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

NetS：小型：协作研究：创建语义支持的可编程网络系统 (SERPENT)

• 批准号: 1526113
• 负责人: Kemafor Anyanwu-Ogan
• 金额: $ 27.83万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-10-01 至 2021-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1526113&HistoricalAwards=false
• 关键词: NeTS; Small; Collaborative; Research; Creating

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, our 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.We 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. We will 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.

软件定义网络 (SDN) 是计算机网络行为编程的新范式。它为提供新颖的服务和更有效地实施现有功能提供了可能性。 SDN 使用逻辑集中控制器的概念，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数据中提取的多种技术和业务因素来做出有关配置网络服务的决策。 SERPENT 将开发新颖的机制来有效处理这些数据，并启用一种基于对这些数据进行查询的 SDN 控制器设计新方法，就像当今的许多 Web 应用程序是使用对大型关系数据库的查询构建的一样。通过允许跨多个查询的计算复杂步骤的高效处理和摊销以及多种类型查询约束的集成，我们的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。这对于未来的数据中心和广域网至关重要。我们计划将通过查询重写来回答本体查询的方法以及使用路径代数框架解决路径问题的方法引入一个统一的模型中，该模型将允许使用本体进行查询（语义）和导航限制。第二个主要部分将是开发算法和优化框架，用于通过这个统一模型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，其中一个阶段完成的繁重工作会产生一个输出，该输出可以在更高效的第二阶段中重复用于许多问题。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和统计信息，然后使用它们来实现高效的查询处理。例如，使用这种方法，已知为 NP Hard 的子图同构问题已得到有效的实际实现。 (b) 设计和开发用于预处理阶段输出的高效表示和索引结构以及利用表示和数据结构进行高效查询处理的算法。我们将展示如何使用这些允许表达结构和语义路径约束的查询机制，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颖的 SDN 控制器。 更广泛的影响。 SERPENT 将通过将网络数据管理转变为基于查询的流程来增强现有和未来 SDN 控制机制的功能，从而无需为新应用程序重新实现这些机制。相反，他们将利用植根于数据库技术的框架，这些技术可以随着时间的推移而重复使用和扩展，就像关系数据库的发展方式一样。 SERPENT 整合了研究生的研究和教育，这将有助于发展位于多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。它将通过产生原型实现来影响 SDN 研究社区，它将通过将结果转化为 GENI 测试平台的运营来影响 GENI（全球网络创新环境）社区。它将影响依赖网络分析并需要在寻路中包含语义约束的其他领域，例如社交和生物网络。