Poster: KUT: Towards Lightweight On-path Network Assessment for Edge Orchestration

Conference Paper (2025)
Author(s)

Wei Geng (Technische Universität München)

Oguz Kagan Altas (Technische Universität München)

David Guzman (Technische Universität München)

Giovanni Bartolomeo (Technische Universität München)

Nitinder Mohan (TU Delft - Networked Systems)

Joerg Ott (Technische Universität München)

Research Group
Networked Systems
DOI related publication
https://doi.org/10.1145/3765515.3771746 Final published version
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Publication Year
2025
Language
English
Research Group
Networked Systems
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository as part of the Taverne amendment. More information about this copyright law amendment can be found at https://www.openaccess.nl. Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.
Pages (from-to)
9-11
Publisher
ACM
ISBN (electronic)
9798400721915
Event
21st International Conference on Emerging Networking EXperiments and Technologies, CoNEXT 2025 (2025-12-01 - 2025-12-04), Hong Kong, Hong Kong
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42
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Abstract

Edge computing orchestration faces significant challenges due to resource constraints, highly distributed topologies, and dynamic network conditions. The discrepancy between theoretical and actual runtime performance often leads to suboptimal deployment decisions. This discrepancy is severe in clustered deployments, as existing tools either saturate network links during testing or lack proactive assessment capabilities. None of these approaches accurately predicts service co-locating compatibility in real-world scenarios. We present KUT (Konnectivity Under Test), a lightweight network assessment framework designed specifically for edge environments, combining service-specific traffic simulation with periodical monitoring to provide accurate compatibility assessments without starving co-located services. KUT enables periodic background assessments that inform orchestration decisions while consuming minimal resources.

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