- Titel
- Continuous Integration for Cloud-Based Swarm Farming Applications
- Zitierfähige Url:
- https://nbn-resolving.org/urn:nbn:de:bsz:ch1-qucosa2-1043565
- Schriftenreihe
- Chemnitzer Informatik-Berichte
- Bandnummer
- CSR-26-02
- Datum der Einreichung
- 27.10.2025
- ISSN
- 0947-5125
- DOI
- https://doi.org/10.60687/2026-0092
- Abstract (EN)
- The fast development of Autonomous Driving Systems (ADS) is of great challenge when implemented in multi-agent systems like agricultural swarms. The problem is to ensure reliability, stability and performance in case there are new software versions that are being released regularly. Conventional Continuous Integration (CI) processes execute unit tests, integration tests, linting and other tests, but fail to address the complexity of such multi-agent systems, such as asynchronous communication, data-intensive processes and resource management. This thesis fills that gap with designing and evaluating a Continuous Integration system, specifically for cloud-based swarm farming applications. The system is based on the microservice architecture of the helyOS framework. It is supported by a set of automated pipelines that are integrated within a simulated multi-agent environment. This results in a strict performance benchmarking, to ensure system behaviour under varying workloads of various metrics of interest, which are typically latency, scalability and resource efficiency. The results suggest that the Continuous Integration (CI) system will be able to identify early integration issues and performance bottlenecks and guarantee considerable improvement of reliability and stability of the developmental life cycles. Ultimately, this work constitutes a practical and replicable blueprint of Continuous Integration and Continuous Deployment (CI/CD) that is needed to make the deployment of autonomous technologies to complex and distributed environments safe and scalable.
- Andere Ausgabe
- Link: https://www.tu-chemnitz.de/informatik/service/ib/
- Freie Schlagwörter (EN)
- Continuous Integration & Deployment, Cloud Computing, Swarm Robotics, Performance Benchmarking, Autonomous Systems
- Klassifikation (DDC)
- 000
- Normschlagwörter (GND)
- Cloud Computing, Benchmarking, Mehrrobotersystem
- GutachterIn
- Dr. Shadi Saleh
- Dr. Carlos Eduardo Viol Barbosa
- Nils Dunkelberg
- BetreuerIn Hochschule / Universität
- Prof. Dr. Wolfram Hardt
- Den akademischen Grad verleihende / prüfende Institution
- Technische Universität Chemnitz, Chemnitz
- Version / Begutachtungsstatus
- angenommene Version / Postprint / Autorenversion
- URN Qucosa
- urn:nbn:de:bsz:ch1-qucosa2-1043565
- Veröffentlichungsdatum Qucosa
- 06.05.2026
- Dokumenttyp
- Masterarbeit / Staatsexamensarbeit
- Sprache des Dokumentes
- Englisch
- Lizenz / Rechtehinweis
