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.

软件定义的网络（SDN）是编程计算机网络行为的新范式。它为提供新颖服务和更有效地实施现有功能提供了可能性。 SDN使用逻辑集中式控制器的概念，该控制器可以远程管理网络中多个基础架构元素的行为。 SDN控制器必须根据从语义上丰富的数据中得出的多种技术和业务因素做出决定，这些技术和业务因素描述了网络中各种资源的配置。 Serpent将开发出新的机制，以有效地处理此数据并启用基于此数据上使用查询的新方法来进行SDN控制器设计，与当今许多Web应用程序相同，与当今的许多Web应用程序相同，是使用大型关系数据库上的查询构建的。通过允许在多个查询中有效地处理和摊销计算复杂的步骤以及许多类型的查询约束的集成，我们的项目将允许创建复杂的控制器行为，从多个来源融合信息，并将资源的结构和语义描述融合在一起，并将其结合在无缝的无缝中对于未来的数据中心和广阔区域网络至关重要的方式。我们计划通过查询重写来实现本体论查询答案的方法，并使用路径代数框架解决统一模型，以解决两个本体论的查询（语义）和导航约束。第二个主要组件将开发算法和优化框架，以回答此统一模型的复杂网络查询。 Serpent将通过两种方式启用查询优化：（a）可以在两个阶段解决问题，而在一个阶段进行繁重的提升可以产生输出，该输出可以在更有效的第二阶段中为许多问题重复使用。这类似于传统的查询优化，该优化使用昂贵的预处理来计算索引，统计信息随后用于启用有效的查询处理。例如，使用这种方法，已知很难进行NP的子图同构问题具有有效的实际实现。 （b）设计和开发有效的表示和索引结构，用于用于利用表示和数据结构以进行有效查询处理的预处理阶段和算法的输出。我们将展示这些查询机制如何使用结构和语义路径约束来通过将它们纳入现有SDN控制器并评估它们来创建新型SDN控制器。 更广泛的影响。蛇将通过将网络数据的管理转换为基于查询的过程，从而有助于增强现有和未来的SDN控制机制的功能，从而消除为新应用程序重新实现这些机制的需求。相反，他们将利用植根于数据库技术的框架，这些框架可以重复使用并延长加长，而关系数据库也会发展。 Serpent整合研究生的研究和教育，这些研究和教育将有助于发展在几个学科交集的领域：网络管理，语义网络和图形数据库数据管理。它将通过产生原型实施来影响SDN研究社区，它将通过将结果转换为Geni Testbends的运营来影响GENI（全球网络创新）社区。它将影响依赖网络分析的其他领域，并需要在社交和生物网络等路径探索中包含语义限制。