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2023 IEEE 9th International Conference on Network Softwarization (NetSoft)最新文献

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ENS Workshop 实体工厂
Pub Date : 2023-06-19 DOI: 10.1109/netsoft57336.2023.10175504
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引用次数: 0
DataSlice Workshop DataSlice车间
Pub Date : 2023-06-19 DOI: 10.1109/netsoft57336.2023.10175500
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引用次数: 0
Design and Implementation of a Slice as a Service Architecture on the Edge Cloud with Resource Constraints 具有资源约束的边缘云上切片即服务架构的设计与实现
Pub Date : 2023-06-19 DOI: 10.1109/NetSoft57336.2023.10175502
Rodrigo Ferraz Azevedo, L. B. D. Paula, F. Verdi
Cloud Network Slicing (CNS) is a concept that describes a mechanism to provide computing, networking, and storage as a virtual slice entity, enabling new approaches to applications and structuring resources at the edge of the network. In this paper, the architecture defined in the NECOS Project is adopted, and the functions for creating CNS in resource-constrained edge devices were designed and implemented. The implementation was evaluated on Single Board Computers (SBCs), using lightweight virtualization solutions (microservices) and the results achieved show that it is possible to instantiate CNSs on that hardware, however, also show some limitations of multiple slice support on resource-constrained devices.
云网络切片(CNS)是一个概念,它描述了一种以虚拟切片实体的形式提供计算、网络和存储的机制,为网络边缘的应用程序和结构化资源提供了新的方法。本文采用NECOS Project中定义的体系结构,设计并实现了在资源受限的边缘设备中创建CNS的功能。使用轻量级虚拟化解决方案(微服务)在单板计算机(sbc)上对实现进行了评估,获得的结果表明,在该硬件上实例化CNSs是可能的,然而,也显示了在资源受限设备上支持多片的一些限制。
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引用次数: 0
PVE-SDN Workshop PVE-SDN车间
Pub Date : 2023-06-19 DOI: 10.1109/netsoft57336.2023.10175432
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引用次数: 0
RESCue: A State-Disaggregated NFV System with Resilience, Elasticity, and State Consistency 救援:具有弹性、弹性和状态一致性的状态分解NFV系统
Pub Date : 2023-06-19 DOI: 10.1109/NetSoft57336.2023.10175485
Hao Jiang, Hyunseok Chang, S. Mukherjee, J. Merwe
State-disaggregated Network Function Virtualization (NFV) architectures decouple NF states from packet processing logic to achieve elasticity and resilience in stateful NFs. However, the existing state disaggregation approaches suffer from either poor NF performance due to frequent remote state access or potential inconsistencies in state updates when multiple NF instances concurrently access shared states. Moreover, they do not properly support state rejuvenation/expiration which is required for resource scalability of stateful NF operations. This paper presents a new state-disaggregated NFV system called RESCue that addresses these problems. RESCue handles remote state access differently for shared and private states. For efficient and consistent access of shared states, it leverages a lightweight custom control message protocol between NFs and a centralized state server. For private state access, it adopts a remote-paging-based interface to avoid introducing expensive blocking remote access within the critical path of NF packet processing. Finally, it utilizes non-blocking operations for state rejuvenation/expiration handling to minimize its performance overhead. Our evaluation of a RESCue prototype shows that it can handle NF scaling and failure recovery well, while supporting consistent state updates and state rejuvenation/expiration without compromising performance.
NFV (state - aggregated Network Function Virtualization)架构将NFV状态与数据包处理逻辑解耦,从而在有状态NFs中实现弹性和弹性。然而,现有的状态分解方法要么由于频繁的远程状态访问而导致NF性能较差,要么当多个NF实例并发访问共享状态时,状态更新可能不一致。此外,它们不能很好地支持状态恢复/过期,而这是有状态NF操作的资源可扩展性所必需的。本文提出了一种新的状态分解NFV系统,称为RESCue,以解决这些问题。RESCue以不同的方式处理共享状态和私有状态的远程状态访问。为了高效和一致地访问共享状态,它利用NFs和集中式状态服务器之间的轻量级自定义控制消息协议。对于私有状态访问,采用基于远程分页的接口,避免了在NF报文处理的关键路径上引入昂贵的阻塞远程访问。最后,它利用非阻塞操作进行状态恢复/过期处理,以最小化其性能开销。我们对RESCue原型的评估表明,它可以很好地处理NF缩放和故障恢复,同时支持一致的状态更新和状态恢复/过期,而不会影响性能。
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引用次数: 0
SecSoft Workshop SecSoft车间
Pub Date : 2023-06-19 DOI: 10.1109/netsoft57336.2023.10175427
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引用次数: 0
Demo: FoReCo – a forecast-based recovery mechanism for real-time remote control of robotic manipulators 演示:FoReCo——一种基于预测的机器人实时远程控制恢复机制
Pub Date : 2023-06-19 DOI: 10.1109/NetSoft57336.2023.10175434
Pablo Picazo-Martínez, Carlos Barroso-Fernández, Jorge Martín-Pérez
In this demonstration, FoReCo is introduced as a solution for recovering lost control commands in remotely controlled robots. Visitors are given the opportunity to remotely control a robotic arm using a joystick, with the added challenge of experiencing packet losses in the wireless medium. The lost control commands cause the robotic arm’s trajectory to become distorted. To combat this issue, FoReCo is implemented and utilizes an ML model that has been trained on a real-world dataset to recover the lost control commands. The demonstration illustrates how FoReCo recovers the lost commands, resulting in the robotic arm operating smoothly despite the presence of wireless medium losses.
