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Kevin Houck

dblp:203/0879 · DBLP profile ↗
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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

TopicWeightPapersLastEvidence papers
Cloud and datacenter computing › container orchestration
container provisioning
0.312018
SOCK: Rapid Task Provisioning with Serverless-Optimized Containers · USENIX ATC 2018
Cloud and datacenter computing
serverless computing
0.312018
SOCK: Rapid Task Provisioning with Serverless-Optimized Containers · USENIX ATC 2018
Operating systems › virtualization
containers
0.112018
SOCK: Rapid Task Provisioning with Serverless-Optimized Containers · USENIX ATC 2018
YearPublicationVenuePosition
2021 Atoll: A Scalable Low-Latency Serverless Platform
abstract
With 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
SoCC3
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 ATC4