인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Abstract With the development of cloud-edge collaborative computing, cloud computing has become crucial in data analysis and data processing. OpenStack and Docker are important components of cloud computing, and the integration of the two has always attracted widespread attention in industry. The scheduling mechanism adopted by the existing fusion solution uses a uniform resource weight for all containers, and the computing nodes resources on the cloud platform is unbalanced under differentiated resource requirements of the containers. Therefore, considering different network communication qualities, a load-balancing Docker scheduling mechanism based on OpenStack is proposed to meet the needs of various resources (CPU, memory, disk, and bandwidth) of containers. This mechanism uses the precise limitation strategy for container resources and a centralized strategy for container resources as the scheduling basis, and it generates exclusive weights for containers through a filtering stage, a weighing stage based on weight adaptation, and a non-uniform memory access (NUMA) lean stage. The experimental results show that, compared with Nova-docker and Yun, the proposed mechanism reduces the resource load imbalance within a node by 57.35% and 59.00% on average, and the average imbalance between nodes is reduced by 53.53% and 50.90%. This mechanism can also achieve better load balancing without regard to bandwidth.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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