在本演示中,介绍了FoReCo作为远程控制机器人中恢复失去控制命令的解决方案。参观者有机会使用操纵杆远程控制机械臂,同时还面临着在无线介质中经历数据包丢失的挑战。失去控制的指令导致机械臂的轨迹变得扭曲。为了解决这个问题,我们实现了FoReCo,并利用了一个在真实数据集上训练过的ML模型来恢复丢失的控制命令。该演示演示了FoReCo如何恢复丢失的指令,从而使机器人手臂在无线介质丢失的情况下仍能平稳运行。
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引用次数: 0
Autonomous Network Management in Multi-Domain 6G Networks based on Graph Neural Networks 基于图神经网络的多域6G网络自治网络管理
Pub Date : 2023-06-19 DOI: 10.1109/NetSoft57336.2023.10175480
Kaan Aykurt, W. Kellerer
Sixth-generation (6G) networks propose integrating multiple networks and domains while improving network performance. Hence, today’s networks are becoming increasingly larger and more complex. Traditional methods to manage networks are facing significant challenges as the topology sizes, traffic patterns, and network domains are changing.This paper presents the state-of-the-art in literature for network management and proposes a research plan for an autonomous network management framework fueled by the Digital Twin (DT) paradigm. Unlike the existing methods such as Queuing Theory (QT) or network simulation studies, the proposed framework relies on state-of-the-art Graph Neural Networks (GNNs) for network performance analysis. We argue that seamless integration of networks while improving performance guarantees can be achieved via autonomous management of networks and present a research plan in this paper.
第六代(6G)网络在提高网络性能的同时,提出了集成多个网络和多个域的方案。因此,今天的网络正变得越来越大,越来越复杂。随着网络拓扑规模、网络流量模式和网络域的不断变化,传统的网络管理方法面临着巨大的挑战。本文介绍了网络管理的最新文献,并提出了一个由数字孪生(DT)范式推动的自主网络管理框架的研究计划。与排队论(QT)或网络仿真研究等现有方法不同,所提出的框架依赖于最先进的图神经网络(gnn)进行网络性能分析。我们认为通过网络的自治管理可以实现网络的无缝集成,同时提高性能保证,并提出了研究计划。
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引用次数: 0
Understanding Roadblocks in Virtual Network I/O: A Comprehensive Analysis of CPU Cache Usage 理解虚拟网络I/O中的障碍:CPU缓存使用的综合分析
Pub Date : 2023-06-19 DOI: 10.1109/NetSoft57336.2023.10175477
Daichi Takeya, Ryota Kawashima, Hiroki Nakayama, Tsunemasa Hayashi, H. Matsuo
One big challenge in cloud-native network functions (CNFs) is the poor performance of packet forwarding. In this paper, we comprehensively analyze CPU cache usage in regard to the interprocess communication (vhost-user) as well as the packet I/O framework (DPDK). We cover four high-end CPUs, and examine 141 implementation/configuration patterns on an EIVU (Essential Implementation of Vhost-User) platform to clarify how the patterns affect the cache behaviors. The result pinpoints the roadblocks in a generalized form; cache invalidations stemming from three design/implementation factors are the major bottle-necks in vhost-user/DPDK, and shows potential of 100+ Mpps container networking for future software-centric environment.
云原生网络功能(cnf)面临的一大挑战是数据包转发性能差。在本文中,我们全面分析了进程间通信(vhost-user)以及包I/O框架(DPDK)的CPU缓存使用情况。我们将介绍四个高端cpu,并研究EIVU (Vhost-User的基本实现)平台上的141种实现/配置模式,以阐明这些模式如何影响缓存行为。结果以广义形式指出了障碍;源于三个设计/实现因素的缓存失效是vhost-user/DPDK的主要瓶颈,它显示了未来以软件为中心的环境中100+ Mpps容器网络的潜力。
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引用次数: 0
NetSoft 2023 Cover Page NetSoft 2023封面页
Pub Date : 2023-06-19 DOI: 10.1109/netsoft57336.2023.10175460
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引用次数: 0
期刊
2023 IEEE 9th International Conference on Network Softwarization (NetSoft)
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