Design and Implementation of a Strong Representation System for Network Policies
Design and Implementation of a Strong Representation System for Network Policies
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DOI：
10.1109/icccn54977.2022.9868871
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发表时间：
2022-07
期刊：
影响因子：
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通讯作者：
Fangping Lan;Sanchari Biswas;Bin Gui;Jie Wu;Anduo Wang
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文献类型：
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作者：
Fangping Lan;Sanchari Biswas;Bin Gui;Jie Wu;Anduo Wang
当今计算机联网中的策略信息，例如在由自主网络独立设置的软件定义网络(以下称为SDN)或边界网关协议(以下称为BGP)配置上运行的控制器程序的可达性目标，很难管理。这与在允许轻松访问的数据库中结构化的关系数据形成鲜明对比。本文提出的问题是，为什么我们不能(或如何能够)将网络策略转换为关系数据。这种方法的一个困难是，策略并不总是转换为明确的网络快照，而是只有在我们包括它承认的所有可能的网络状态时才能完全描述。我们提出的关系策略，虽然能够以与单个网络状态完全相同的方式表示和操作网络状态集，但形成一个强大的表示系统，并使用通常的结构化查询语言(以下称为SQL)接口准确地捕获策略中的信息。我们展示了与关系数据库一样，关系策略如何提高应用程序生产率并实现快速创新，使我们能够扩展数据库社区开发的优秀解决方案，以协调多个数据源，以应对分布式网络环境中自主决策的长期挑战和新机遇。通过对合成策略和现实网络拓扑的评估，证明了关系策略的可行性。
Policy information in computer networking today, such as reachability objectives of a controller program running on a Software Defined Network (henceforth referred to as SDN) or Border Gateway Protocol (henceforth referred to as BGP) configurations independently set by autonomous networks, are hard to manage. This is in sharp contrast to the relational data structured in a database that allows easy access. This paper asks why cannot (or how can) we turn network policies into relational data. One difficulty to such an approach is that a policy does not always translate to a definite network snapshot, but rather is fully described only when we include all the possible network states it admits. We propose relational policies that, while capable of representing and manipulating sets of network states in exactly the same way as a single one, form a strong representation system and accurately capture the information in a policy with the usual Structured Query Language (henceforth referred to as SQL) interface. We demonstrate how, like relational database improves application productivity and enables rapid innovation, relational policies allow us to extend the elegant solutions that the database community developed, to mediate multiple data sources in order to address long-standing challenges and new opportunities for autonomous policy making in the distributed networking environment. We also show the feasibility of relational policies by evaluation on synthetic policies and realistic network topologies.