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Model-based Analysis of Next-Generation Networks

下一代网络基于模型的分析

基本信息

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

项目摘要

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，计算机网络中的新范例，如网络功能虚拟化（NFV）、网络虚拟化（NV）和软件定义网络（SDN），将增加现代通信基础设施的灵活性和开放性。新方法将实现网络功能（NFV）的虚拟化、网络切片（NV）和网络（SDN）的（逻辑）集中控制，使得功能可以以物理解耦的方式实现，例如在数据中心中运行。SDN使新的方法来分析和控制网络中的流量，但是，需要深入了解底层硬件。虽然详细说明了精心设计的专用硬件的数据包处理管道，但商品硬件上的虚拟化软件更难处理。另一方面，通过虚拟化网络功能（NFV）（如自定义分组处理管道和动态布局）实现的额外自由度为优化创造了新的可能性。本项目旨在评估、联合收割机并增强与分组处理有关的网络及其组件的性能模型。新型网络的性能评估需要合适的建模工具，例如，以表示控制平面上的交互或考虑基于软件的数据包处理。新模型还需要考虑网络硬件的变化，这些变化描述了CPU互连或内存、PCIe或以太网带宽等限制因素的影响。我们的目标是将描述个体效应的联合收割机模型组合成更大的实体，从而可以对复杂的数据包处理任务进行建模。ModANet涵盖了各种性能分析方法，例如基于资源的模型，基于网络演算的模型和模拟。我们计划建立一个模型评估框架，它允许自动确定模型的质量和范围，从而能够覆盖大的参数空间。我们计划使用机器学习技术自动校准和评估分析模型。我们还旨在评估建模方法的复杂性，以获得可行的models.The项目的结果应该提供一个基于SDN的网络中的不同处理管道的特性的深刻理解。考虑网络节点中的单独的分组处理步骤允许对组成的分组处理链的性能做出可靠的陈述。此外，增强的配置可能性导致新的优化。

项目成果

期刊论文数量（8）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

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)
影响因子：
0
作者：
Amaury Van Bemten;N. Deric;Amir Varasteh;Andreas Blenk;S. Schmid;W. Kellerer
通讯作者：
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)
影响因子：
0
作者：
A. Blenk;A. Basta;W. Kellerer;S. Schmid
通讯作者：
S. Schmid

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)
影响因子：
0
作者：
D. Scholz;A. Oeldemann;F. Geyer;S. Gallenmüller;H. Stubbe;T. Wild;A. Herkersdorf;G. Carle
通讯作者：
G. Carle

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
影响因子：
0
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
影响因子：
0
作者：
S. Gallenmüller;D. Scholz;H. Stubbe;G. Carle
通讯作者：
G. Carle