SeaNet --基于知识图谱的软件定义网络自治管理
SeaNet -- Towards A Knowledge Graph Based Autonomic Management of Software Defined Networks
摘要：
由人工智能技术驱动的自动网络管理已经被广泛讨论了几十年。然而，目前的报告主要集中在理论的建议和架构设计，在现实生活中的网络上的实际实现的工作还没有出现。本文提出了我们的努力实现知识图谱驱动的方法，自主网络管理软件定义网络（SDN），称为SeaNet。在ToCo本体的驱动下，SeaNet基于Mininet（SDN仿真器）重新编程。它由三个核心组件组成：知识图谱生成器、SPARQL引擎和网络管理API。知识图谱生成器将电信网络管理任务中的知识表示为形式化表示的本体驱动模型。网络管理API可以将专家经验和网络管理规则形式化为知识图谱，通过SPARQL引擎自动推理，将技术细节打包，并向用户展示与技术无关的接口。实验进行了评估建议的工作，通过比较与商业SDN控制器Ryu实现相同的语言Python。评估结果表明，在大多数情况下，SeaNet比Ryu快得多，SeaNet代码明显更紧凑。由于采用了RDF推理，SeaNet在不同尺度的知识图谱上都能达到O（1）的时间复杂度，而传统的数据库最高可以达到O（nlogn）。通过开发的网络管理API，SeaNet使研究人员能够在自己的SDN上开发语义智能应用程序。
英文摘要：
Automatic network management driven by Artificial Intelligent technologies has been heatedly discussed over decades. However, current reports mainly focus on theoretic proposals and architecture designs, works on practical implementations on real-life networks are yet to appear. This paper proposes our effort toward the implementation of knowledge graph driven approach for autonomic network management in software defined networks (SDNs), termed as SeaNet. Driven by the ToCo ontology, SeaNet is reprogrammed based on Mininet (a SDN emulator). It consists three core components, a knowledge graph generator, a SPARQL engine, and a network management API. The knowledge graph generator represents the knowledge in the telecommunication network management tasks into formally represented ontology driven model. Expert experience and network management rules can be formalized into knowledge graph and by automatically inferenced by SPARQL engine, Network management API is able to packet technology-specific details and expose technology-independent interfaces to users. The Experiments are carried out to evaluate proposed work by comparing with a commercial SDN controller Ryu implemented by the same language Python. The evaluation results show that SeaNet is considerably faster in most circumstances than Ryu and the SeaNet code is significantly more compact. Benefit from RDF reasoning, SeaNet is able to achieve O(1) time complexity on different scales of the knowledge graph while the traditional database can achieve O(nlogn) at its best. With the developed network management API, SeaNet enables researchers to develop semantic-intelligent applications on their own SDNs.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
