
함정 폐쇄망 조건을 고려한 LLM 시스템 구축과 운용 시나리오
Ⓒ 2025 Korea Society for Naval Science & Technology
초록
본 논문에서는 해군 함정과 같은 폐쇄망 환경에서 운용 가능한 LLM 시스템 구축 방안을 제안한다. 제한된 연산 자원과 네트워크 단절 조건을 고려하여, MCP(model context protocol)와 RAG(retrieval-augmented generation) 기술을 통합한 아키텍처를 설계하고, 실시간 문서 기반 질의응답이 가능한 프로토타입 시스템을 구현하였다. 또한, 해군 내 운용 시나리오를 기반으로 LLM의 적용 가능성을 확인하였다. 오픈소스 모델 활용을 위한 GPU 자원 분석으로 제한된 하드웨어를 탑재한 함정에서 LLM을 도입하게 되었을 때 참고지표로 활용할 수 있다.
Abstract
This study proposes an LLM system for closed network environments like Navy ships, addressing limited hardware and no-network conditions. By combining MCP and RAG techniques, a prototype for real-time, document-based Q&A was developed and validated through a Navy operational scenario. Additionally, by analyzing GPU resource requirements of open-source LLMs, we provide reference benchmarks for implementing such systems on ships with constrained hardware capabilities.
Keywords:
Closed-Network of Battleship, Large Language Model, Model Context Protocol, Retrieval-augmented Generation, Navy’s Operational Scenarios키워드:
함정 폐쇄망, 거대 언어모델, 모델 컨텍스트 프로토콜, 검색 증강 생성, 해군 운용 시나리오Acknowledgments
이 논문은 2025년도 한국해군과학기술학회 하계학술대회 발표 논문임.
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