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
With the help of lightweight virtualization technology such as containers, the spaceborne virtualization platform encapsulates computing tasks into containers to form task containers, so as to achieve efficient utilization of resources. However, the platform's task container scheduling problem is a difficult problem that needs to be solved urgently. In this paper, we aim at this problem by establishing a multi-pass scheduling model for separable container tasks based on non-blocking communication mode. On the basis of this model, we propose a new scheduling algorithm, aiming at determining the optimal processor scheduling sequence and scheduling times. The algorithm combines the concept of divisible task container and multi-pass scheduling. By decomposing the task into executable subtasks, and performing task allocation and processor scheduling in multiple scheduling stages, it can optimize the scheduling order to improve the overall processing efficiency. This algorithm is an improved genetic algorithm that adds the optimization strategy of subpopulation isolation to the traditional genetic algorithm. Its core idea is to improve the performance and effect of the genetic algorithm by introducing the population division strategy into the algorithm process. We verify the effectiveness and convergence of the algorithm through experiments, and the experimental results show that the algorithm makes the task have less completion time.
#Computer science
#Distributed computing
#Fair-share scheduling
#Rate-monotonic scheduling
#Two-level scheduling
#Scheduling (production processes)
#Virtualization
#Dynamic priority scheduling
#Executable
#Fixed-priority pre-emptive scheduling
#Round-robin scheduling
#Algorithm
#Mathematical optimization
#Operating system
#Cloud computing
#Computer network
#Quality of service
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