Demo Data from VLDB 2026 / reviewers in the wild / expert
Kevin Houck
dblp:203/0879
· DBLP profile ↗
2ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 2 · 1 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
1 paper |
Cloud and datacenter computing · 100% | |
| Software engineering, system software, and programming languages
1 paper |
Operating systems · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Cloud and datacenter computing › container orchestration
container provisioning |
0.3 | 1 | 2018 | SOCK: Rapid Task Provisioning with Serverless-Optimized Containers · USENIX ATC 2018 |
Cloud and datacenter computing
serverless computing |
0.3 | 1 | 2018 | SOCK: Rapid Task Provisioning with Serverless-Optimized Containers · USENIX ATC 2018 |
Operating systems › virtualization
containers |
0.1 | 1 | 2018 | SOCK: Rapid Task Provisioning with Serverless-Optimized Containers · USENIX ATC 2018 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Atoll: A Scalable Low-Latency Serverless PlatformabstractWith user-facing apps adopting serverless computing, good latency performance of serverless platforms has become a strong fundamental requirement. However, it is difficult to achieve this on platforms today due to the design of their underlying control and data planes that are particularly ill-suited to short-lived functions with unpredictable arrival patterns. We present Atoll, a serverless platform, that overcomes the challenges via a ground-up redesign of the control and data planes. In Atoll, each app is associated with a latency deadline. Atoll achieves its per-app request latency goals by: (a) partitioning the cluster into (semi-global scheduler, worker pool) pairs, (b) performing deadline-aware scheduling and proactive sandbox allocation, and (c) using a load balancing layer to do sandbox-aware routing, and automatically scale the semi-global schedulers per app. Our results show that Atoll reduces missed deadlines by ~66x and tail latencies by ~3x compared to state-of-the-art alternatives. Arjun Singhvi, Arjun Balasubramanian, Kevin Houck, Mohammed Danish Shaikh, Shivaram Venkataraman, Aditya Akella |
SoCC | 3 |
| 2018 | SOCK: Rapid Task Provisioning with Serverless-Optimized Containers
Edward Oakes, Leon Yang, Dennis Zhou, Kevin Houck, Tyler Caraza-Harter, Andrea C. Arpaci-Dusseau, Remzi H. Arpaci-Dusseau |
USENIX ATC | 4 |