NeTS: Small: Collaborative Research: Creating Semantically-Enabled Programmable Networked Systems (SERPENT)

软件定义网络（SDN）是计算机网络行为编程的一种新范式。它为提供新服务和更有效地实现现有功能提供了可能性。SDN使用逻辑集中式控制器的概念，远程管理网络中多个基础设施元素的行为。SDN控制器必须根据从描述网络中各种资源配置的语义丰富的数据中提取的大量技术和业务因素做出有关提供网络服务的决策。SERPENT将开发新的机制来有效地处理这些数据，并使SDN控制器设计的新方法基于对这些数据的查询，就像今天许多web应用程序使用对大型关系数据库的查询来构建一样。通过允许跨多个查询有效处理和分摊计算复杂的步骤，以及集成多种类型的查询约束，该项目将允许创建复杂的控制器行为，将来自多个来源的信息融合在一起，并以无缝的方式结合资源的结构和语义描述，这对未来的数据中心和广域网至关重要。研究人员计划将通过查询重写的本体论查询回答方法和使用路径代数框架解决路径问题的方法引入到一个统一的模型中，该模型将允许具有本体论（语义）和导航约束的查询。第二个主要组成部分将是开发算法和优化框架，用于在这个统一模型上回答复杂的网络查询。SERPENT将以两种方式实现查询优化：(a)问题可以分两个阶段解决，在一个阶段完成繁重的工作，产生的输出可以在效率高得多的第二个阶段重用，用于许多问题。这类似于传统的查询优化，其中使用昂贵的预处理来计算索引，然后使用统计数据来实现高效的查询处理。以这种方法为例，已知的NP困难的子图同构问题已经有了有效的实际实现。(b)为预处理阶段的输出设计和开发有效的表示和索引结构，以及利用表示和数据结构进行有效查询处理的算法。研究人员计划展示这些允许表达结构和语义路径约束的查询机制如何通过将它们合并到现有的SDN控制器中并对其进行评估来创建新的SDN控制器。更广泛的影响。通过将网络数据的管理转换为基于查询的过程，SERPENT将有助于增强现有和未来SDN控制机制的功能，从而消除了为新应用程序重新实现这些机制的需要。相反，他们将利用植根于数据库技术的框架，这些框架可以随着时间的推移而被重用和扩展，就像关系数据库的发展一样。SERPENT整合了研究生的研究和教育，这将有助于发展位于几个学科交叉点的领域：网络管理、语义网和图形数据库数据管理。它将通过生产原型实现来影响SDN研究社区，它将通过将结果转化为GENI测试平台的操作来影响GENI（全球网络创新环境）社区。它将影响其他依赖网络分析并需要在寻路中包含语义约束的领域，如社会和生物网络。

Software-Defined Networking (SDN) is a new paradigm in programming the behavior of computer networks. It opens possibilities for offering novel services and implementing existing functions more efficiently. SDN uses a concept of a logically centralized controller that remotely manages the behavior of multiple infrastructure elements in the network. SDN controllers must make decisions about provisioning network services based on a multitude of technical and business factors drawn from the semantically rich data describing the configuration of various resources in the network. SERPENT will develop novel mechanisms for efficiently handling this data and enabling a new approach to SDN controller design that is based on using queries on this data, same as many web applications today are built using queries on large relational databases. By allowing efficient processing and amortization of computationally complex steps across multiple queries and the integration of many types of query constraints, the project will allow to create complex controller behaviors that fuse together information from multiple sources and combine structural and semantic descriptions of resources in a seamless way, something that would be critical for future datacenter and wide-area networks.The investigators plan to bring the approach of ontological query answering via query rewriting and of solving path problems using a path algebra framework into a unified model that will allow queries with both ontological (semantic) and navigational constraints. The second major component will be developing the algorithmic and optimization framework for answering complex networking queries over this unified model. SERPENT will enable query optimization in two ways: (a) problems can be solved in two phases with the heavy lifting done in one phase producing an output that can be reused for many problems in a much more efficient second phase. This is similar to traditional query optimization where expensive preprocessing is employed to compute indexes, statistics which are then used to enable efficient query processing. Using this approach for example, the subgraph isomorphism problem which is known to be NP Hard has been made to have efficient practical implementations. (b) design and development of efficient representation and indexing structures for the output of the preprocessing phase and algorithms for exploiting the representations and data structures for efficient query processing. The investigators plan to show how these query mechanisms that allow to express both structural and semantic path constraints are used to create novel SDN controllers by incorporating them into existing SDN controllers and evaluating them. Broader Impact. SERPENT will contribute to enhancing the functionality of existing and future SDN control mechanisms by transforming the management of networking data into a query- based processes that will remove the need to reimplement these mechanisms for new applications. Instead they will leverage the framework rooted in database techniques that can be reused and extended over-time, same way relational databases have evolved. SERPENT integrates research and education of graduate students that will help evolve the area that lies at the intersection of several disciplines: network management, Semantic Web and graph database data management. It will impact SDN research community by producing prototype implementations, it will impact GENI (Global Environment for Network Innovations) community by transitioning the results into operations of GENI testbeds. It will impact other domains that rely on network analysis and require the inclusion of semantic constraints in pathfinding like social and biological networks.