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Eric Caron

dblp:364/7066 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2023
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 1 · 1 first-author · 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 networks
1 paper
Edge and fog computing · 100%
Software engineering, system software, and programming languages
1 paper
Services computing and microservices · 100%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Cloud and datacenter computing · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Edge and fog computing
resource management
0.712023
The Nanoservices Framework: Co-Locating Microservices in the Cloud-Edge Continuum · ICNP 2023
Services computing and microservices › microservice architecture
microservice deployment
0.712023
The Nanoservices Framework: Co-Locating Microservices in the Cloud-Edge Continuum · ICNP 2023
Cloud and datacenter computing › virtualization
containerization
0.212023
The Nanoservices Framework: Co-Locating Microservices in the Cloud-Edge Continuum · ICNP 2023

Methods — techniques the papers use, named apart from their topics

container co-location · 2.0
YearPublicationVenuePosition
2023 The Nanoservices Framework: Co-Locating Microservices in the Cloud-Edge Continuum
abstract
Today, the microservices paradigm has emerged as one of the most widely adopted patterns to develop, package, and deploy software on a large scale. However, as they were originally designed for the cloud, the direct application of microservices DevOps practices to resource-constrained environments like the Edge may not be optimal. Specifically, deploying each piece of software as an individual microservice may result in a significant resource footprint (e.g., storage space and network bandwidth related to managing base images, CPU, and memory). In this work, we explore the concept of opportunistically grouping microservice code within the same container to reduce resource footprint when deploying multiple microservices at the Edge. To materialize this concept, we present the N anoservices framework: a framework that formalizes and provides practical means for developers to build and deploy groups of microservices on the same container (a.k.a., Nanoservices). Our early results show that with Nanoservices we can achieve a significant resource footprint reduction (base image storage, CPU, memory) with minimal effort from the developer's viewpoint.
Eric Caron, Raúl Gracia Tinedo
ICNP1