知识图驱动的计算能力网络自动调度技术

Yanheng Bi, Yingchi Long, Yanzheng Jin, Shengwen Zheng, Huaiyuan Liu, Hongzhi Wang
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引用次数: 2

摘要

近年来,由于数据爆炸,人工智能行业对计算资源的需求十分迫切,这推动了运营商构建新时代的计算能力网络。从云网络时代到今天的计算能力网络,对计算服务的效率和安全性提出了更严格的要求。尽管有计算能力调度技术,如按需边缘计算和高效计算优先网络,但对图的知识图技术的探索较少。知识图作为一种非常容易表达图中节点之间关系的新技术,在表达计算能力网络中计算节点的特征信息方面具有天然的优势。为此,提出了一种新的计算能力网络体系结构的知识图表示方法。并采用知识表示的方法构建了计算能力网络的知识图。提出的知识驱动方法基于构建的知识图自动执行计算能力网络的调度任务。与目前的计算能力网络调度技术不同,随着知识的不断增加,该模型在理论上会变得越来越高效和准确。
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Automatic Scheduling Technology of Computing Power Network Driven by Knowledge Graph
In recent years, the demand for computing resources of AI industry is urgent because of the data explosion, which promoted the construction of computing power networks in the new era for operators. From the cloud network era to today's computing power network, stricter requirements are proposed to ensure the efficiency and security of computing services. Despite computing power scheduling technologies such as on-demand edge computing and efficient compute first network, knowledge graph techniques for graphs are less explored. As a new technology that can express the relationship between nodes in the graph extremely easily, knowledge graph has a natural advantage in expressing feature information of computing nodes in computing power network. Therefore, a novel knowledge graph representation for the architecture of computing power networks is proposed. And the knowledge graph of the computing power network is constructed by using the knowledge representation method. The scheduling tasks of computing power network is automatically executed by the proposed knowledge driven method based on the constructed knowledge graph. Different with the current scheduling technology of computing power network, the model will theoretically become more and more efficient and accurate with continuously addition of knowledge.
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