Publications
2026
Schultheis, Alexander; Jilg, David; Traphöner, Ralph; Schander, Roman; Bergmann, Ralph
Applying Distributed Case-Based Reasoning in the Edge-Cloud Continuum Proceedings Article
In: Artificial Intelligence XLIII - 46th SGAI International Conference on Artificial Intelligence, AI 2026, Cambridge, UK, December 15-17, 2026, Proceedings, Springer, 2026.
Abstract | BibTeX | Tags: Distributed Case-Based Reasoning, Edge-Cloud Continuum, Load Balancing, ProCAKE
@inproceedings{SchultheisJTSB2026,
title = {Applying Distributed Case-Based Reasoning in the Edge-Cloud Continuum},
author = {Alexander Schultheis and David Jilg and Ralph Traphöner and Roman Schander and Ralph Bergmann},
year = {2026},
date = {2026-01-01},
booktitle = {Artificial Intelligence XLIII - 46th SGAI International Conference on Artificial Intelligence, AI 2026, Cambridge, UK, December 15-17, 2026, Proceedings},
publisher = {Springer},
series = {Lecture Notes in Computer Science},
abstract = {Case-Based Reasoning (CBR) is well suited for recurring but context-dependent industrial decisions and is therefore a promising artificial intelligence approach for the Edge-Cloud Continuum (ECC). The ECC denotes a distributed infrastructure in which tasks are placed dynamically across resource-constrained nodes near data sources and centralized cloud resources. However, the systematic transfer of CBR to distributed edge-cloud settings has received little attention. This paper presents a project-grounded approach for operationalizing CBR in the ECC. Based on experience from the EASY project and exchanges with industry and research partners, industrial application scenarios are structured, load balancing metrics are adopted, and an architecture for distributed CBR is introduced. The paper further discusses opportunities, challenges, and cross-organizational perspectives. To demonstrate technical feasibility, a ProCAKE-based prototype is implemented and investigated in a distributed case base scenario. The results demonstrate that distributed CBR in the ECC is technically feasible, while highlighting the need to assess potential runtime benefits in relation to case base characteristics, heterogeneous processing capabilities, and distribution overhead.},
keywords = {Distributed Case-Based Reasoning, Edge-Cloud Continuum, Load Balancing, ProCAKE},
pubstate = {published},
tppubtype = {inproceedings}
}
Case-Based Reasoning (CBR) is well suited for recurring but context-dependent industrial decisions and is therefore a promising artificial intelligence approach for the Edge-Cloud Continuum (ECC). The ECC denotes a distributed infrastructure in which tasks are placed dynamically across resource-constrained nodes near data sources and centralized cloud resources. However, the systematic transfer of CBR to distributed edge-cloud settings has received little attention. This paper presents a project-grounded approach for operationalizing CBR in the ECC. Based on experience from the EASY project and exchanges with industry and research partners, industrial application scenarios are structured, load balancing metrics are adopted, and an architecture for distributed CBR is introduced. The paper further discusses opportunities, challenges, and cross-organizational perspectives. To demonstrate technical feasibility, a ProCAKE-based prototype is implemented and investigated in a distributed case base scenario. The results demonstrate that distributed CBR in the ECC is technically feasible, while highlighting the need to assess potential runtime benefits in relation to case base characteristics, heterogeneous processing capabilities, and distribution overhead.