Model-based Analysis of Next-Generation Networks

下一代网络基于模型的分析

• 批准号: 397973531
• 负责人: Professor Dr.-Ing. Georg Carle
• 金额: --
• 依托单位: Lehrstuhl für Kommunikationsnetze (LKN)
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2018
• 资助国家: 德国
• 起止时间: 2017-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/397973531?language=en
• 关键词: Model; based; Analysis; Next; Generation

It is foreseen, that new paradigms in computer networking like Network Function Virtualization (NFV), Network Virtualization (NV) and Software Defined Networking (SDN), will increase the flexibility and openness of modern communication infrastructure. The new approaches will enable virtualization of network functions (NFV), network slicing (NV) and a (logically) centralized control of the network (SDN), such that functionality can be implemented in a physically decoupled way, e.g. running in a data center. SDN enables novel approaches to analyze and control the traffic in the network, however, requiring a deep understanding of the underlying hardware. While the packet processing pipeline of well-designed, specialized hardware is specified in detail, virtualized software on commodity hardware is more difficult to tackle. On the other hand, the additional degrees of freedom enabled by virtualizing network functions (NFV), such as custom packet processing pipelines and dynamic placement, create new possibilities for optimization.This project aims to evaluate, combine, and enhance performance models of networks and their components concerned with packet processing. The performance assessment of novel networks requires suitable modeling tools, e.g. to represent interaction on the control plane or take software-based packet processing into account. New models are also required to account for changes in the networking hardware that describe the effects of limiting factors like CPU interconnects or the bandwidth of memory, PCIe, or Ethernet. We aim to combine models, that describe individual effects, into larger entities that allow the modeling of complex packet processing tasks.ModANet covers various methods for performance analysis, e.g. resource-based models, models based on Network Calculus, and simulations. We plan to build a framework for model evaluation, which allows for automated determination of the quality and scope of models, thus enables covering a large parameter space. We plan to automate the calibration and evaluation of the analyzed models using machine learning techniques. We also aim to evaluate the modeling approaches with regard to their complexity to obtain feasible models.The outcomes of the project should provide a deep understanding of the characteristics of the different processing pipelines in SDN-based networks. Considering separate packet processing steps in network nodes allows to make reliable statements about the performance of composed packet processing chains. Furthermore, the enhanced configuration possibilities lead to new optimizations.

可以预见的是，计算机网络中的新范例（例如网络函数虚拟化（NFV），网络虚拟化（NV）和软件定义的网络（SDN））将提高现代通信基础架构的灵活性和开放性。新方法将实现网络函数（NFV），网络切片（NV）和A（逻辑上）集中式网络（SDN）的虚拟化，因此可以以物理脱钩的方式实现功能，例如。在数据中心运行。 SDN可以采用新颖的方法来分析和控制网络中的流量，但是需要对基础硬件有深入的了解。详细指定了精心设计，专业硬件的数据包处理管道，但有关商品硬件的虚拟化软件更难解决。另一方面，通过虚拟化网络功能（NFV）启用了其他自由度他们的组件与数据包处理有关。新型网络的性能评估需要合适的建模工具，例如表示控制平面上的交互或考虑基于软件的数据包处理。还需要新模型来说明网络硬件的变化，以描述CPU互连或内存，PCIE或以太网的限制因素的影响。我们的目标是将描述个体效应的模型结合到允许复杂数据包处理任务建模的较大实体中。Modanet涵盖了各种绩效分析的方法，例如基于资源的模型，基于网络演算的模型和仿真。我们计划建立一个用于模型评估的框架，该框架允许自动确定模型的质量和范围，因此可以覆盖较大的参数空间。我们计划使用机器学习技术对分析模型的校准和评估自动化。我们还旨在评估其复杂性以获得可行模型的建模方法。项目的结果应深入了解基于SDN的网络中不同处理管道的特征。考虑网络节点中的单独的数据包处理步骤，可以对组成的数据包处理链的性能发表可靠的语句。此外，增强的配置可能性导致了新的优化。

项目成果

Empirical Predictability Study of SDN Switches

• DOI: 10.1109/ancs.2019.8901878
• 发表时间: 2019-09
• 期刊: 2019 ACM/IEEE Symposium on Architectures for Networking and Communications Systems (ANCS)
• 作者: Amaury Van Bemten;N. Deric;Amir Varasteh;Andreas Blenk;S. Schmid;W. Kellerer

On the Impact of the Network Hypervisor on Virtual Network Performance

论Network Hypervisor对虚拟网络性能的影响

• DOI: 10.23919/ifipnetworking.2019.8816839
• 发表时间: 2019
• 期刊: 2019 IFIP Networking Conference (IFIP Networking)
• 作者: A. Blenk;A. Basta;W. Kellerer;S. Schmid
• 通讯作者: S. Schmid

A Framework for Reproducible Data Plane Performance Modeling

可重复数据平面性能建模框架

• DOI: 10.1145/3493425.3502756
• 发表时间: 2021
• 期刊: Proceedings of the Symposium on Architectures for Networking and Communications Systems
• 作者: D. Scholz;H. Harkous;S. Gallenmüller;H. Stubbe;M. Helm;B. Jaeger;N. Deric;E. Goshi;Z. Zhou;W. Kellerer;G. Carle
• 通讯作者: G. Carle

The pos framework: a methodology and toolchain for reproducible network experiments

pos 框架：可重复网络实验的方法和工具链

• DOI: 10.1145/3485983.3494841
• 发表时间: 2021
• 期刊: Proceedings of the 17th International Conference on emerging Networking EXperiments and Technologies
• 作者: S. Gallenmüller;D. Scholz;H. Stubbe;G. Carle
• 通讯作者: G. Carle

Cryptographic Hashing in P4 Data Planes

P4 数据平面中的加密哈希

• DOI: 10.1109/ancs.2019.8901886
• 发表时间: 2019
• 期刊: 2019 ACM/IEEE Symposium on Architectures for Networking and Communications Systems (ANCS)
• 作者: D. Scholz;A. Oeldemann;F. Geyer;S. Gallenmüller;H. Stubbe;T. Wild;A. Herkersdorf;G. Carle
• 通讯作者: G. Carle