchko |
OSDI | 5 |
| 2021 | Log-structured Protocols in DelosabstractDevelopers have access to a wide range of storage APIs and functionality in large-scale systems, such as relational databases, key-value stores, and namespaces. However, this diversity comes at a cost: each API is implemented by a complex distributed system that is difficult to develop and operate. Delos amortizes this cost by enabling different APIs on a shared codebase and operational platform. The primary innovation in Delos is a log-structured protocol: a fine-grained replicated state machine executing above a shared log that can be layered into reusable protocol stacks under different databases. We built and deployed two production databases using Delos at Facebook, creating nine different log-structured protocols in the process. We show via experiments and production data that log-structured protocols impose low overhead, while allowing optimizations that can improve latency by up to 100X (e.g., via leasing) and throughput by up to 2X (e.g., via batching). Mahesh Balakrishnan 0001, Ahmed Jafri, Suyog Mapara, David Geraghty, Jason Flinn, Vidhya Venkat, Ivailo Nedelchev, Santosh Ghosh, Mihir Dharamshi, Jingming Liu, Filip Gruszczynski, Rounak Tibrewal, Ali Zaveri, Rajeev Nagar, Ahmed Yossef, Francois Richard, Yee Jiun Song |
SOSP | 18 |
| 2020 | Virtual Consensus in Delos
Mahesh Balakrishnan 0001, Jason Flinn, Mihir Dharamshi, Ahmed Jafri, Santosh Ghosh, Hazem Hassan, Aaryaman Sagar, Rhed Shi, Jingming Liu, Filip Gruszczynski, Xianan Zhang, Huy Hoang, Ahmed Yossef, Francois Richard, Yee Jiun Song |
OSDI | 16 |