Home ›
Entities
› academia
› Optimizing Microservice Deployment in Edge Computing with Large Language Models: Integrating Retrieval Augmented Generation and Chain of Thought Techniques
Optimizing Microservice Deployment in Edge Computing with Large Language Models: Integrating Retrieval Augmented Generation and Chain of Thought Techniques
Research article (Symmetry, 2024) · cited 15× · AI/ML
Optimizing Microservice Deployment in Edge Computing with Large Language Models: Integrating Retrieval Augmented Generation and Chain of Thought Techniques
Summary
Optimizing Microservice Deployment in Edge Computing with Large Language Models: Integrating Retrieval Augmented Generation and Chain of Thought Techniques is a scholarly article[1].
Key Facts
Optimizing Microservice Deployment in Edge Computing with Large Language Models: Integrating Retrieval Augmented Generation and Chain of Thought Techniques's instance of is recorded as scholarly article[2].
References
Programmatic citations — every numbered marker resolves to a verifiable graph row below.
Use these citations when quoting this entity in research, articles, AI prompts, or wherever provenance matters. We aggregate Wikidata + Wikipedia + authoritative open-data sources; the stitched, scored, cross-referenced view is what 4ort.xyz contributes.
APA4ort.xyz Knowledge Graph. (2026). Optimizing Microservice Deployment in Edge Computing with Large Language Models: Integrating Retrieval Augmented Generation and Chain of Thought Techniques. Retrieved May 24, 2026, from https://4ort.xyz/entity/optimizing-microservice-deployment-in-edge-computing-with-large-language-models-integrating-retrieval-augmented-generati
MLA“Optimizing Microservice Deployment in Edge Computing with Large Language Models: Integrating Retrieval Augmented Generation and Chain of Thought Techniques.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/optimizing-microservice-deployment-in-edge-computing-with-large-language-models-integrating-retrieval-augmented-generati.
BibTeX@misc{4ortxyz_optimizing-microservice-deployment-in-edge-computing-with-large-language-models-integrating-retrieval-augmented-generati_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Optimizing Microservice Deployment in Edge Computing with Large Language Models: Integrating Retrieval Augmented Generation and Chain of Thought Techniques}}, year = {2026}, url = {https://4ort.xyz/entity/optimizing-microservice-deployment-in-edge-computing-with-large-language-models-integrating-retrieval-augmented-generati}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Optimizing Microservice Deployment in Edge Computing with Large Language Models: Integrating Retrieval Augmented Generation and Chain of Thought Techniques — https://4ort.xyz/entity/optimizing-microservice-deployment-in-edge-computing-with-large-language-models-integrating-retrieval-augmented-generati (retrieved 2026-05-24)