Reckon-ing Kubernetes at the Edge using Emulated Clusters

Kubernetes is the industry standard cluster orchestrator and it (or its derivatives) have been proposed for orchestrating edge network resources as used in, e.g., IOT deployments. The limited resources and unreliable connectivity in edge environments present challenges to orchestrators including K8s. Their impact is typically studied through emulation on cloud resources but these are difficult to control and highly variable in performance. We present Reckon-K8s, a single-host container-based emulator of Kubernetes clusters over a configurable virtual network. We validate its design and implementation via calibration against a (small) physical cluster, and use it to demonstrate how cluster topology and network conditions influence performance in edge scenarios.

Authors

Institutions

Publication Details

Published
2025-03-27
DOI
https://doi.org/10.1145/3719159.3721222
Citations
1
Primary Topic
Software-Defined Networks and 5G
Type
article
Field-Weighted Citation Impact
1.49
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Reckon-ing Kubernetes at the Edge using Emulated Clusters

Alessandro Sassi, Richard Mortier, Chris Jensen
1 citations
Software-Defined Networks and 5G
1.49
article

Reckon-ing Kubernetes at the Edge using Emulated Clusters

Alessandro Sassi, Richard Mortier, Chris Jensen
article en
1 citations

Abstract

Kubernetes is the industry standard cluster orchestrator and it (or its derivatives) have been proposed for orchestrating edge network resources as used in, e.g., IOT deployments. The limited resources and unreliable connectivity in edge environments present challenges to orchestrators including K8s. Their impact is typically studied through emulation on cloud resources but these are difficult to control and highly variable in performance. We present Reckon-K8s, a single-host container-based emulator of Kubernetes clusters over a configurable virtual network. We validate its design and implementation via calibration against a (small) physical cluster, and use it to demonstrate how cluster topology and network conditions influence performance in edge scenarios.

University of Cambridge (GB), Microsoft Research (United Kingdom) (GB), Politecnico di Milano (IT)
Openalex Percentile: Top 19%
Software-Defined Networks and 5G
1.49
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Reckon-ing Kubernetes at the Edge using Emulated Clusters — Alessandro Sassi, Richard Mortier, et al. · (2025) | TGRS Research Map | TGRS